We’re witnessing the rise of a new wave of intelligent applications reshaping how organizations operate, embedding real-time data and critical operational context with AI models to enable swift and thoughtful decisions. Unlike traditional software that is governed by rigid business rules, these modern applications can learn and adapt to rapidly evolving customer and market demands 鈥� detecting changes to optimize processes, anticipate needs, and collaborate with both human and artificial “thinkers” to create competitive advantage for an organization. 

Yet, we stand at the cusp of a bolder wave of innovation, one that unfortunately only the discerning few organizations may fully harness. Despite the vast potential of AI and cloud technologies, their true impact hinges on using these innovations with the secure and semantically rich data that is vastly available within an organization. 

Transform outcomes with intelligent applications

This year at 麻豆原创 Sapphire, we unveiled a significant expansion of 麻豆原创 Business Data Cloud to deliver on the promise of intelligent applications: prebuilt, composable applications that seamlessly integrate trusted data products, AI capabilities, and business simulations to serve the needs of every business leader.

These intelligent applications are not just analytics tools; they transcend traditional analytics by automating and orchestrating work across both analytical and transactional workflows, enabling customers to make decisions and execute actions within 麻豆原创 Business Data Cloud.

Today, we are introducing new intelligent application capabilities in 麻豆原创 Business Data Cloud, starting with People Intelligence, an offering grounded in workforce composition, skills, and compensation data products. Built on data from 麻豆原创 SuccessFactors software, People Intelligence provides HR and business leaders with AI-driven recommendations to optimize talent decisions, drive engagement, and ensure compliance. It features capabilities such as workforce composition insights, compensation insights, and skill insights, all available in the second half of 2025.

Additional intelligent application capabilities in 麻豆原创 Business Data Cloud that are entering technology preview include: 

• Cloud ERP Intelligence: Empowers leaders with transformative insights, business simulations, and AI capabilities to manage uncertainty, drive profitability, and meet sustainability goals. These capabilities include new data products from key business processes such as manufacturing (production execution, resource optimization, etc.), supply chain (inventory, deliveries. etc.), and contract accounting (payments, billing, etc.). 
• Customer Intelligence: Guide sales, service, marketing, and commerce teams with a 360-degree customer view to anticipate needs, improve targeting, and build a comprehensive customer profile.  
• Finance Intelligence: Provides CFOs and finance teams with real-time forecasting and planning, connected data across systems, and AI-powered anomaly detection. 
• Spend Intelligence: Delivers procurement and operations leaders real-time spend visibility to minimize supplier risk, flag spend outliers, and reduce costs.

Each intelligent application in 麻豆原创 Business Data Cloud is underpinned by curated, governed data products, sets of structured business data and metadata designed to accelerate use cases and reduce data integration overhead. And with 麻豆原创 Databricks natively available in 麻豆原创 Business Data Cloud, users can leverage 麻豆原创 data products with existing lakehouses with a zero-copy approach.

As part of these technology previews, we are also announcing the delivery of hundreds of new data products throughout 2025 across all 麻豆原创 Business Suite domains 鈥� from inventory optimization and delivery analysis to sustainability and compliance data products. The first wave includes new environmental, health, and safety (EHS) and product compliance datasets, with sustainability footprint data to follow later in the year. 

Amplify the value of AI with your most powerful data

In addition, 麻豆原创 Business Data Cloud is expanding its knowledge graph capabilities. Originally launched within 麻豆原创 Datasphere, the knowledge graph can now ingest and map metadata across 麻豆原创 and external sources, and seamlessly consume models published in 麻豆原创 Knowledge Graph on 麻豆原创 BTP. This creates a living model of how business data is structured and connected, providing a semantic backbone for AI to operate with higher precision.

Paired with Joule in 麻豆原创 Business Data Cloud, now generally available, users can engage with complex business data as naturally as they think, without the constraints of traditional technology. Joule unlocks the full richness of enterprise information, empowering people across the organization to navigate, reason, and act with intelligence grounded in real business context.

Open data ecosystem: Expanding intelligence beyond 麻豆原创

We are also making 麻豆原创 Business Data Cloud more accessible to power the next generation of intelligent, multi-cloud applications.

Starting in the second quarter, 麻豆原创 Business Data Cloud is available on AWS, with Google Cloud and Microsoft Azure expected to follow in the second half of 2025. This makes 麻豆原创鈥檚 data foundation more accessible and deployable within multi-cloud strategies, giving customers the flexibility to run intelligent workloads wherever they operate. 

At the same time, 麻豆原创 is actively collaborating with leading partners to build the next wave of intelligent applications.

• Accenture will release six intelligent applications addressing key challenges in supply chain, talent, finance, and procurement (GA timeline pending). 
• Adobe and 麻豆原创 are co-developing an application that fuses Adobe鈥檚 marketing data with 麻豆原创鈥檚 financial and supply chain data, enabling real-time alignment between demand signals and operational planning, expected in late 2025. 
• Palantir and 麻豆原创 are partnering to facilitate joint customers鈥� cloud migration journey and modernization programs. Seamless connectivity between Palantir and 麻豆原创 Business Data Cloud will enable customers to build a harmonized data foundation across their enterprise landscape. 麻豆原创 Business Data Cloud and Palantir Foundry and AIP will transform data silos into a trusted data foundation that enables human + AI teaming in the real world. Together the companies will responsibly deliver essential outcomes and support customers, including the U.S. government, to quickly adapt to changes and disruptions.
• Thomson Reuters will develop an intelligent application to help customers navigate the fast-moving challenges in the current global trade and tariffs environment, planned for end of 2025.
• Joint Collibra and 麻豆原创 Business Data Cloud customers can now run up to 10x more active data quality jobs in Collibra Data Quality & Observability when run on 麻豆原创 BDC data, at no additional cost. This limited time offer helps accelerate decision-making, strengthen compliance, and improve AI readiness, and is available until May 30, 2026.

The scope of partner collaboration also extends to data enrichment use cases. A new partnership with 惭辞辞诲测鈥檚 will let our joint customers blend 麻豆原创鈥檚 accounts receivable data with 惭辞辞诲测鈥檚 risk datasets to enhance cash flow forecasting, prioritize collections, and reduce exposure to bad debt. This solution is scheduled for general availability in the fourth quarter of 2025. 

We鈥檙e excited to partner with our customers and ecosystem to unlock a new generation of intelligent applications in 麻豆原创 Business Data Cloud, where trusted data, AI, and business context come together to drive meaningful change. The future of modern business will belong to those who turn intelligence into action.

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• featuring the latest on data products and intelligent applications in 麻豆原创 Business Data Cloud

Irfan Khan is president and chief product officer of Data and Analytics at 麻豆原创.

Edgewell鈥檚 portfolio of more than 25 well-known personal care brands, including Schick, Banana Boat, Wilkinson Sword, and Wet Ones, drove . The company relies on a people-first culture that enables the right environment for employees to be efficient and the company at large to 鈥渨in the shelf,鈥� as Colin Emery, director of Global HR Systems at Edgewell, puts it.聽

In 2022, Emery was tasked with establishing a People Analytics function at Edgewell, but he quickly realized that the underlying data he needed was inaccurate. 鈥淥ur system of record was no longer the system of record. We didn鈥檛 actually have one,鈥� Emery explains. At that time, the company鈥檚 HR data accuracy was just 37% for key data fields within the Position and People Profile. 

Since Edgewell was formed in 2015, Emery says, it has relied on the 鈥渋nfinite configurability鈥� of to scale, systemize, and standardize the company鈥檚 HR systems across the world. While the solutions were working as designed, the data housed in them wasn鈥檛 being maintained properly, causing a backlog of inaccuracies to flow downstream. 鈥淚t was clear that the quality of our data within 麻豆原创 SuccessFactors was less than perfect in some parts of the world, particularly in countries where we don鈥檛 have 麻豆原创 SuccessFactors Payroll integrated,鈥� he says.

Knowing that high data quality is crucial for effective decision-making, reporting accuracy, a painless user experience, and future innovation鈥攂ut not having the budget or time to engage external resources鈥擡mery decided to develop Edgewell鈥檚 methodology in-house to tackle the issue.

Upskilling to establish HR data champions

After identifying the priority data fields that needed to be cleaned and maintained to have the most impact on data quality, Emery turned to the people who owned and best understood the data: the HR business partners (HRBPs). To ensure the success of the data quality project, the HRBPs needed to buy in. This required a mindset shift and significant change management, he says, since not all HRBPs felt responsible for maintaining the data in the 麻豆原创 SuccessFactors solutions and some needed training to understand systemized HR processes. 

To help with the transition, Emery established an HR data steward program to upskill Edgewell鈥檚 HRBP community. Designated data stewards receive weekly reports and are tasked with personally resolving the data errors or informing an appropriate colleague. They are trained on the causes and consequences of the inaccuracies and how to remedy them, empowering the data stewards to become experts and educate other HRBPs. Upskilling the HRBPs helped them shift from a reactive to a more proactive mindset, which was a critical factor in the data quality project鈥檚 success, Emery says. 

Case in point: the number of data inaccuracies has decreased from 2,700 to just a handful. 鈥淚t鈥檚 a tiny, tiny fraction of what it was,鈥� Emery says. 鈥淭hat鈥檚 based on the fact that the HRBPs are getting it right the first time, instead of making errors that need to be fixed.鈥�

The project began in the U.S. and eventually flowed to Europe, LATAM, and APAC. Now, Edgewell鈥檚 data accuracy consistently holds at 96%鈥�97%, Emery says.

Quality data drives quality decision-making

The success of its data quality and data steward project is clear, and now Edgewell can reap the rewards of a clean HR data foundation. This has had profound effects on the reliability of the company鈥檚 HR reporting, for which Edgewell uses stories in 麻豆原创 SuccessFactors solutions. 鈥淭here’s a massive advantage to using stories when we’re using live, in-the-moment 麻豆原创 SuccessFactors data,鈥� Emery says, adding that the ability to send a link that is accessible based on existing role-based permissions makes sharing the data simple and fast. Edgewell uses stories to look at data around inclusion and belonging, leadership, tenure, talent acquisition, and more, sharing the insights with company leadership, HR leaders, and HRBPs.

This data-driven culture has helped Edgewell identify areas of improvement and make strategic HR decisions. For example, in looking at the data, the People Analytics team uncovered a short-term turnover issue for specific roles and locations. Based on this insight, Edgewell鈥檚 HR function created a new candidate experience to help improve and systemize recruiting and onboarding processes. Called 鈥淛oyful Journey,鈥� the program also doubles as a way for the company to share about itself and attract talent to the organization. 鈥淲e never would have known that was the right thing to do without the data,鈥� Emery says. 鈥淭hat then led us to invest time, effort, and dollars in those processes, which immediately made a positive impact on short-term turnover.鈥�

鈥淥ver the last three years, we have been providing data and explaining its importance by cleaning up the data within the system to make it more meaningful to us,鈥� Emery adds. 鈥淔or us, it鈥檚 never going to be data for data鈥檚 sake. It has to be about what the actions that this data suggests.鈥�

Ready for the future

Not only does Edgewell鈥檚 impressive data quality equip its leaders with actionable insights, but it creates a strong foundation for the personal care company to take advantage of HR innovations, especially considering that many, like AI, require clean data to work properly. AI copilots and agents, like , are only as good as the data they run on, which is why data quality and data governance initiatives are becoming business imperatives.聽

In that case, Edgewell is ahead of the curve. 鈥淲hen I started working on People Analytics three years ago, I knew that we had to focus on [cleaning up the data] first to prepare for super automation and the AI tools that were coming,鈥� Emery says. 鈥淚t will set us up in good stead for the next iteration of tools.鈥�

Gillian Hixson is an integrated communications specialist at 麻豆原创.

A recent survey reported that cognitive skills, such as creative thinking, analytical thinking, and technology literacy, a type of critical thinking skill, are forecast to be the most sought-after employee skills by 2027.

Collaboration between academia and industry is essential to deliver these skills at speed to students. That鈥檚 why the has been forging partnerships with educational institutions for 25 years, with more than 2,800 institutions currently working with 麻豆原创 to educate tomorrow鈥檚 talent with 麻豆原创 skills.

One of these partners is , a prestigious, internationally recognized business school with a long history of creating innovative learning approaches to equip students with 麻豆原创 skills.

Two decades ago, HEC Montr茅al pioneered , a revolutionary and hugely successful educational tool immersing students in a real-life business scenario within 麻豆原创. Today, an estimated 30,000 students a year learn with ERPsim.

In an interview, Professor Pierre-Majorique L茅ger of HEC Montr茅al talked about the latest collaboration between HEC Montr茅al and 麻豆原创: Business Builders, the next generation of 麻豆原创 gamified learning.

Business Builders: Game On with 麻豆原创 Analytics Cloud

Business Builders is a gamified learning tool that can develop STEM skills and helps students sharpen their analytical, critical, and creative thinking skills using the solution.

Professor L茅ger says educators are caught up in the generative AI tsunami and need to 鈥渞ethink a new pedagogical approach for students to develop data analytics and data literacy skills while at the same time recognizing that ChatGPT, for example, makes it super easy for students to circumvent doing the tasks themselves.鈥�

Business Builders is one solution to that problem.

The game can be played either face-to-face or in virtual teaching sessions, either synchronously in a single session or over several sessions.

Students find themselves in one of three scenarios in a fast-paced, competitive game with interactive, realistic learning scenarios. There is no chance of resorting to ChatGPT or a similar AI tool to win. Instead, students must demonstrate data-driven decision-making skills and apply visualization techniques to make informed decisions.

In each game, students take on roles such as marketing or product researcher, financial analyst, or supply chain analyst. Each game has multiple stages, with subsequent stages demanding greater skills and knowledge.

The stages comprise 10 business questions targeting different levels of skills and knowledge. The business questions are designed for students with little or no data analytics skills as well as those with more advanced data visualization and manipulation skills.

As part of the game, students use 麻豆原创 Analytics Cloud to visually analyze the data and identify the best graphical representations to answer the questions.

Real-Life Problems with Realistic Data

The game uses vast synthetic data sets to make the business decision-making process as authentic as possible. 鈥淭he notion of synthetic data is important,鈥� Professor L茅ger explains, 鈥渂ecause sometimes reality is too complex to bring into the classroom and does not serve the pedagogical process. Based on experience with ERPsim, creating a realistic synthetic data set that is as close as possible to reality is the best way to go.鈥�

Business Builders currently offers three game scenarios offering a diverse range of real-life problems that students can solve using 麻豆原创 Analytics Cloud: environmental, social, and governance; supply chain resilience; and international expansion.

According to HEC Montr茅al, the most-played scenario to date is supply chain resilience. This scenario involves a real-life problem where the Panama Canal gets shut down due to climate change, affecting the shipment of holiday gifts from Southeast Asia to the United States. Students are tasked with deciding how to reroute the containers and prioritize products to minimize the impact of this event.

A Win-Win for Students, Educators, and Employers

鈥淚t is the challenge of our generation of professors faced with generative AI to come up with a novel way to teach students about data analytics,鈥� Professor L茅ger says. 鈥淲e have found a way of using gamification to engage students in leveraging what they know about analytics and mathematics to become business builders. Using data to get insights and solving problems on the best technology that exists 鈥� 麻豆原创 Analytics Cloud. And the best thing of all, it鈥檚 free for lecturers and their students around the world.鈥�

To guide students through the game scenario questions and help optimize the learning experience, educators have access to tailor-made training materials. Instead of taking a hit-and-miss approach with the data and platform features, these tailor-made training materials help lecturers deepen the learning experience. Students can understand how insights are uncovered and how to make informed business decisions based on analysis of data sets and data visualizations.

麻豆原创 has also created a handbook about the basic concepts of data visualization and storytelling in 麻豆原创 Analytics Cloud. Available in a slide-deck format, educators can refer to the theoretical aspects while students are getting hands-on practical experience in 麻豆原创 Analytics Cloud.

Since its launch in July 2024, more than 300 educational institutions have registered for access to the Business Builders game and an anticipated 2,500 students will use 麻豆原创 Analytics Cloud to compete with their peers in the game by the end 2024.

With technology accelerating at an ever-increasing speed, the good news is that educators can register and get up and running with Business Builders free of charge in a just matter of days. Find out how on the website.

That is where effective data integration tools come into play. These tools allow organizations to efficiently connect, manage, and orchestrate their data assets.

Data integration solutions from 麻豆原创 鈥� including 麻豆原创 Datasphere, 麻豆原创 Data Intelligence Cloud, 麻豆原创 Data Services, and 麻豆原创 Landscape Transformation Replication Server 鈥� provide customers with timely, relevant, and trusted information, simplifying their data landscapes and unlocking valuable business insights.

麻豆原创’s Recognition

Gartner庐 recently evaluated 20 vendors in the 2024 Magic Quadrant™ for Data Integration Tools, recognizing 麻豆原创 as a Leader for our 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision.鈥�

We believe this recognition underscores 麻豆原创鈥檚 commitment to delivering innovative, world-class data integration tools that empower our customers and marks 17 consecutive years as a Leader.

Business Data Fabric

Effective data integration is fundamental for gaining actionable insights that drive better decision-making. Without the right tools and strategies, organizations struggle to integrate, process, curate, govern, and enhance their data.

麻豆原创 takes a business data fabric approach, which goes beyond a traditional data fabric. A business data fabric is a data management architecture that delivers an integrated, semantically rich data layer over underlying data landscapes to provide users with scalable access to their data without duplication.

This eliminates the need to recreate the business context that was lost from extracting and replicating data. It gives users the ability to accelerate their decision-making with trust and confidence, knowing they always have the complete picture of their data, regardless of where it is stored or how it was designed.

麻豆原创 Datasphere

麻豆原创 Datasphere 鈥� along with its open data ecosystem 鈥� is the foundation for a business data fabric. It equips any organization to deliver meaningful data to every data consumer 鈥� with business context and logic intact. 麻豆原创 Datasphere helps customers:

• Access authoritative data: Accelerate time to value by automatically reusing the semantic definitions and associations from 麻豆原创 applications
• Enrich all data projects: Harmonize heterogeneous data into a business semantic model of diverse data landscape
• Simplify the data landscape: Access all data across hybrid and cloud environments no matter where it resides

With a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization, 麻豆原创 Datasphere enables data professionals to easily distribute authoritative business data 鈥� with business context and logic preserved 鈥� across the data landscape.

麻豆原创 Datasphere advances data management with innovations like knowledge graph which uncovers hidden insights by revealing deep relationships between data, metadata, and business processes. The knowledge graph can then be used with Joule, 麻豆原创鈥檚 generative AI co-pilot, allowing business users to ask both open-ended and specific questions and get instant and well-documented answers.

By leveraging these capabilities within a business data fabric powered by 麻豆原创 Datasphere, organizations can save up to 138%.

Real-World Success

Since its launch, 麻豆原创 Datasphere has seen widespread adoption and innovation. Companies like have experienced transformative benefits.

Frode N忙ss Larsen, CIO at POWER International AS, highlights their experience: 鈥淭he 麻豆原创 Datasphere solution is intuitive and simple in terms of data movement from on premise to a cloud environment. The solution helps simplify our data landscape, saving hundreds of hours every year in pipeline development. They say the best run 麻豆原创, so for us, it鈥檚 a good match.鈥�

Get Started

For more than 17 years, 麻豆原创 has been at the forefront of data integration, helping customers convert fragmented data into actionable insights.

Join the movement and unlock the full potential of your business data with 麻豆原创鈥檚 leading data integration solutions. Take the next step in your data integration journey:

• Visit the
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Daniel Yu is senior vice president of Product Marketing for 麻豆原创 Data and Analytics at 麻豆原创.

Gartner, Magic Quadrant for Data Integration Tools, Thornton Craig, Sharat Menon, Robert Thanaraj, Michele Launi, Nina Showell, 3 December 2024
Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner鈥檚 Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.

Sights Set on the European Championship

鈥�麻豆原创 Sports One enables us to efficiently share tactical insights and key information about our next opponents with our players. And by accessing the software on a tablet, we can even give them the latest updates in the changing room shortly before kickoff or at half time,鈥� says Benjamin Gl眉ck, assistant coach to the German national A-team.

鈥溌槎乖粹�檚 sports management suite is very important to the national soccer team as a central platform for collecting and analyzing data and for presenting the insights gained from that data to our players,鈥� explains Gl眉ck. 鈥淲e use the video and visualization functions in 麻豆原创 Sports One to help us illustrate findings about our opponents and their key players. These features make conveying tactics and preparing for specific matches much easier and clearer.鈥� The German team also uses analytical insights to prepare for penalty scenarios. In 麻豆原创 Penalty Insights, goalkeepers can study the behavior of potential penalty-takers, such as which area of the goal they usually aim for and even how these preferences change under pressure. Conversely, penalty-takers can gain insights into the tactics of their opponents鈥� goalkeepers.

The coaches and analysts of the German Football Association (Deutscher Fu脽ball-Bund, or DFB) work with data created within 麻豆原创 Sports One as well as data and analyses from third-party sources. The 麻豆原创 solution serves as the central platform for consolidating and analyzing all the data.

An 麻豆原创 App for All Players

Germany鈥檚 national players stay in close contact with their coaches and analysts through the 麻豆原创 Sports One messaging app 鈥� 麻豆原创 Team One 鈥� which they have on their phones. Among other things, the mobile app is used to pass on match preparation information, such as opponent analyses, annotated clips, and videos.

The players also use the mobile app to share information about themselves. For example, they complete questionnaires about how intense they perceived the last training session or match, how well they slept, and how they are feeling overall. Their responses are used to generate an RPE (rating of perceived exertion) value. By gauging each player鈥檚 general health and well-being in this way, coaches can manage intensity levels according to each individual鈥檚 situation. Both the DFB and the player鈥檚 home club monitor this RPE value to guard against overtraining and injury. 麻豆原创 Analytics Cloud can draw on data from 麻豆原创 Sports One to create player-specific reports that are forwarded to the player鈥檚 home club after courses, tournaments, and matches the German team takes part in.

DFB and 麻豆原创: An Established Partnership

The DFB is a familiar name around the globe. With almost 7 million members spread across more than 25,000 clubs, it is the world鈥檚 largest national sports federation. At the World Cup in Brazil in 2014, which Germany won, the country鈥檚 national team was already using 麻豆原创 Match Insights, a prototype of the solution that is now part of 麻豆原创 Sports One. This prototype helped the DFB evaluate large volumes of data for match analysis for the first time.

Today, more than 1,000 DFB users 鈥� players and the 鈥渢eams behind the teams鈥� 鈥� work with 麻豆原创 Sports One. 鈥淥ur successful collaboration with the German national team was a key factor in 麻豆原创鈥檚 decision to turn the prototype we developed for the DFB into a standard product. Now, clubs and associations in 19 countries are using 麻豆原创 Sports One,鈥� says Fadi Naoum, senior vice president and head of Development, 麻豆原创 Sports One. More joint projects followed, including the development of 麻豆原创 Penalty Insights and 麻豆原创 Challenger Insights, a mobile app that helps teams prepare for upcoming matches. On the horizon of this co-innovation partnership are plans to leverage the power of AI to make the functions in 麻豆原创 Sports One even more efficient.

Shaping the Future

In addition to Germany鈥檚 national men鈥檚 and women鈥檚 soccer A-teams, the DFB manages 12 junior and U21 teams, too. 鈥淭he challenge for us is to keep a close eye on the pool of talented young players we have and to help them reach their full potential,鈥� says Christofer Clemens, the DFB鈥檚 head of Scouting, Match Analysis, and Diagnosis. 鈥淥ur coaching teams watch an average of 1,500 games every season and identify a large number of gifted talents in the process. To qualify these players, the coaching teams compile a huge volume of scouting reports, which we manage in 麻豆原创 Sports One. These qualitative insights are vital for us. However, at the moment, the task of judging the development of a player or comparing individual players based on that information is time-consuming,鈥� says Clemens. 鈥淲e鈥檙e hoping that AI will make the complex task of analyzing these vast amounts of data much simpler for us.鈥� Alongside scouting reports, the DFB plans to use publicly available data sources and match statistics to complete player profiles.

鈥淎nother area where the DFB sees enormous potential for AI is in analyzing opponents before international matches,鈥� says Martin Vogelbein, a member of the DFB鈥檚 Scouting, Match Analysis, and Diagnosis team and project lead in managing the 麻豆原创 Sports One solution. 麻豆原创 Sports One is already helping the DFB prepare for big games, he explains, but the plan is to go a step further and use AI to automatically analyze insights from opponents鈥� past matches.

鈥淲e are hoping that 麻豆原创鈥檚 AI copilot, , will bring enormous benefits in terms of consolidating match reports. That would minimize the manual tasks our match analysts need to complete and reduce the time it takes to get answers to a range of key questions we have when preparing for games,鈥� says Vogelbein. Typical questions are: What patterns are visible in the opposing team in different phases of the match? What does this tell us about the team鈥檚 strengths, weaknesses, and about the options we have? 鈥淲e already have a huge amount of information 鈥� particularly qualitative data 鈥� available to us before games. 麻豆原创 Challenger Insights, a component of 麻豆原创 Sports One, allows us to visualize insights from that information and discuss them with the team. But, looking ahead, AI-driven analyses could help us prepare key background information for our players even more easily,鈥� says Vogelbein.

Clemens and Vogelbein are very pleased with the results so far. 鈥淲e see enormous potential in our work with 麻豆原创 on the AI-driven evaluation of information that is relevant for scouting and match analysis. The prototypes 麻豆原创 has presented to the DFB look very promising, and we are looking forward to using them live soon.鈥�

Top image courtesy of Thomas B枚cker

For decades, our partners have leveraged their industry expertise and technological know-how to bring immense value to companies of all sizes. They possess a rare fusion of deep industry insights and technological expertise, which they leverage to guide businesses through the delicate process of modernization while ensuring that the essence of their identity remains intact.

We recently how they鈥檙e helping customers take better advantage of their organization鈥檚 data. Our partners have observed a significant shift in the way data is perceived and utilized. It’s no longer just a byproduct of business operations but a core asset that, when effectively distributed and made accessible, can revolutionize customer experiences and enable a more strategic, company-wide approach to decision-making.

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However, the mere availability of data is not a panacea. The crux of the matter is transforming data into actionable insights. This is where our partners excel, mapping out advanced use cases and facilitating the transition to cutting-edge platforms like 麻豆原创 Datasphere and 麻豆原创 Analytics Cloud. These solutions can empower organizations to evolve into entities where data is not just present but central to every action and decision.

The practical implications of data are vast and deeply rooted in the operational successes of our clients. AI, for instance, is a frontier rich with potential, but its success is inextricably linked to the quality and accessibility of data. Recognizing this, 麻豆原创 partners are investing in building AI capabilities that can not only propel new business functions but also deliver substantial value.

Another key area of focus for our partners is the concept of a business data fabric, which is critical in developing a flexible enterprise architecture. Such an architecture allows for co-innovation and customization of solutions, ensuring that data is not just an afterthought but a driving force in business operations.

The journey toward a data- and AI-centric business model is an ongoing one, marked by evolving needs, emerging challenges, and a relentless pursuit of innovation. The ultimate aim is to convert potential into lasting business success.

The essence of our relationship with our partners is rooted in a shared vision. We are united in our pursuit of discovery, innovation, and improvement as we navigate the future together. Be sure to with our seven strategic partners and discover how the can help your company become a data-driven organization.

Karl Fahrbach is chief partner officer at 麻豆原创.

Consider this: your business implements new software intended to speed up processes but finds out that your processes are instead stalling. Why? Because your employees never fully adopted the solutions. Now you may ultimately decide to stop using that software. To avoid this scenario, more and more software vendors are turning to an adoption-focused mindset that empowers customers to make the most of their software investments.

In fact, . Yet, only one-third of software vendors on the market have a documented adoption framework to assess how well specific customers are adopting their technology. Enter telemetry, which can help organizations make more informed decisions, optimize business processes, and realize the full potential of emerging technologies.

Telemetry Helps Us Help You

Telemetry often refers to the automatic collection of data measurements from physical equipment. Telemetry has had profound impacts on Industry 4.0, as it鈥檚 adopted by not only manufacturers but also by any business that uses virtually any kind of equipment. But with the advent of artificial intelligence (AI) and its seamless integration into many cloud applications, companies from all industries can consume AI-driven insights and capabilities. These innovations are transforming the way businesses operate, creating new opportunities, and driving efficiencies.

Increasingly though, telemetry is also helping software vendors gather data on the performance and use of their customers鈥� deployments of their software. This includes 麻豆原创. Just like Industry 4.0 data analytics help your business optimize equipment, telemetry from your 麻豆原创 software helps us see where you could best use our solutions to meet your unique goals, how it can be optimized, and where further enhancements may be necessary.

The ever-expanding landscape of intelligent software and next-generation technology has opened many new doors for businesses, but all these opportunities can be overwhelming and even confusing. Telemetry empowers software vendors 鈥� including 麻豆原创 鈥� to help their customers understand the full potential presented by new software solutions.

Telemetry-Driven Customer Success

Telemetry is a game-changer in the realm of customer success. It provides a more accurate, near-real-time look at how software investments are performing. For software vendors, telemetry鈥檚 greatest advantages to help our customers include:

• Identifying user patterns: Telemetry can provide a real look at user behavior with our software. By tracking navigation patterns and time spent on specific tasks, we can gain a comprehensive understanding of how your users work every day 鈥� and how they should work instead. With this insight, businesses can make data-driven decisions to enhance user experiences and drive greater adoption, which drives greater value.
• Optimizing business processes and performance: Using telemetry, we can see how your software is performing across environments. It helps us discover process bottlenecks, frequently occurring errors, and system resource usage. With these insights, we鈥檙e better prepared to help you find out what processes simply aren鈥檛 working and why.
• Analyzing feature use: Find out what features are most popular among your users 鈥� and which ones aren鈥檛. Using this information, we can encourage users to take advantage of the features you鈥檝e implemented or implement new ones that help users work more efficiently.
• Predictive analytics: Telemetry data can be leveraged to create predictive models, anticipating potential issues or opportunities before they arise. This can help businesses stay one step ahead, ensuring smooth technology adoption and minimizing disruptions.

Telemetry serves as a source of 360-degree signal interpretation, and it provides you with opportunities for intervention in the moments that matter most. Building off the above benefits, you can use telemetry to take advantage of predictive analytics for feature development, feedback-driven iterations, and customized user training.

Bridge the 鈥淗ype-Reality鈥� Gap

Telemetry and data analysis are helping us help our customers solve arguably the greatest threat to solution adoption: the 鈥渉ype-reality鈥� gap. Often, businesses hype up their latest software investment to users, claiming they鈥檒l save employees time and effort. But when users don鈥檛 see results, they get disappointed 鈥� and they stop using the new software. Telemetry, by providing insight into how real users have been using your new software, is a critical way to show real-time results and get the entire business on board.

In addition, telemetry builds on the increasing value of partnership between software vendors and their customers. By harnessing the power of real-time insights right from our customers鈥� own deployments of our software, we鈥檙e better prepared to steer the future of our software toward outcomes that support our customers. As organizations combine telemetry with advances in generative AI, they have a powerful tool at their disposal to drive customer technology adoption and success with data-driven insights.

Claudio Muruzabal is chief business officer at 麻豆原创.

Global specialty materials company overcame its HR reporting challenges by implementing story reports in 麻豆原创 SuccessFactors solutions, making its reporting easier and more efficient. For example, a standard talent report 鈥� once a labor-intensive task that took several days of precious time 鈥� is now generated in under two hours complete with detailed graphics that are continuously updated with live data. Indeed, an 麻豆原创 found that with the analytics tools available in 麻豆原创 SuccessFactors solutions, customers reported a 74% decrease in time spent on report generation, saving days and even weeks on HR reporting.  

鈥淭he ability to give our [HR] information to leaders as they need it is huge,鈥� says Nina Nabors, manager of Talent Systems, Eastman. She summarizes the transformation in improvement over past reporting methods. 鈥淏efore, it was lagging data. It was never data that was live. Having that benefit of building the story report in 麻豆原创 SuccessFactors and it continuously updating with the latest information is very nice.鈥�

Based in Tennessee, U.S., Eastman Chemical Company was founded in 1920 as a subsidiary of Eastman Kodak. It has a workforce of 14,000 employees in 15 countries. Energized in its purpose to 鈥渆nhance the quality of life in a material way,鈥� Eastman engages with customers in 100 countries to deliver innovative materials found in items people use every day, including safe, durable medical materials; premium plastics for eyewear frames and lenses; food and beverage packaging; sustainable fibers for luxury home furnishings; and energy-efficient window glass for the construction industry, among others.

Cloud HR Delivers Sustainable Value with Exceptional Employee Experience

To future-proof its workforce, Eastman set itself up for success by moving to the cloud with 麻豆原创 SuccessFactors solutions. Eastman was already using an on-premise human capital management (HCM) solution from 麻豆原创, but wanted the scalability and cost-effectiveness of a cloud-based HR solution. 鈥淒elivering [HR] services in the cloud gives us an opportunity to make the technology available to our employees in a way that is more sustainable than having it housed on our servers,鈥� says Nabors.

Prachi Sathe, director of Global HR Technology and Solutions, Eastman, underscores the value of receiving the latest innovations and new features with each biannual 麻豆原创 SuccessFactors release update. 鈥淲e also wanted to make sure our HR platform is sustainable in terms of how we support it, how we grow it, and how we make more functions available to our employees. Going to 麻豆原创 SuccessFactors just made sense for us,鈥� she says.

Eastman uses a range of solutions in 鈥� including 麻豆原创 SuccessFactors Employee Central and modules for recruiting, learning, compensation, variable pay, performance and goals, career development planning, and succession 鈥� to help harness the efficiency of end-to-end integration and provide an exceptional experience throughout the employee journey from hire to retire.

The 麻豆原创 SuccessFactors Recruiting solution, for example, is a key driver of Eastman鈥檚 talent strategy. 鈥淭hat鈥檚 how we bring our new talent into the organization. That鈥檚 really their first introduction to our tools,鈥� says Nabors. 鈥淲e鈥檙e bringing great talent into the organization. How we do it is very important, and 麻豆原创 SuccessFactors is a part of that.鈥�

Accelerating Efficiency with Real-Time Analytics

Eastman needed a streamlined approach to HR reporting that accelerated efficiency and optimized value by fully using the analytics and data in 麻豆原创 SuccessFactors solutions. 鈥淲e were using separate tools outside of 麻豆原创 SuccessFactors solutions to pull our reporting together,鈥� recalls Sathe. 鈥淭he challenges with that [were figuring out] how we get data out of 麻豆原创 SuccessFactors solutions and feed it into those reporting tools.鈥�

Eastman鈥檚 customer success partner for the plan identified 麻豆原创 resources to help Eastman increase value from its use of 麻豆原创 SuccessFactors People Analytics. Eastman also joined a hands-on lab session at SuccessConnect 2022 to gain experience working with story reports, a tool available in the report center of 麻豆原创 SuccessFactors solutions. Story reports can deliver real-time data analytics and generate reports faster by using live data from across 麻豆原创 SuccessFactors HXM Suite, displaying presentation-style reports in a clear format with detailed visual graphics that communicate insights in an understandable way. As Sathe notes, 鈥淲hen we saw [story reports], it was so motivating for us that data is already there and tools are there. We came back and started working on our first dashboard.鈥�

鈥淲e鈥檙e so happy Eastman joined us at SuccessConnect,鈥� says Maryann Abbajay, chief revenue officer, 麻豆原创 SuccessFactors. 鈥淗ands-on lab sessions like the one Eastman participated in are invaluable learning experiences. Eastman is a great example of how customers are applying that new knowledge to unlock value with 麻豆原创 SuccessFactors. With story reports, they are already able to deliver the type of data-driven insights that transform HR into a strategic partner for the business.鈥�    

Data-Driven Insights That Advance People Strategy

Eastman began working with a manager dashboard, one of the many time-saving templates preloaded in story reports, and later built its own version tailored to the information requirements of its organizational leaders, supervisors, and people managers. The HR team also developed custom objects to use in its story reports, including an organizational hierarchy table with extensive drilldown capabilities and a currency exchange table to help executives track international labor costs. The story reports, customized with the look and feel of Eastman鈥檚 branding, quickly gained broad acceptance with Eastman鈥檚 organizational leaders.

The HR team recently built a dashboard showing a holistic view to help leaders identify opportunities to advance the organization鈥檚 people strategy. This dashboard uses data from 麻豆原创 SuccessFactors Employee Central and will later be augmented with data from the recruiting and learning solutions. A talent dashboard is also forthcoming to Eastman鈥檚 HR community, which includes talent partners and leaders. Sathe notes, 鈥淏y creating the stories, as its name says, we are bringing various data sources together.鈥�

Michael Glenn, talent assessment and analytics manager, Eastman, is building a new learning dashboard that will go out to all learning administrators and supervisors to enable them to see how many people are overdue on their learnings and what learnings are coming up in the next 30 days 鈥� and how many hours are required to complete the learning sessions. This information is especially important for production teams that work on fixed schedules, as it enables managers to plan the learning hours into the employee鈥檚 schedule.

To ensure the reports provide the right level of information to each recipient based on their role, Glenn intends to use the role-based access permissions available in story reports. So far, he is impressed with the feature, which saves him time from performing manual activities and distribution list maintenance. 鈥淲e鈥檝e been testing out role-based permissions and it is just working great,鈥� he says.

Empowering HR Administrators with User-Friendly Solutions for Improved Productivity

Nabors says that though she has no background or training in analytics, she found that she was able to get up to speed with stories very quickly. She recalls previously spending several days to build a single report that integrated data from 麻豆原创 SuccessFactors Employee Central and 麻豆原创 SuccessFactors Recruiting. In stories, she is now able to generate the same report in just one to two hours.

Also, troubleshooting and addressing gaps in data is much easier. 鈥淚f there鈥檚 an error somewhere 鈥� for example, requisition data that shows up under the wrong person鈥檚 name 鈥� being able to see it in a story is very easy,鈥� she says. 鈥淚t鈥檚 easy to address that error quickly because you can go right to the error without having to dig through lines and lines of data, rows and columns of data.鈥�

Better Analytics for Faster Decision-Making

Eastman plans to build on its early success with story reports to drive more insights for the organization. For example, there are plans to integrate data to track progress towards Eastman鈥檚 ambitious inclusion and diversity , which include increasing diverse talent and supporting employees in bringing their whole selves to work. Real-time information from 麻豆原创 SuccessFactors solutions supports organizational leaders in advancing Eastman鈥檚 strategy to build a high-performing organization.

鈥淲e really believe in sustainability and sustainable outcomes,鈥� says Sathe. 鈥淲e want our employees to be self-service reporting employees and create better analytics that give them information versus data. What we were doing previously was giving them data. Story reports transformed this.鈥�

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It’s a special thrill for Team Liquid fans, as both teams 鈥� the Dota 2 and the League of Legends squad 鈥� have qualified for the championships and will compete for the title. We tapped into our connection with Team Liquid and had the exclusive opportunity to talk to two team members, Haitham 鈥淗aitham鈥� Algbory, head analyst of the League of Legends team, and Mathis 鈥淛abbz鈥� Friesel, assistant coach and analyst of the Dota team, about how they prepare the teams for the world championships and what role 麻豆原创 technology plays for the teams to perform at their top level.

A big part of what 麻豆原创 brings to Team Liquid is , which helps make data analysis for both League of Legends and Dota a lot easier. The database allows the analysts to focus less on gathering data and more on analyzing it. Both Jabbz and Haitham have been working in this field for a long time, and there are things that they can do now that they never could before, thanks to a tool specifically made for esports data analysis.

鈥淚 support both the general manager and the coaching staff with scouting new talent,鈥� Haitham said. 鈥淭he way I do that is by providing periodic solo queue and scrim reports and end-of-season scouting reports. When it comes to the Academy teams of the East Regions, at the same time, we just track the players that are in the scene in general and we see their improvement based off the metrics that we have set in our tools.鈥�

On the League of Legends side, 麻豆原创 HANA Cloud is Haitham鈥檚 primary tool for scouting. But that鈥檚 not what Jabbz uses the data for. For Team Liquid Dota, the data is more match-focused.

鈥淔or us, 麻豆原创 HANA Cloud has more of a different function,鈥� Jabbz said. 鈥淲e use it mostly for performance-related things. I think the big advantage we have with the database is that we can actually import any public game that we want. Let鈥檚 say things have changed in a recent patch; we can make sure that we鈥檙e always up-to-date with how the meta is evolving. We also get to have a replay of every tournament game, so we can pick up all the information we need from any game, especially during live events. This is incredibly helpful. By having this tool available, you can quickly see how teams are adapting, how teams are thinking. I save a lot of time getting that information, whereas before I would have to open up the replays in the game and manually scroll through everything.鈥�

According to Haitham, being able to use real gameplay clips to corroborate the data 鈥� and vice versa 鈥� often helps build a stronger case for whatever argument he鈥檚 trying to make. Players are more inclined to believe the data once they have a reference point, which then allows them to gain a deeper understanding of the game.

鈥淲ith 麻豆原创, we have a lot of good [visualization] tools,鈥� Haitham said. 鈥淲e have an entire map tool that will just visualize where the wards are and what the movement is looking like. In addition, we have 麻豆原创 Analytics Cloud that gives us an opportunity to build charts and graphs for the players. I would use videos or clips that are important to show the opponent鈥檚 style, and then I support that with the maps or graphs from the 麻豆原创 tools.鈥�

For some, all these details might sound small, even insignificant. However, any coach or analyst will tell you that at the highest level of esports, the difference lies in the details. When pretty much every player is equal in skill, it鈥檚 those minor advantages that matter 鈥� which makes data analysis an important factor for success. After all, a close win is still a win. Both Haitham and Jabbz point to 鈥渢he small margins鈥� as the reasons why they love their roles as analysts.

鈥淧ersonally, I work on my own goal to help others achieve theirs at the same time,鈥� Haitham said. 鈥淪eeing how players are able to use science while playing video games, to beat opponents that they may not be able to without that kind of information鈥t just makes everything worthwhile.鈥�

鈥淚 agree. I think it鈥檚 always very satisfying to give information to the guys that they wouldn鈥檛 pick up on,鈥� Jabbz added. 鈥淚 guess we鈥檙e very similar in that regard. I also enjoy helping the guys and that鈥檚 what gives me the joy in this job. I don鈥檛 necessarily have to see myself in the limelight or at the front of the stage, but I really just like seeing my friends succeed.”

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Isabelle Schuhmacher is director of Global Sponsorships at 麻豆原创.
Christian Kreidt is storytelling lead for Global Sponsorships at 麻豆原创.

Photos courtesy of Team Liquid.

What most people don鈥檛 realize: the NHL is a sustainability pioneer in the sports industry.

I sat down with Omar Mitchell, vice president of Sustainable Infrastructure and Growth Initiatives at the NHL, to record a . We discussed why the NHL is focused on environmental stewardship and how technology can help understand and manage the organization鈥檚 carbon footprint. .

鈥淲hen we think about things that we need for the continuation of hockey, we need things like natural ice, cold weather, and fresh water,鈥� said Mitchell. 鈥淲e also need vibrant and healthy communities where we can play our sport.鈥�

Mitchell explained the environmental impact of holding games indoors: 鈥淲e play in what is essentially a giant refrigerator and we use a lot of energy — not to mention the lights we use to illuminate the ice鈥檚 surface.鈥�

Environmental sustainability is a priority for聽 the NHL. That鈥檚 why Commissioner Gary Bettman initiated the program, launched at the 2010 Bridgestone NHL Winter Classic, announcing its mission to embed sustainable business practices across the League and its member clubs.

In 2014, the organization issued its first sustainability report, which was also the first of its kind created by any North American professional sports league. The report included a carbon inventory for the League, allowing the NHL to have an initial understanding of the environmental impact of its Clubs.

鈥淚t was a documentation of all the scope one, scope two, and limited-scope three greenhouse gas emissions associated with our game and with everything around hosting these events throughout the calendar year,鈥� said Mitchell. The three scopes look at an organization鈥檚 emissions from both direct and indirect sources.

Mitchell explained that this was a complex undertaking because no one had previously assembled and calculated a similar carbon inventory. It meant manually gathering and analyzing data from across all its venues. While painstaking, this first step was critical and powerful: it established a baseline for the League that helped them refine their goals and strategy.

After the League issued its second sustainability report in 2018, it became clear that there was an opportunity to modernize the data collection and processing by using a modern technology platform. 鈥淲e needed an innovative platform that could help us streamline that data collection, make it easier for all stakeholders to be able to input that data, and to visualize and process it — so that there are meaningful insights that our Clubs and venue partners could act on.鈥�

That was the impetus for the NHL to co-innovate with 麻豆原创 on a new digital platform to gather and process this data from all Clubs, now called . The organizations had successfully collaborated to develop the 麻豆原创-NHL Coaching Insights mobile app, based on (麻豆原创 BTP), which delivers real-time player and game data to coaches. Based on this joint success, the League again turned to 麻豆原创 to tackle this new challenge.

The 2014 sustainability report showed that 70% of the NHL鈥檚 carbon emissions came from its venues鈥� energy consumption. The data and analytic capabilities within 麻豆原创 BTP have helped the NHL start to generate insights from the data with the goal to turn it into concrete actions that can reduce the organization鈥檚 carbon footprint.

NHL Venue Metrics has also started to improve access to data for Club and League stakeholders; finding time to analyze the data to drive sustainability decisions can be challenging. With the data collected by NHL Venue Metrics, the League will be able to help individual operators identify meaningful investments or upgrades that will help them decarbonize.

For example, Mitchell described the process of replacing older, energy-intensive lightbulbs with LED lights. As some venues started to install new LED lights, the NHL was able to track energy reduction. Not only did the new lights improve venues鈥� energy impact, but they also created a better broadcast experience for television viewers. As Mitchell explains, these improvements have benefited both the environment and the business.

Moving forward, NHL Venue Metrics will help open up new opportunities for the NHL — and its Clubs and venues — to embed sustainable practices into their operations. Driven by 麻豆原创 BTP, this solution makes it easier to share knowledge and create best practices across the organization about which new technologies, products, and services can help lower emissions. And even more important: it can help to engage fans by providing transparency into how their Clubs are improving sustainability, as well as ultimately how they can contribute to the success of NHL Green.

鈥淭he millions of fans who watch our sport can be positively impacted by the League鈥檚 efforts and, hopefully, embed sustainability into their lifestyle,鈥� said Mitchell. 鈥淭hat’s where we’re going to have a network effect that’s going to move the needle positively in our climate fight.鈥�

Now that鈥檚 a hat trick: one where technology helps the business, environment, and fans鈥� experience.

To find more episodes of the 鈥淏etter Together: Customer Conversations鈥� series, visit .

Ragunath Ramanathan is chief revenue officer for 麻豆原创 Business Technology Platform.

麻豆原创 data and analytics solutions were recognized with the following 2023 Best Of awards:

• in the Cloud Data Warehouse market category
• in the Predictive Analytics, Business Intelligence, and Corporate Performance Management market categories
• in the Embedded Database, Database-as-a-Service (DBaaS), Data Virtualization, In-Memory Databases, and Relational Databases market categories

Unleash the Power of Business Data with 麻豆原创 Datasphere

is a comprehensive data solution that can enable every data professional to deliver seamless and scalable access to mission-critical business data. It can provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

In a recent review, a TrustRadius customer described 麻豆原创 Datasphere as 鈥渆legant and robust.鈥� They went on to say that 麻豆原创 is 鈥渆xcellent at ensuring data integrity by eliminating duplications鈥� and that 麻豆原创 Datasphere can 鈥渉andle large volumes of data at ease [and] the efficiency of data virtualization makes modeling easy.鈥� Read more of the review .

Build Intelligent Data Applications with 麻豆原创 HANA Cloud

is a modern database as a service powering the next generation of intelligent data applications 鈥� self-learning and self-adapting applications that leverage built-in analytical and operational database capabilities to provide new experiences. 麻豆原创 HANA Cloud can empower users to build intelligent data solutions with cloud-native scalability, speed, and performance.

Megan Headley, vice president of Research at TrustRadius, noted: 鈥淩eviewers on TrustRadius appreciate 麻豆原创 HANA Cloud鈥檚 low administrative overhead, speedy data processing, and ease of use for new users.鈥�

Bring Together Analytics and Planning with 麻豆原创 Analytics Cloud

supports trusted insights and integrated planning processes enterprise-wide to help you make decisions without doubt. It can automate data-driven insights with the power of machine learning, helping you utilize the full context of 麻豆原创 data so that you can bring analytics closer to the point of decision.

麻豆原创 Analytics Cloud is the 鈥渂est financial planning and analytics innovative cloud solution,鈥� noted one TrustRadius reviewer. 鈥溌槎乖� Analytics Cloud is an innovative and solid product to improve FP&A, analytics, and consolidation [for] cloud-based business transformation processes.鈥� Learn more in the .

Give Data Purpose with 麻豆原创 Data and Analytics Solutions

Data and analytics empower business users to make informed decisions with 麻豆原创 solutions. 麻豆原创 Datasphere, 麻豆原创 Analytics Cloud, and 麻豆原创 HANA Cloud can work together seamlessly to help provide trusted insights while easily integrating into your business processes.

We鈥檙e honored that our customers have made their voices heard and we are proud that TrustRadius has recognized our products as top rated. Thank you to our passionate data and analytics customers for your continued support.

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Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics at 麻豆原创.

But Harrods鈥� most important channel is still its flagship store.

鈥淲hen we talk about luxury and the importance of experience, the store is core to what we do,鈥� Erik Rasmussen, head of 麻豆原创 & Data Analytics at Harrods, told 麻豆原创 on the NRF 2023 showfloor. 鈥淗aving that single flagship store is still absolutely crucial to Harrods鈥� DNA and something that we expect to drive going forward for a long time.鈥�

Harrods鈥� flagship store is about 1 million square feet (about 93,000 square meters) of retail space in Knightsbridge, an upscale London neighborhood known for grand Victorian and Georgian homes, fine dining, and, of course, high-end shopping. This single, full-line department store offers food, fashion, homeware, furniture, and technology 鈥� and it reaped 拢2.4 billion in sales last year.

鈥淪o, small footprint but massive business,鈥� Rasmussen said, noting that the flagship store alone carries more than 400,000 products from about 4,000 brands. 鈥淎nd incredible things [are] going on every day.鈥�

To keep incredible things happening, Harrods and 麻豆原创 invested in the Single View of Customer project, an analytics initiative to help Harrods better understand how customers interact with the brand. When Harrods can accurately anticipate what shoppers will want, it can deliver memorable experiences that make delighted customers say, 鈥淲ow!鈥�

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How to “Wow!”

鈥淗arrods is a unique model…A lot of other retailers will have a smaller selection of products in store and an endless aisle online,鈥� Rasmussen said. 鈥淎t Harrods, the most complete shopping experience is still to come into the store because of the variety…[and] the different experiences you have.鈥�

Indeed, Harrods rewards shoppers at its brick-and-mortar flagship store with expert associates and a truly impressive array of products. For instance, in the furniture department, you can see examples of each piece and then choose your very specific model based myriad variables, such as size, headboard style, and even jewelry configuration.

鈥淲ith one single product, you can very quickly get into things like 10,000 different permutations,鈥� Rasmussen said during a presentation at 麻豆原创鈥檚 NRF booth. 鈥淲hen you think about that spread across an entire product assortment 鈥� spread across all the brands that we carry 鈥� you suddenly start to find yourself in a really challenging data management perspective.鈥�

To conquer that challenge, Harrods consolidated all the relevant data from vendors and others into its backend, according to Rasmussen. Harrods鈥� digital technology team then built a Web app that lets shoppers personalize furniture from start to finish 鈥� from browsing to home delivery.

鈥淎 lot of heavy lifting that we had to do on the backend 鈥� it鈥檚 not easy to make this work,鈥� Rasmussen said. 鈥淏ut from a customer experience, ultimately it becomes pretty seamless.鈥�

Investing in Customers 鈥� And Single View of Customer

It鈥檚 vital that Harrods get better acquainted with the roughly 2.5 million consumers registered in its loyalty scheme, according to Rasmussen. Of the 400,000 or so unique customers who shop in store each year, the top 0.1%, roughly 400 people, account for about 20% of Harrods鈥� sales.

A 2021 implementation of 麻豆原创 Customer Activity Repository and 麻豆原创 BW/4HANA laid the foundation for much of Harrods鈥� analytics, according to Rasmussen. And, as a high-value 鈥� as opposed to high-volume 鈥� business, Harrods鈥� enterprise resource planning (ERP) system and data warehouse could analyze every individual transaction.

鈥淭his type of investment 鈥� giving us the right insights, the right analytics, the right visibility 鈥� has really empowered our teams,鈥� Rasmussen said. 鈥淜nowing that information 鈥� and we let that feed things like the Single View of Customer platform or our data science initiatives or replenishment 鈥� is fuel to the things we can do to drive our business.鈥�

Such drivers include reactivation campaigns, as happened with a shopper to whom Harrods offered a free pastry with a 拢50 purchase, according to Rasmussen. The customer made a qualifying purchase, received the complimentary gift, and then promptly returned to the salesfloor to spend another 拢30,000.

鈥淚f we can reactivate those types of customers across the entire 2.5 million [customers], the opportunities for our growth will be enormous,鈥� Rasmussen said. 鈥淚t鈥檚 something that we鈥檙e already seeing pay dividends, and we鈥檙e really excited to see what we can develop for the future.鈥�

The Future Is Still Experience

Predictive analytics will be a big focus for Harrods, especially identifying new shoppers who might be similar to its high-value customers, according to Rasmussen. Data from 麻豆原创 Marketing Cloud, 麻豆原创 Customer Data Cloud, and 麻豆原创 Service Cloud can help Harrods spot 鈥� and serve 鈥� its next big spenders, alongside transactional information through 麻豆原创 Customer Activity Repository and analytics via 麻豆原创 BW/4HANA.

鈥淗ow can we take a customer who might look like they鈥檙e spending 拢2,000 and realize that they are customers who should be spending 拢200,000?鈥� Rasmussen said in . 鈥淕et them the right personalized service within either our personal shopping department, our concierge service, or a stylist to make sure that we can nurture them more quickly.鈥�

And, again, this seamless customer experience is made possible by a lot of work on the backend. But it鈥檚 worth it, according to Rasmussen.

鈥淭he two things I take away from what we鈥檝e done at Harrods are one, customer experience comes first,鈥� Rasmussen said. 鈥淪econdly, I think we鈥檝e really benefited from the strong partnership we鈥檝e made with our technology partners, 麻豆原创 being one of them. We鈥檙e making sure that we can invest with them, co-innovate with them, and…we鈥檙e collectively moving towards giving the customer the absolutely best experience.鈥�

Whether motivated by the food waste epidemic, climate change, the growing desire of consumers to support sustainability-minded retailers, or impending carbon taxes, many food producers and retailers have defined goals to reduce their food waste and carbon footprints. This includes investing in systems and processes to bring about meaningful and measurable improvements to their business.

Understanding Demand Signals

Retailers and businesses in the food supply chain are increasingly turning to analytics and technology to help address this problem. Often, the solution begins with understanding how existing systems and processes can be improved. Common areas to focus on include demand planning and replenishment.

Retailers can reduce the amount of waste they produce simply by improving their forecasts. There are a lot of approaches to do this, which all come back to better understanding and anticipating customer shopping patterns. One factor to consider is the weather. No other external variable shifts consumer buying as frequently, immediately, or directly as the weather.

Most retailers lean heavily on recent performance to determine how much to replenish in different regions or individual stores. While recent sales trends are important, they are distorted by weather conditions and do not factor in how upcoming weather conditions are going to change sales volumes.

, an 麻豆原创 partner, measures the impact of weather. The quantification of weather鈥檚 impact is called Weather-Driven Demand (WDD). WDD precisely calculates when, where, and how much demand for specific products increases or decreases due to changes in the weather. Planalytics WDD values integrate into 麻豆原创 at scale to enable retailers to proactively manage the impact of weather and improve both preseason planning and in-season inventory management. Using weather as a demand signal in 麻豆原创 can enable retailers to ensure they have the right amount of perishable products on the shelves to match consumer demand on a localized level.

A Sustainable Solution

By quantifying the impact of weather, changes in upcoming weather conditions can be used to account for localized increases or decreases in demand for fresh food products. These demand metrics, when integrated into 麻豆原创, can reduce waste at scale up to 35% annually.

In addition, improved demand forecasts translate to less waste, which means fewer emissions. This enables retailers to more quickly reach 鈥� and track progress towards 鈥� their sustainability goals.

Measure First, Then Manage

鈥淲eather is a demand signal that helps you better understand your customer and what drives them to buy, or to not buy, specific products. Unlocking these insights is a quick and effective first step to proactively managing the impact of weather. Integrating this demand signal into your systems and processes enables businesses of all sizes to leverage the power of analytics to drive meaningful, measurable, and repeatable benefits,鈥� said , EVP of Global Partnerships & Alliances at Planalytics.

Demand more to take the fast track to a better demand forecast. Want to find out how your company can benefit from a better demand forecast? to reduce food waste!

Carina Legl is co-lead of Business Development and Strategy for Industry Cloud MEE of 麻豆原创 Consumer Industries.

That鈥檚 because business transformation is about far more than simply digital transformation. It鈥檚 about the adoption of new technology and the implementation of the best people, processes, and operations 鈥� so you can quickly adapt to evolving challenges and opportunities. More so, it鈥檚 about learning to embrace data throughout every step of the process. Data drives outcomes and ensures you can meet changing customer needs while continuing to drive innovation and future growth.

The business transformation success story of our partners at the National Hockey League (NHL) is an amazing example of this, as its relationship with data has helped reinvigorate the sports league鈥檚 position in the global marketplace. Dave Lehanski, EVP of Business Innovation and Development for the NHL, recently spoke with Scott Russell, member of the Executive Board of 麻豆原创 SE, Customer Success, at 麻豆原创 Business Innovation Day to share the NHL’s story.

A Brand-New Outlook on On-Ice Action

Since working with 麻豆原创 in 2015, the NHL has undergone a total reinvention of its data capabilities 鈥� transforming the way players, coaches, and fans interact with data in the process.

鈥淯nlike other sports, hockey is not defined by discrete events during games,鈥� Lehanski said. 鈥淭hat makes it harder for us to tell full stories, because there are fewer stoppages throughout the competition. That鈥檚 why we need live, in-game data. It helps us tell stories as they are unfolding.鈥�

Data helps the NHL tell better stories 鈥� with things like NHL Edge, its puck and player tracking technology 鈥� because it works across multiple levels.

鈥淐oaches and players were hesitant [when we first tried it],鈥� Lehanski said. 鈥淎nalytics can be imposing to those on the ice when they are first introduced. But now that they鈥檝e seen what is possible, the data has really built trust 鈥� and helped change operations entirely 鈥� across general managers鈥� offices, scouting departments, and entire organizations.鈥�

The NHL is also using data with a focus on sustainability, specifically to gain a better understanding of energy utilization, water consumption, waste, and recycling across all NHL club venues. That鈥檚 why the league recently built the NHL Venue Metrics platform using . It enables them to measure those data points and clearly understand environmental impacts. In turn, they can set goals 鈥� while scoring goals 鈥� that set them up for the future.

What鈥檚 Next

If businesses today intend to continue growing and competing in their industries, they must take steps to become more resilient and responsive. The NHL has done that, and it’s a perfect example of what it looks like to let new technology drive transformation. As analytics, artificial intelligence (AI), cloud, and machine learning tools continue to advance, it will be vital for enterprises like the NHL to continue finding ways to innovate 鈥� to ensure that they鈥檒l always be top-shelf.

The summit featured the most recent trends, technologies, and strategies in the world of data and analytics. It offered a unique opportunity for attendees to learn from industry experts and gain insights into how businesses are using data and analytics to foster innovation.

While a wide variety of topics were addressed, data fabric stood out as a recurring theme. Data fabric is an approach to data management, deployment, and automation, and it took center stage during the sessions, workshops, and even the booth conversations.

The prominence of data fabric at the event underscores its growing importance in the field of data and analytics technology, which was exciting to see. Let’s dive into the key highlights.

1. Taking an Integrated Approach to Data and Analytics at the 麻豆原创 Booth

麻豆原创鈥檚 booth presence was a major highlight at the summit, showcasing our suite of . Many attendees were interested in learning more about the launch of , as well as our recently announced open data partnerships with Databricks, Collibra, Confluent, and DataRobot.

麻豆原创 Datasphere was last month and is our comprehensive data service that enables users to easily distribute mission-critical business data across their data landscapes. Together with our partnerships, 麻豆原创 Datasphere is the foundation that can enable a business data fabric.

More than ever before, organizations need accurate, easily accessible data that鈥檚 available in business-friendly terms. A business data fabric architecture delivers an integrated, semantically rich data layer over underlying data landscapes and provides seamless and scalable access to data without duplication. By leveraging a business data fabric, organizations can deliver meaningful data to every user 鈥� with the business context and logic intact 鈥� and position themselves for long-term success.

It was inspiring to see so much interest in the business data fabric topic, not only in the sessions at the conference but also in the conversations at the 麻豆原创 booth. This level of enthusiasm demonstrates the growing recognition of data fabric’s potential to revolutionize data and analytics strategy, further validating its importance in the evolving digital landscape.

2. Leveraging a Business Data Fabric with Glanbia

Tom Harrington, senior business intelligence analyst at Glanbia, led the session 鈥溌槎乖�: How Glanbia Drives Better Financial Decisions with Trusted, Authoritative Data.鈥� Harrington shared how Glanbia, a world leader in performance and lifestyle nutrition, gained a complete overview of its business by connecting data across cloud, on-premise, and flat files.

Glanbia leveraged 麻豆原创 Datasphere and 麻豆原创 Analytics Cloud to federate data from different sources using a business data fabric. Now, Glanbia business users create their own dashboards using 麻豆原创 Analytics Cloud and their own models in 麻豆原创 Datasphere, without assistance from IT users. They鈥檝e generated more meaningful financial insights to maximize the impact of decisions on their bottom line.

鈥淲e鈥檝e been able to transform into a data-driven organization in a quick amount of time,鈥� Harrington said. 鈥溌槎乖� Datasphere and 麻豆原创 Analytics Cloud have enabled us to do that.鈥�

Glanbia is an example of how companies can use a business data fabric to better manage, access, and analyze their data, leading to more informed decision-making, improved efficiency, and increased competitiveness in the market.

Harrington ended the session by saying, 鈥淲e鈥檙e excited about the future.鈥�

3. Showcasing Advanced Analytics at the Show Floor Showdown

麻豆原创 Analytics Cloud was featured as part of the 鈥淪how Floor Showdown: Analytics and Business Intelligence Vendors II.鈥� 麻豆原创 competed against two other vendors to analyze and interpret a data set from Gartner.

Robert Thibodeaux, senior solution engineer, leveraged 麻豆原创 Analytics Cloud and 麻豆原创 Datasphere to combine data from disparate sources, define calculations and measures, and create hierarchies and dimensions. He then presented a visualization of his findings and demonstrated the interactive storytelling features of 麻豆原创 Analytics Cloud. Thibodeaux ended his presentation by emphasizing the ease of use for business users.

鈥淚f the user knows the data, they can trust data,鈥� he said. 鈥淎ll that insight is in one place.鈥�

The show floor showdown was a great illustration of the practical applications of advanced analytics, and it highlighted 麻豆原创 Analytics Cloud as a standout solution. Advanced analytics play a crucial role in helping businesses transform raw data into actionable insights, enabling them to make better decisions, improve performance, and maintain a competitive edge in today’s rapidly evolving marketplace.

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Don’t miss the 鈥淓nd-to-end Data Governance with 麻豆原创 and Collibra” webinar on April 18, 2023. Tune in to learn how 麻豆原创 and Collibra can deliver a simplified way to govern your data estate. for the webinar to find out more.

Join us at 麻豆原创 Sapphire to learn more about 麻豆原创鈥檚 latest innovations and connect with industry experts. Attend the event online or in Orlando from May 16-17, in Barcelona from May 24-25, and in S茫o Paulo from June 1-2. for 麻豆原创 Sapphire today.

Unleash the Power of Your Business Data

can maximize the value of your 麻豆原创 data for the most impactful decisions by retaining its full business meaning and context. With 麻豆原创 data and analytics solutions, you can deliver trusted insights on a modern data stack and extend planning and analysis across the enterprise for better outcomes.

Read more about the recently launched and its capabilities. To experience the power of 麻豆原创 Datasphere firsthand, try the

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics.

TrustRadius shares unbiased reviews from authenticated users across a variety of industries and identifies the top-performing products. The Winter 2023 Best Of awards highlight solutions that have earned outstanding customer feedback regarding their features, price, and support.

麻豆原创 data and analytics solutions maximize the value within all data for the most impactful decisions. We view this recognition from TrustRadius as a testament of our mission to give data purpose, connect business processes, and accelerate innovation.

We鈥檙e honored that our data and analytics solutions have been recognized with the following awards:

• : Best Feature Set, Best Value for Price, and Best Relationship in the Relational Databases category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Cloud Data Warehouse category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Master Data Management category
• : Best Feature Set, Best Value for Price, and Best Relationship in the Data Fabric category

Modernize the Data Foundation with 麻豆原创 HANA Cloud

is a modern database as a service powering the next generation of intelligent data applications and analytics across all enterprise data. It empowers users to build data solutions with cloud-native scalability, speed, and performance.

Megan Headley, vice president of Research at TrustRadius, noted, 鈥淩eviewers on TrustRadius appreciate 麻豆原创 HANA Cloud鈥檚 low administrative overhead, speedy data processing, and ease of use for new users.鈥�

One TrustRadius reviewer noted, 鈥淚t鈥檚 great to run mission-critical operations in real time from anywhere, introduce new business models within the industry, and expand globally with a trusted partner.鈥� They also mentioned that it 鈥渞educes the complexity of multi-cloud or hybrid system landscapes鈥� and that the support is 鈥渁lways great.鈥� Read the for more.

Make Data Meaningful with 麻豆原创 Data Warehouse Cloud

goes beyond traditional data warehousing to provide a multi-cloud, multisource business semantic service for enterprise analytics and planning. This software as a service helps users to better understand business data and make decisions based on real-time information.

鈥淏uyers have a wide range of cloud data warehouse products to choose from,鈥� said Headley. 鈥淥n TrustRadius, reviewers highlight 麻豆原创 Data Warehouse Cloud鈥檚 no-code data modeling tools and no-ETL connections to data sources.鈥�

In a recent evaluation, one TrustRadius reviewer called it 鈥渢he future of cloud data warehousing.鈥� They went on to say that 鈥渆nd users have way more flexibility in making changes to the models without interference from IT鈥� and that 麻豆原创 Data Warehouse Cloud 鈥渋s the first tool [they鈥檝e] seen that can easily facilitate self-service data warehousing from a business user point of view.鈥� Find out more in the .

Manage Data Centrally with 麻豆原创 Master Data Governance

A unified, trusted view of a business allows for working more efficiently and making better decisions. The application helps pull together master data and manage it centrally using a master data management layer based on (麻豆原创 BTP).

鈥淩eviewers of 麻豆原创 Master Data Governance on TrustRadius appreciate the product鈥檚 impact on their data integrity and robust auditing capabilities,鈥� said Headley.

A TrustRadius reviewer mentioned, saying 鈥渢his program is just intuitive鈥� and it 鈥渟hortened the time to bring a solution to the client.鈥� The customer is 鈥渁ble to maintain [their] master data without the worry of having a duplicate moving in from another system or being created downstream.鈥� For more information, read the .

Integrate Data Across the IT Landscape with 麻豆原创 Data Intelligence Cloud

is a comprehensive data management solution supporting data fabric implementations. As the data orchestration layer of 麻豆原创 BTP, it transforms distributed data sprawls into vital data insights, supporting innovation and business growth.

Headley stated that 鈥渞eviewers on TrustRadius highlight 麻豆原创 Data Intelligence鈥檚 self-service data catalog, data lineage tools, and data integration capabilities.”

鈥溌槎乖� Data Intelligence suits all business scenarios that encompasses data,鈥� noted one TrustRadius reviewer. 鈥淚t simplifies exploration, enticement, modeling and visualization of data.鈥� The reviewer also mentioned that it helps them 鈥渋ntegrate data from flat files and external applications, process, and manage it in one spot.鈥� Learn more in the .

Give Data Purpose with 麻豆原创 Data and Analytics Solutions

Data and analytics are at the core of enterprise decision-making. 麻豆原创 data and analytics solutions bring together data warehousing, management, and integration to deliver trusted insights on a modern, open cloud architecture. These solutions empower users to retain the full perspective of their 麻豆原创 data and facilitate seamless integration with their business processes.

To us, this recognition from TrustRadius represents the voice of our customers. We鈥檙e proud that our products have inspired such gracious feedback in the user community, and we thank our passionate data and analytics customers for their support.

To learn more, visit the .

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics at 麻豆原创.

That is one reason why Ragunath Ramanathan, chief revenue officer of (麻豆原创 BTP), thinks that a software platform is particularly important for organizations considering strategies to help them weather economic headwinds.

鈥淭his is going to be a period of uncertainty in the macro-economic environment, including capital and labor markets,鈥� Ramanathan says. 鈥淎 platform can help create a more resilient business. It offers holistic insight and planning capabilities to help you understand what will happen to your cash flow, talent base, stocks, and demand — and allows businesses to plan for contingencies.鈥�

Facing cost-cutting measures, companies can use automation functionality within platforms like 麻豆原创 BTP to improve efficiency. Ramanathan explains that historically, organizations expect employees to take care of certain tasks manually. 鈥淏ut the line between what machines and people can do changes all the time. With embedded artificial intelligence and process automation features, platforms can help automate work and fill in for employees that organizations may not be able to afford.鈥�

Beyond automation, platforms with low-code and no-code (LCNC) development capabilities will help companies do more with less. 鈥淲hat鈥檚 exciting for 麻豆原创 customers is that the platform makes it easier to address innovation,鈥� says Ramanathan. 鈥淥ur recently announced LCNC offering, 麻豆原创 Build, makes coding easier — opening up innovation to normal business workers. With IT skills in short supply and volatile labor markets, it helps tap into existing labor pools.鈥�

But the economy is not the only reason for customers to accelerate their platform strategies in 2023.

鈥淲e need to put our heads above cyclical waves of recession and growth, which come and go,鈥� Ramanathan says. 鈥淐ertain challenges, like sustainability, don鈥檛 go away. We need to look beyond micro- and macro-economic trends to realize we don鈥檛 have much time. That鈥檚 where a platform can help.鈥�

Platforms that include analytics, reporting, and the ability to harness data across and within organizations provide huge benefits to help measuring progress against sustainability goals.

As Ramanathan points out, 鈥淲e鈥檙e in the wild west of sustainability and there are very different ideas about what it is and how to measure it.鈥� This makes it difficult to compare organizations to assess who鈥檚 doing well versus those that fall short. He explains that sustainability needs a 鈥渢ruth mirror鈥� to accurately reflect where companies stand in terms of their commitment, resources, successes, and areas for improvement.

鈥淭hink about the early days of accounting,鈥� says Ramanathan. 鈥淭here were many different accounting practices and 麻豆原创 created processes that became the gold standard in accounting software for companies that were serious about measuring their finances.鈥�

That鈥檚 what 麻豆原创 BTP can be for sustainability. It can enable integrated reporting that provides both a baseline and standard for all sustainability reporting. This will allow companies to drill down into and understand how to demonstrate progress to governing agencies and stakeholders.

One example of a platform鈥檚 power is a city in China that will use 麻豆原创 BTP to help achieve China鈥檚 鈥渄ual carbon鈥� goals: to 鈥減eak鈥� its carbon emissions before 2030 and become carbon neutral before 2060. With 麻豆原创 BTP, the city can eliminate data silos, allowing them to visualize the city鈥檚 carbon data by category and build industry-specific carbon emission data models. Access to integrated information will help them make the right choices to get to where they want to be as a city and a nation.

To get the most value out of a cloud platform, organizations must decide whether it is hosted in a public versus private cloud. While both have pros and cons — and many organizations will adopt a hybrid approach — Ramanathan provides this advice: 鈥淓ven in a cloud world, companies often wind up maintaining complex IT systems. But the real benefits of the cloud, especially in resource-short times, is that it can free up those responsibilities so companies can focus on innovating to advance their business.鈥�

This is where public cloud comes in. As Ramanathan explains, private cloud requires more discipline and know-how to configure and use the system. But public cloud allows companies to outsource that work to cloud vendors with that exact expertise.

鈥淢oreover, public cloud solutions are being used by hundreds of customers of all sizes,鈥� says Ramanathan. 鈥淪o you can be assured that if others are using the software successfully, it will work for you. You get the highest service levels, security, resiliency, and easier upgrade paths.鈥�

Milliken was relying on an outdated, on-premise human capital management (HCM) system that struggled to keep up with the changing demands of its workforce. A poor user experience led to limited adoption and a slew of frustrations for admins and users alike. In addition, obtaining accurate reports was nearly impossible due to the number of disparate HR processes in use around the globe. It was clear that a new approach was needed. To fully support its workers, Milliken decided that it was time to move to the cloud.

Taking a phased approach, Milliken began by implementing cloud solutions to support its recruiting, succession planning, performance management, and analytics processes. By leveraging , it was able to offer mobile-friendly job applications in a number of languages and to create a more accessible and user-friendly experience for applicants. In addition, an expanded presence across more than 40 job sites helped Milliken make significant strides towards creating a diversified talent pool with quality candidates. Within one year, applicant volume increased by more than 300%. To further align its recruiting and succession processes with business diversity, equity, and inclusion (DE&I) goals, Milliken leveraged advanced analytics to capture data on headcount, turnover, and hiring. Comprehensive graphs and reporting capabilities enabled Milliken to visualize data across the workforce, from compensation and benefit trends to key diversity metrics.

Building upon its initial successes, Milliken began to transition its core HR processes from on premise to the cloud. To improve data quality and overall transparency, it leveraged to manage employee and organizational data across the globe. Moving towards a single platform has helped better support HR compliance and allowed Milliken to respond more proactively to legal and regulatory changes. Mobile capabilities were deployed to deskless associates, supporting the company鈥檚 sustainability goal to reduce paper consumption.

Looking forward, Milliken intends to continue its cloud transformation by moving benefits and compensation administration processes to the cloud. Improving the access and overall experience of key HR functions is an integral part of Milliken鈥檚 mission to support its people and ultimately create a sustainable workforce. With less time spent on operational tactics, Milliken鈥檚 associates can focus on delivering positive outcomes for their customers and communities.

Jeff Glauber is global solution marketing lead for 麻豆原创 SuccessFactors Employee Central at 麻豆原创.

To better understand customer needs around translytical platforms, Forrester Research has studied many real-time offerings and evaluated them for suitability across multiple dimensions such as architecture, translytical functions, data handling, streaming, and security.

An intelligent enterprise consistently applies advanced technologies and best practices within agile, integrated business processes and can wisely plan yet act in the moment. But to respond accurately in real time, organizations must analyze transactions as they are generated and correlate diverse signals from ever-growing data sources. Moving and aggregating data can undermine agility and increase vulnerabilities; thus the need for translytical data platforms with all workloads running simultaneously on the same database.

Translytical data platforms are a crucial technology to combat data sprawl and reduce the number of data copies by allowing users to run real-time analysis on the transactional systems themselves.

The translytical capabilities of 麻豆原创 HANA Cloud turn data into business value by supporting a variety of workloads and use cases, including real-time transaction processing, streaming analytics, machine learning, and rapid operational reporting within a single database. Our various cloud and on-premise deployment options deliver a high level of openness, scalability, and flexibility for customers. 麻豆原创 HANA Cloud has built-in design and runtime capabilities for smart multi-model processing, combined with integrated multi-tier storage, making it uniquely suited to support intelligent data applications.

When it was released over 10 years ago, 麻豆原创 HANA was one of the biggest innovations in enterprise information technology. By combining analytical and transactional processing in a single in-memory database, 麻豆原创 brought a radically different approach to the database market.

The in-memory performance and unique architecture of 麻豆原创 HANA Cloud, however, enabled 麻豆原创 to do just that: dramatically changing the game by enabling customers to attain real-time visibility across their businesses. 麻豆原创 HANA Cloud continues to impact customers — such as , , , and the — in all industries.

Data and analytics solutions from 麻豆原创 maximize the value of 麻豆原创 data by uniquely using the complete business context and meaning for the most impactful decisions. For us, this report鈥檚 conclusion is a testament to our mission to help organizations transform their data strategy and give data purpose.

To learn more, visit the . For a deeper dive into The Forrester Wave™: Translytical Data Platforms 2022, download a .

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics.

analysts predicted 80% of worldwide energy suppliers will use digital customer engagement solutions by 2026 to cater to the appetites of millennials and Gen Z, which will make up the majority of the utility industry鈥檚 customer base. A survey of Asia-Pacific city planners found they planned to prioritize initiatives that would manage critical resources like water using smart meters.

Similar to societal norms around sustainability, smart cities as a concept has evolved and expanded. According to James McClelland, senior global director of Industry Marketing for Utilities at 麻豆原创, organizations serving every community 鈥� from rural to urban and everything in between 鈥� care about efficiency, sustainability, and the circular economy.

鈥淲hether it鈥檚 water, gas, electricity, or other natural and energy resources, utilities want to become more efficient and reduce waste and lower carbon emissions for a more sustainable environment,鈥� said McClelland. 鈥淭he real power of a smart city comes down to data analytics from innovations like smart meters. With a better understanding of individual usage, utility providers can help customers make sustainable choices based on their household needs, collectively making the world a better place.鈥�

Case in point is American Water, which provides regulated and regulated-like drinking water and wastewater services to an estimated 14 million people in 24 states. Neeru Sharma, the company鈥檚 senior director of Business Partnership and Delivery, said the company distills every major decision into two questions: How will it make our company more efficient? And how will it positively change the customer experience?

I talked with Sharma at the event, where she told me about her company鈥檚 digitalization plans that included a network of smart meters based on the Internet of Things (IoT).

鈥淲e are a purpose-driven, customer-focused business,鈥� said Sharma. 鈥淥ur company vision revolves around efficient operations to deliver a superior customer experience and contribute to a sustainable society with better water consumption management. Going to a cloud-based platform is our first step in becoming an intelligent enterprise.鈥�

Operational Efficiencies from IoT-Based Sensors

American Water is at the vanguard of the utility industry鈥檚 digitalization trend that is fueled by consumer demographics and sustainability mandates.

Sharma equated technology innovation with her company鈥檚 business agility and resilience. Headquartered in New Jersey, American Water is the largest and most geographically diverse U.S. publicly traded water and wastewater utility company.

American Water recently selected to collect real and near real-time data from meters, as well as 聽to connect information to billing and other systems. Unlike yesteryear鈥檚 monthly meter readings that relied on resource-intensive truck rolls, sensor-based smart meters automatically capture water usage data more frequently, giving American Water a clearer understanding of actual water consumption levels for billing and planning purposes. Access to real-time and on-demand data will also flag potential problems, helping the company keep meters in peak working condition.

鈥淲e won鈥檛 have to wait until the end of the month for usage data,鈥� said Sharma. 鈥淲e can identify and manage meter read issues, consumption patterns, and potential leak patterns at scale in buildings, and connect it directly to our billing systems. As a water utility, it鈥檚 very important for us to use our own resources to efficiently and better manage water distribution across our communities.鈥�

Analytics Behind Sustainable Business

Of course, sustainable water management does not mean reducing customer access to water. In this case, it translates to analyzing and acting on data from smart meters. For example, an unnatural spike in water consumption beyond typical usage rates could indicate a potential leak or a malfunctioning meter.

鈥淵ou need solutions that will provide up-to-the-minute information, surfacing water consumption trends on a daily basis,鈥� said Sharma. 鈥淎nalyzing that data, we can see if a customer鈥檚 consumption is consistent with or outside of historical norms. Having this on-demand data available can help us conduct proactive maintenance to prevent disruptions.鈥�

Sharma credited technology innovations like smart meters with helping the company meet sustainability objectives and build trusted relationships with customers.

鈥淚t takes a lot of steps to deliver clean water from the source to the customer鈥檚 faucet,鈥� she said. 鈥淭echnology is integral to providing that visibility into our entire process of bringing quality water in compliance with regulations to our customers. We want our customers to be fully aware of their water usage and what they can do for a more sustainable community. Data transparency is just as important to tracking our performance against ESG objectives.鈥�

Smart Communities are the Future

Smart meters are a harbinger of what鈥檚 to come as utilities grapple with managing water, arguably the most finite valuable natural resource on the planet. Leading utility providers are gearing up for major transformation.

analysts predicted that by next year, stricter environmental regulations will have pushed 30% of water utilities to invest in integrated information technology (IT) 聽and operational technology (OT) data. Forrester analysts said that by 2024, 40% of energy suppliers will have lifted the core business logic from billing to customer data and experience management, becoming three times more effective at marketing new products.

Between climate change risks and consumer and community demands, water utilities need technology more than ever to boost efficiencies that improve the customer experience, representing the dawn of the next generation of sustainable smart communities.

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Sight, hearing, smell, taste, and touch: the classic five senses of humans allow us to experience the world around us, with our nervous system receiving and processing huge amounts of information and relaying signals to the brain in order to react with the world. It is almost impossible to say how much data the human brain receives and processes on a daily basis. At best, one can specify a lower limit of perhaps around 1,000 gigabytes.

Humans not only process but also generate data in abundance. How many Instagram Stories did you click through last night before falling asleep in bed? How much time did you spend on different news portals? Just one more episode of 鈥淪tranger Things鈥� on Netflix? The list goes on and on.

Navigating the Data Jungle

Companies struggle with this too and collect and analyze more data than ever before. Not without reason, data is referred to as the new gold. The way to increased profitability and competitive advantage by means of intelligent data usage seems to be a rocky one. Using the sheer amount of data to its full advantage remains a challenge.

At 麻豆原创, we want to help our customers navigate the data jungle, regardless of infrastructure and where the data is saved. For 50 years, 麻豆原创 has been storing, processing, and analyzing innumerable amounts of customer data. Building on these strong data management capabilities, we want customers to be able to base all their decisions on intelligent, data-driven insights with easily accessible business data — when and where they matter the most.

Our ambition is a clear shift from the current state of analytics to the future, which means that we see the future of analytics as autonomous, hence always learning and monitoring; proactive, in order to provide solutions and alternatives to problems that haven’t even been discovered yet; and personalized, meaning that insights are contextualized and can be provided per desired medium or experience preference.

Bringing Future Technologies to Customers Today

While we envision a true system of intelligence in the future, 麻豆原创 is already demonstrating value for customers today. 麻豆原创 Innovation Center Network is exploring multiple key technologies to help customers capitalize more on data and boost productivity to stay competitive in the long run.

Businesses are constantly in motion, and data continues to grow in size, complexity, and velocity. “Laura,” a risk manager at a company that evaluates the potential risks of a business and strategizes preventive measures, needs to be able to monitor standard KPIs via dashboards and constantly adapt them to catch trends and patterns or anomalies — at least it should be that way.

Today, however, autonomous, proactive, and personalized tools are needed to automate business monitoring and proactively identify and report relevant signals in data.

To address this need, we built a prototype of a self-learning, easy-to-integrate cloud service that continuously monitors business data for anomalies and proactively delivers actionable insights to risk managers like Laura in real time. We call this , and by integrating it into her day-to-day operations, Laura can spend less time exploring data and can detect unknown yet critical signals without manual intervention. She can also filter anomalies by relevance to receive critical signals, ultimately helping to get insights faster and react accordingly — before the business is impacted.

With all information at hand, the system can autonomously propose a response in real time, such as, 鈥淗ey Laura, something is going wrong, and here are a few proposals on what you can do.鈥� This is made possible by what-if scenarios enabled by the . It helps her autonomously consider multiple scenarios, simulate their outcomes, and offer recommendations for the next steps. For example, instead of relying on the usual measures, she might be shown alternative approaches that she had not thought of before but that would solve the problem even faster.

By providing holistic impact analysis and autonomous identification of what-if scenarios, Laura can better plan ahead and react quicker to uncertainties with data-driven insights. Optimized recommended actions that are aligned with company priorities and constraints allow her to recognize and mitigate risks early on — and decide on actions with confidence.

Like most of us, Laura is a visual person who processes images much faster than text. No wonder visualizing data in an easy-to-understand form has also become a trend in analytics. Thanks to their length of just a few seconds, short videos have evolved into the dominant format for sharing and receiving updates and notifications. Consuming information like you would consume content in social apps helps professionals like Laura capture vast chunks of complex data and become the one-stop shop for business insights in the future.

麻豆原创 is bringing such short-form videos to the enterprise. With automatically generated personalized content, concise stories deliver key insights about the business in a short, animated, and convenient format. Video data stories provide customers with a one-stop channel for timely notifications, digests, and alerts about business-critical events. It automatically translates real-time business insights into self-explaining audio-visual data stories, making it easier for Laura to make decisions.

Effective business processes depend on intelligent decisions with insights from data in the organization and beyond its networks. 麻豆原创鈥檚 vision is to infuse these data-driven insights into every decision-making process. This would be possible with AI-powered, lightweight, self-service analytics that seamlessly integrate into the day-to-day work routines of business users, blending human ingenuity and data-driven insights into context-rich, fact-based decision-making processes.

Automation and data contextualization are key trends shaping the future of analytics, requiring an evolution from the current state of analytics to the future of analytics being autonomous, proactive, personalized, and reinventing business decisions as a service.聽 麻豆原创 is a reliable partner to anticipate that change, drive innovation, and help our customers prepare for the future.

Data is the new gold of every enterprise. If you also want to base your decisions on intelligent data-driven insights in the future, you can become part of 麻豆原创鈥檚 innovation journey and get in touch with us. Customer feedback is key to solving real pain points in the data and analytics space and we would be delighted to co-innovate and solve your data challenges together.

Martin Heinig is head of New Ventures and Technologies at 麻豆原创.
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As a leading independent research and review platform, TrustRadius recognizes top software solutions based on user feedback. Decision makers across industries turn to TrustRadius鈥� 415,000 reviews to find unbiased perspectives from real customers when searching for the right software for their needs.

鈥淚n the age of the self-serve buyer, software buyers rely heavily on third-party sources,鈥� said TrustRadius CEO Vinay Bhagat. 鈥淭hat鈥檚 why third-party reviews and awards from a trusted source like TrustRadius are so important.鈥�

Our data and analytics solutions maximize the value of 麻豆原创 data by uniquely utilizing its complete business context and meaning for the most impactful decisions. We view these awards as a testament to our mission to help organizations transform their data strategy and give data purpose. We’re honored to be recognized by TrustRadius, and by our customers.

麻豆原创 data and analytics solutions include 麻豆原创 HANA Cloud, a single database foundation for modern applications and analytics, 麻豆原创 Data Warehouse Cloud, a semantic service for unifying all data, and 麻豆原创 Analytics Cloud, which brings planning and analytics together to make decisions without doubt.

Top Rated Award Wins

Within the TrustRadius platform, reviewers rate products based on usability, support, return on investment, and likelihood of recommendation. The Top Rated Awards recognize solutions with the highest customer satisfaction scores. TrustRadius evaluates candidates for these awards based on recency, ratings, and relevancy. To win, products must have earned recent reviews, a high percentage of positive ratings, and considerable site traffic.

We鈥檙e thrilled to have earned multiple 2022 Top Rated Awards:

• won in the following categories: Business Intelligence, Corporate Performance Management, and Predictive Analytics
• won in the following categories: Data Catalog, Data Fabric, and Data Integration
• won in the category Cloud Data Warehouse
• won in the following categories: Database-as-a-Service, Data Virtualization, Embedded Database, In-Memory Databases, and Relational Databases
• won in the following categories: Data Governance and Master Data Management

Best of Award Wins

The TrustRadius Best of Awards recognize software with the Best Feature Set, Best Relationship, and Best Value, according to reviewer insights. These awards highlight the features that buyers care about most and the products that excel in these areas. In order to win, products must have at least 10 recent ratings and be ranked in the top three positions of their category in terms of the percentage of positive reviews.

鈥淏2B relationships built on trust lead to better outcomes for both tech buyers and vendors,鈥� said Megan Headley, vice president of Research at TrustRadius. 鈥淪o we鈥檙e highlighting software vendors who do the best job of delivering on promises and expectations set during the sales cycle. The Best of Awards help buyers identify products with stand-out features, transparent pricing, and the best implementation and support experience.鈥�

麻豆原创 data and analytics solutions were recognized with multiple 2022 Summer Best of Awards:

• won Best Value in the Corporate Performance Management category
• won Best Feature Set, Best Relationship, and Best Value in the Cloud Data Warehouse category
• won Best Feature Set, Best Relationship, and Best Value in the Relational Databases category

For more information about recent reviews, product details, and comparisons, visit the TrustRadius product pages for , , , and .

Transform Your Data Strategy with 麻豆原创 Data and Analytics Solutions

麻豆原创 data and analytics solutions retain the full perspective of 麻豆原创 data, up-to-date and authoritative while bringing other data into the context-rich environment of your existing business systems. Using 麻豆原创鈥檚 modern data stack, you can create intelligent data apps and collaborative plans seamlessly integrated with 麻豆原创 business processes.

At 麻豆原创, we鈥檙e proud and humbled that our solutions have inspired such positive reviews in the user community. Thank you for supporting our work, and for sharing your feedback on the TrustRadius platform.

To learn more information and experience the software,
visit the page on sap.com.

Daniel Yu is senior vice president of Solution Management and Product Marketing for 麻豆原创 Data and Analytics.

Esports is a rapidly growing industry. Online gaming and its competitive form, referred to as esports, are well on the way to becoming a global cultural phenomenon. These days, tournaments attract million-strong audiences and offer prize money also well into the millions. Gamers enjoy rock-star status and compete in sold-out stadiums. The took esports鈥� popularity to new heights and vastly accelerated its development. In 2020, revenue in the industry soared, surpassing US$1billion for the first time.

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Tournament in Berlin: 麻豆原创 Shows What Innovation and Data Can Do for Esports

麻豆原创 first joined forces with a professional esports team back in 2018. The company is the sponsor and official innovation partner of Team Liquid, one of the most successful gaming teams. has recently hosted the very first tournament of its own. The event鈥檚 executive sponsor, Martin Heinig, who is head of New Ventures and Technologies at 麻豆原创 and managing director of 麻豆原创 Labs Berlin, says: 鈥淚t is the first time 麻豆原创 owned an esports event, making this experience so unique. It excites me to see how we were able to bring together students and 麻豆原创 employees to see them play against each other and contribute to their gaming success with 麻豆原创 technologies, such as in-game data analytics. I’m very proud that 麻豆原创 Labs Berlin hosted this special event.鈥�

In holding its own competition, 麻豆原创 showed how it is not just part of the esport ecosystem but that it can help shape it, too. 麻豆原创 Labs Berlin is constantly looking for ways to raise its profile in the German capital鈥檚 esports scene, which is one of the biggest of its kind. Digital gaming has the potential to be a significant economic opportunity for the city.

Juergen Mueller, member of the Executive Board and chief technology officer at 麻豆原创, was at the tournament, too. He is a huge esports and gaming fan: 鈥淚t’s amazing! The arena is packed, you can sense the excitement, it鈥檚 noisy, and many people are having a lot of fun. 麻豆原创 and esports are a great match. As a technology company, we use our expertise in data analytics and innovation in esports just like in any other business area to help gamers tell the story behind their data. I鈥檓 happy to see the immense interest from our customers, partners, and students on-site.鈥�

Competitors battled it out over Dota 2, the sequel to Defense of the Ancients, which aficionados abbreviate to Dota. In this game, two teams play against each other, with one side trying to take and destroy the main building, called the 鈥淎ncient,鈥� and the other side defending it. Each team has five players, and each player controls a 鈥渉ero鈥� from a bird鈥檚-eye view. The game has a pool of more than 120 heroes with different abilities.

Dota 2 has many facets and is tactically demanding. Each hero has a 鈥渢alent tree鈥�: when a player reaches a particular experience level, their hero can gain extra talents. This results in thousands of possible combinations, which makes each game unique.

New Insights from 麻豆原创: How Data Can Improve Performance

At the professional level, by 麻豆原创. The data and analytics tools available to the team help ensure it is best prepared for competitions and for countering its opponents鈥� tactics. The solutions it uses are built on (麻豆原创 BTP) and include 麻豆原创 HANA Cloud and artificial intelligence (AI) functionality. Being able to analyze data in real time enables professional gamers to optimize their performance and make faster decisions during the match itself.

Just like in the business world, the players need to be able to spot which information is most relevant to them instantly if they are to gain strategic advantage from it. An esport tournament creates huge amounts of data, so 麻豆原创 realized it needed to display the data it captured in a clear and visually appealing way. 鈥淚t’s inspiring to see that 麻豆原创 technology provides value in an esports context by improving player performance through live data and insights,鈥� says Heinig.

Match data and statistics can be shared with audiences and commentators in real time, giving them greater insights into each player鈥檚 performance and helping them better understand certain decisions. At the 麻豆原创 event, matches played by the finalists demonstrated how this works. As at professional tournaments, Jonathan Liebig (nicknamed 鈥淧impmuckL鈥�), one of the top observers and producers of Dota 2, ensured spectators did not miss any of the action. 麻豆原创 BTP was used to combine data from past games with live data from the finals, which Liebig could use to and player performance to the audience.

Bringing Together Students, Fans, and Employees

At the tournament in Berlin, 麻豆原创 offered spectators a hybrid experience, combining an in-person event with live streaming. Almost 100 gamers took part, half of whom were students and the other half 麻豆原创 employees. Since they competed as mixed teams, the event was also an opportunity to network. More than 230 guests came to the venue, with 2,500 viewers following the action on the live-streaming portal Twitch. On social media, the event reached more than 420,000 people.

The tournament was a big hit with the students: 鈥淚 wouldn鈥檛 have thought that 麻豆原创 has a connection to esports. I’m really happy to have been part of this special event in Berlin, and it鈥檚 great to see that 麻豆原创 is doing something so cool. Also, it is an amazing opportunity to network and I could meet the CTO of 麻豆原创!鈥� says Fritz Hinze, a student at the Free University of Berlin.

The competition brought friends and 麻豆原创 employees together to share their passion for gaming. In a live online interview, Mathis 鈥淛abbz鈥� Friesel, one of Germany鈥檚 professional Dota 2 players and an analyst on Team Liquid, gave the audience a glimpse of how his team uses 麻豆原创鈥檚 data and analytics solutions to prepare for games by analyzing opponents鈥� playing style and strategies. The event was organized just like a professional tournament, giving spectators and the players an authentic experience. They could also try out that are normally available only to the pros on Team Liquid.

鈥淭he high-tech sector is under regulatory pressure to consistently capture data measuring the carbon footprint of their devices throughout the entire product life cycle, from sourcing materials to end of life and reuse,鈥� said Joerg Kaufmann, director of high-tech solution management at 麻豆原创. 鈥淭hey need a certifiable, auditable trail of data to prove regulatory compliance and avoid penalties. This will help manage operational costs while building a more sustainable business model.鈥�

A recent found that high-tech executives demonstrated the most mature outlook on sustainability: over 75% agreed that good sustainability practices reduced overall risk, versus 61% of total respondents. They were also the most likely of any sector to have a specific plan for reducing carbon emissions (71%).

Tracking Product Lifetime CO2 Emissions

Make no mistake, for high tech and every industry, net zero is a bottom-line issue. researchers predicted that by 2024, to improve long-term supply chain profitability, 70% of manufacturers in global supply chains will invest in software tools supporting sustainability and a circular economy business model. analysts said that by 2025, 40% of all manufacturing IT will own the responsibility of data modeling for sustainability and net-zero carbon targets.

Consider the carbon footprint of a laptop. It begins with the sourcing of raw materials that are transported to the plant, stored in a warehouse, and productized into the manufacturing of the laptop, which is shipped to customers who use it before, hopefully, recycling it for another use. During each phase of life, the product emits CO2, increasing a company鈥檚 total carbon footprint over time. Tracking this level of tonnage with accuracy and consistency is the next frontier in sustainable business.

鈥淐O2 is the new currency for resilient, sustainable supply chains,鈥� said Kaufmann. 鈥淔or example, is designed to collect internal and external data and calculate carbon emissions across the product life cycle. Companies can explore what-if scenarios, such as finding closer suppliers to reduce shipping miles and energy consumption. They could look at alternate designs and operations, sourcing recycled materials or increasing manufacturing efficiencies to produce an identical product for the same price with a lower carbon footprint.鈥�

Circular Economy Beats High-Tech Obsolescence

Built-in obsolescence has become both a growth driver and reporting burden for high-tech manufacturers. Yes, we want the latest innovations, but sustainable business isn鈥檛 tenable at the expense of climate change regulations. Many high-tech companies are transforming business models, in part, to innovate and better manage costs plus address climate change requirements. analysts predicted that by 2024, digital-first enterprises will enable empathetic customer experiences and resilient operating models by shifting 70% of all tech and services spending to as-a-service and outcomes-centric models.

鈥淥ver the past decade, many of our high-tech clients have shifted from selling boxes to services,鈥� said Kaufmann. 鈥淲e鈥檙e researching analytics that would help a manufacturer that sold, for instance, printing-as-a-service to track usage and provide insights prolonging the sustainable life cycle of the printer, including service and maintenance, replacement and exchange timelines, and reuse for business value and lowered lifetime carbon emissions.鈥�

High-Tech Players Recalculate Cost of Innovation

Having connected data may already be paying off for some companies. In the Oxford survey, high-tech respondents appeared to have made more progress in ensuring suppliers have sourced sustainable materials (72%) versus other industries. Business model transformation isn鈥檛 necessarily wholesale change all at once. With the right data, high-tech manufacturers can make adjustments that deliver stronger business results. No doubt regulations will spark innovations as well.

鈥淲hen you can measure your product鈥檚 entire CO2 footprint, you can reduce it,鈥� said Kaufmann. 鈥淲ith more comprehensive data, high-tech companies can factor CO2 emissions into the entire cost of the product, alongside everything else like the battery or the shell. They can make more informed decisions about the total cost to the company, including the environment.鈥�

Innovation at any cost is no longer sufficient for sustainable business. With the right data, high-tech leaders can recalculate the price all of us pay for a more sustainable world.

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With the growing volume, complexity, and velocity of data, it鈥檚 no surprise that businesses often consider only small subsets of what鈥檚 available for analytics. Research suggests that several of today鈥檚 best-of-class application operators are using of their collected data.

Continuously monitoring business data for anomalies helps identify the root cause and respond faster to such hidden events and changing trends. This approach to analytics provides continuous intelligence that helps brands make smart, real-time business decisions.

What Is Continuous Intelligence?

Traditionally, dashboards are checked periodically to monitor the most relevant KPIs and manually explore data along pre-defined paths. However, considering only pre-defined indicators and performance metrics leads to a limited perspective and misses information about unknown signals and trends in other parts of the data or at lower granularity.

Keeping track of what is relevant in this very moment is therefore a challenge for businesses across industries. Enter continuous intelligence.

According to Gartner, continuous intelligence 鈥渋s a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support.鈥�

The approach uses a variety of technologies such as machine learning, event stream processing, optimization, and business rule management.

Uncover the Unknown with AI

While humans cannot inspect every possible characteristic and combination in the flood of incoming data, machines can.

Complementing analytics that provide precise answers to questions users know to ask, a machine can continuously monitor data in the background to detect unknown correlations and trends that deviate from what would have been expected by the system based on previous observations.

This way, companies can identify hidden, but potentially relevant signals in the data. Gartner predicts that by 2022, more than half of major new business systems will incorporate continuous intelligence capabilities.

By integrating artificial intelligence (AI)-based continuous intelligence into their day-to-day operations, companies can:

• Boost efficiency by spending less time sifting through data from a variety of disparate sources
• Focus on what really matters for their business
• Speed time to action

By automatically inspecting critical business health indicators such as revenue, Web page views, active users, or transaction volume in real time, businesses can accelerate their time to insight and action and better respond to situations before business is impacted.

Putting Continuous Intelligence to Work

is exploring the business potential and requirements of continuous intelligence and developed a prototype of a self-learning cloud service.

This service autonomously discovers patterns in historic data to detect trends in new data that deviate from the expected. Insights are ranked by relevance and proactively provided to the user as comprehensive data stories with full context.

Especially in industries with fast-moving assets such as retail, the service could be critical for quickly adapting to changing buying behavior, trends, and market conditions. It could alert retailers to surging sales of Kate Middleton look-alike dresses, food trends such as avocados and oat milk, or demand for umbrellas due to bad weather.

But more than retailers could benefit. Service ticketing is another area of application that the 麻豆原创 Innovation Center Network team is investigating.

With continuous intelligence, service personnel could, for instance, identify hot topics of interests, indicated by an unusually high number of open tickets. Then, they could respond with tailored material for additional information.

Moving at Market Speed

Relying solely on default indicators and monitoring standard KPIs is no longer sufficient when it comes to understanding and responding to the dynamics of complex systems or businesses.

Looking ahead, continuous intelligence is expected to become the norm, as the speed at which businesses must react to rapidly changing market conditions will only increase. It will be a critical component for companies that want to point users to relevant data and trigger actions when it matters most.

Is your business ready to become an intelligent enterprise?

Matthias Uflacker is part of 麻豆原创 Innovation Center Network.
This article was originally published on .

Its health information systems were weak, outdated, and underfunded. Data was manually collected and siloed. Information tended to be listed on paper forms rather than in the cloud.

Given the circumstances, it was difficult for health officials to identify high-risk regions, spreaders, and asymptomatic patients. Administrative delays prevented all but a few labs from testing. But even when the results came in, details about available drugs were hazy at best.

A Need for the Ugly Truth

Aggravating the situation was the nature of the Moroccan healthcare system, which was divided into complicated layers, distinguishing facilities by location, university affiliation, and other categories.

The conditions had officials alarmed about the possibility of COVID-19 exploding up and down the Atlantic and Mediterranean coasts, as well as the country鈥檚 mountainous interior.

To save lives, Morocco鈥檚 Ministry of Health needed to quickly come up with a single source of truth 鈥� whether the truth was ugly or not. At a glance, officials would then be able to gain insights into total confirmed cases, instances of recovery and death, the growth of daily outbreaks across the various tiers of the country鈥檚 healthcare network, and the stock of drugs in various hospitals and regions.

鈥淲e didn鈥檛 have a system like this,鈥� observed Dr. Ahmed Rguig, director of Morocco鈥檚 Centre of Epidemiology. 鈥淲e were very aware that we had to put something in place that allowed us to manage the scale of the pandemic with professionalism and in real time.鈥�

Quickly Partnering to Combat a Crisis

With no time to spare, the ministry turned to the ALGO Consulting Group, an international technology services provider based in the city of Rabat.

ALGO proposed a user-friendly, innovative solution, enabling country-wide monitoring of the pandemic in real time. The application would be available on numerous devices and help officials make accurate decisions swiftly.

As the first partner in Africa to be certified for , ALGO already had experience developing a solution for Morocco鈥檚 transport sector. Now, it went back to 麻豆原创 to use its enterprise software proficiency to help manage the pandemic.

鈥淏ecause of our analytics expertise鈥e could help our country adopt its first-ever digital tracking system in response to the coronavirus outbreak,鈥� noted Naoual Hammane, the 麻豆原创 director working with ALGO.

The use of 麻豆原创 Analytics Cloud allowed for the creation of real-time, role-specific dashboards, which could be accessed via desktops and mobile devices. Every 10 minutes, the control center data would be updated, empowering experts to make efficient, life-saving decisions.

鈥淭wo teams worked in 24-hour shifts to get the project delivered,鈥� said Hammane. 鈥淚 have been managing 麻豆原创 projects for 14 years and this is the first time ever a project has been managed virtually. We used video conferencing and telephone calls.鈥�

Working at Breakneck Speed to Slow Outbreaks

On March 1, 2020, just two weeks after the first case of COVID-19 was recorded in Morocco 鈥� and 11 days before the World Health Organization (WHO) declared the outbreak a pandemic 鈥� the country鈥檚 COVID-19 Real-Time Monitoring system was deployed.

Officials accustomed to tracking down data with phone calls now had all the data they needed at their fingertips.

The results were nothing short of miraculous:

• ALGO developed training videos that enabled users to learn the intricacies of the new system in just four hours.
• Laboratory test capacity increased 100 times 鈥� from 100 to 10,000 COVID-19 tests administered each day.
• The ability to receive IT resources, data, and other technology services increased four times.
• The speed at which information was received allowed the government to deliver tests where they were most needed.
• With the enhanced understanding of the drug stock, allocations could be capably targeted.

Using Mass Media to Save Lives

To ensure that everyone 鈥� regardless of technological capacity 鈥� was informed, the Ministry of Health provided televised updates each night at 6:00 p.m.

The number of lives saved as the result of these broadcasts is impossible to calculate.

鈥淲e can use this project as something to be proud of,鈥� said Dr. Rguig. 鈥淚t demonstrates that we have succeeded in this crisis.鈥�

Its quick deployment of the COVID-19 Real-Time Monitoring system helped the Moroccan Ministry of Heath earn recognition as a 2021 麻豆原创 Innovation Awards finalist. The yearly awards honor organizations that have used 麻豆原创 solutions to improve business and society.

Get all the details about the Moroccan Ministry of Health鈥檚 innovative solution .

Keith Greenberg is an 麻豆原创 global marketing contributor.

In other cases, people can鈥檛 make decisions because they have too much data 鈥� or at least not the right data or analytics to generate relevant, actionable insight. This 鈥渕ore is better鈥� way of thinking about data and analytics leads to an everything-but-the-kitchen-sink approach to making decisions. Not sure what to do? Throw more data at the problem and see what sticks.

But as with most projects, throwing more resources 鈥� both people and data 鈥� at a problem can lead to 鈥渁nalysis paralysis.鈥� In such cases, either you can鈥檛 see clearly through the chaos to make a decision, or you end up applying a bunch of arbitrary, unrelated data to a new kind of problem and coming up with muddled view upon which to make a decision or recommendation. The problem is, it鈥檚 not necessarily the 鈥渂est鈥� one. This, of course, defeats the whole purpose of analyzing data and generating insights in the first place. They are supposed to make us smarter 鈥� help us see things we couldn鈥檛 on our own 鈥� so we can make the best possible decision to drive the best possible outcome and do so faster and with less effort.

The best decisions are made when you look at the right data at the right time and analyze it with the right tools.

This is true for business decision-makers 鈥� and for everyone else, too. For example, before I start a drive, I always check Waze first. I know my preferred and likely best route. But Waze captures real-time data from people actually on the road, deriving traffic patterns, identifying accidents, and more. So, it can provide a data-driven recommendation that ultimately helps me get to my destination faster, safer, and easier.

Put simply, by using Waze, I become more intelligent and therefore able to realize my objective. Similarly, when your organization uses the right data and analytics tools to support decisioning, your enterprise becomes more intelligent 鈥� and thus better able to achieve its goals such as executing strategy, driving revenue, managing costs, or mitigating human capital and business risks.

The question is, how do you avoid the pitfalls of kitchen-sink analytics and analysis paralysis?

麻豆原创 understands this common challenge and has created resources like 鈥�,鈥� which is geared for human resource professionals and talent managers. These questions are designed to help decision-makers think critically about the talent management issues they face and what data and insights will have the greatest impact on their organization.

Rather than looking at the 鈥渒itchen sink,鈥� it is recommended that you select the top 10 to 15 questions that most impact your organization鈥檚 ability to execute your strategy, drive revenue, manage costs, or mitigate human capital and business risks. Selecting a subset is also important for the next steps 鈥� setting targets and assigning staff resources to implement interventions and monitor progress, both of which are more feasible with a smaller number of metrics. The document also provides guidance on selecting key performance indicators (KPIs) that can demonstrate progress toward addressing your specific questions.

For example, if your business strategy is to increase market share, focus on questions relating to talent drivers that impact the execution of that strategy and the metrics that HR should monitor to demonstrate progress toward strategic goals, such as:

• Average manager tenure
• Employee retention index
• Managerial quality index
• Staffing rate 鈥� expatriates
• Training hours per full-time employee

Here are five recommendations for how to select and manage a set of KPIs.

Focus on a small core set of KPIs.

When in doubt, leave it out. Select only as many KPIs as you can actively manage. Resist the temptation to include everything you can measure as a KPI. Use three key criteria: a clear link to strategy, a willingness to set targets against the measure, and a willingness to commit resources to managing progress.

Get management buy-in and continuous support.

The saying 鈥渨hat isn鈥檛 measured, isn鈥檛 managed, and what isn鈥檛 managed, isn鈥檛 done鈥� applies here 鈥� active support from executives helps ensure that progress is tracked. Several organizations involve their CEO or head of business unit in KPI selection workshops, which helps with the challenge of gaining executive support. Firms also routinely report performance against KPIs to their boards or executive committees.

Help ensure data quality.

Nothing makes managing KPIs more difficult than suspect data, so you should spot-check the data needed to populate your KPIs. Conduct a structured data verification process to help ensure definition consistency and data validity.

Communicate performance actively and often.

Keep KPIs top of mind. Reports, social media, e-mails, conference calls, and manager question-and-answer sessions all help reinforce the importance of the business objective being measured by a KPI. You should set targets and use benchmarks wisely.

Revisit KPIs periodically.

As your organization鈥檚 strategy changes, so should your KPIs. Your organization should actively pressure test your KPIs at least once a year.

Armed with the right data-driven metrics and insights, your organization can better execute your strategy, drive revenue, manage costs, and mitigate human capital and business risks.

Want to learn more about the power of data-driven decisioning for human capital management 鈥� and how you can start taking advantage of 麻豆原创 SuccessFactors Workforce Analytics quickly?

• Be sure to download the document.
• Watch and learn how you can for downstream usage, from a library of over 2,000 metrics with built-in intelligence, and .
• And if you just want a little bit of fun, check out our .

For more information, visit .

Tammie Eldridge is part of Solution Marketing for 麻豆原创 SuccessFactors.

For many, Martin Luther King Jr.鈥檚 name is synonymous with his dream of a United States void of segregation and racism. And while his dream has been recognized globally, there is still much work to do to realize it.

I recently sat down with to discuss how people analytics can support organizations’ diversity, equity, and inclusion (DE&I) strategy. Dias is the managing director of as well as the chair and founder of the . He specializes in supporting businesses to make better HR decisions using people analytics and enabling data-driven HR culture.

Q: How does people analytics help HR to solve diversity problems?

A: What areas of your business have the lowest levels of diversity and inclusion, and how bad is the imbalance? Over the years, which HR decisions have caused and added to that inequality? Do different types of employees get promoted differently? Rewarded differently? Hired and retained faster or slower? If you do not change anything, how much worse will the inequality get? If you want to reduce inequality within five years, what HR strategies are most likely to achieve that goal?

With or without data, organizations are making decisions to try to become fairer and more equal. The purpose of people analytics is to enable organizations to make better people decisions; in this case, about achieving diversity goals and solving inequality. By using HR data to answer questions, people analytics helps organizations to make better decisions increasing the likelihood of achieving diversity outcomes across the entire employee experience.

What types of diversity questions are 麻豆原创 SuccessFactors customers answering using their data?

In the 2020 Benchmarking study by the HR Analytics ThinkTank, , which is no surprise given DE&I is a priority for most organizations.

These people analytics functions are empowering their HR leaders to solve diversity problems by supplementing HR expertise with answers gleaned directly from data. From day one, people analytics teams can answer descriptive questions, providing facts about what happened in the past and over time. For example, within a particular job family or location, a specific minority group was three times more likely to be promoted than another. Other functions may go one step further, answering questions that diagnose a problem and use data to answer why an outcome has occurred in the past. For example, they might be able to answer why minority groups are more like to resign in particular locations.

The more advanced functions, which research shows take two to three years to build, will create even more value. Some will be asked to spend more time answering critical questions, predicting how the gender equity gap will increase if nothing changes. The most advanced will provide answers to questions by prescribing what should be done; for example, what strategies are most likely to achieve 25% ethnic minority representation at board level within six years.

How are 麻豆原创 SuccessFactors customers using Workforce Analytics and Report Stories to tackle diversity problems?

The 麻豆原创 SuccessFactors People Analytics solutions has the functionality to support organizations to tackle their diversity issues.

In order to support strategic decision-making, they use 麻豆原创 SuccessFactors Workforce Analytics to transform HR data into metrics and dashboards, showing end users the answers to questions about what has happened in the past, displaying insights and trends over time. For example, where is minority representation worsening? In particular grades, job families or geographies is there a difference in the way in which different workers are promoted or hired? Using 麻豆原创 SuccessFactors Workforce Analytics, HR leaders can create better strategies and track progress over time.

Using report stories, 麻豆原创 SuccessFactors software can provide anyone in the entire business with a snapshot view of their business area. Stories will allow end users to check an answer at any given moment; for example, whether their recruitment pipeline contains a diverse selection of candidates or if all the resignations in the last month have been women.

What steps can 麻豆原创 SuccessFactors customers take to prepare for diversity analytics?

The first thing that organizations should do is confirm the objectives that leaders are trying to achieve and identify the questions they need answered to make better choices. In our 2020 study, 94% of 麻豆原创 SuccessFactors People Analytics leaders said their function was directly sponsored by an HR executive but only 32% were positive that they knew what their leader鈥檚 goals were. HR leaders need to clearly articulate what their diversity goals are and establish what questions they would like answered by the people analytics team.

The second thing they should do is audit the foundations for data-driven HR success and prepare for the journey. According to the same study, only 42% of 麻豆原创 SuccessFactors customers had a plan for what data to capture, only 16% were sure they knew how the people analytics team should be structured, and only six percent were confident that decision-makers understood how to use their insights in decision-making. A lot of diversity questions can be answered on day one using standard 麻豆原创 SuccessFactors data, but a plan will be required to provide more complex answers over time.

The final tip is to provide answers with evidence to help ensure that decision-makers are empowered to actually use the insight. If given the option, most HR and business professionals will welcome evidence that helps them achieve their goals, but they will only use the evidence if it is easy to access and formatted in a way that makes it easy to use in the context of their job. The organizations most successful with data-driven HR make sure that decision-makers are enabled with the right skills, and their dashboards create the best experience for users to find the answers they are looking for.

To hear more on this topic, for the upcoming webinar (or listen to the recording), 鈥溾�� on January 26, or visit .

鈥淲e are providing a holistic solution for clinical trials management, what we call ERP for clinical research,鈥� said Uma Janapareddy, founder and managing director at SyMetric. 鈥淗aving easily accessible data on one unified platform helps researchers develop more effective drugs with stronger study results so they can bring pioneering medicines faster to people.鈥�

People-Driven Clinical Trials

Physicians, researchers, project managers, investigators, and biostatisticians are using SyMetric Trial Analytics to conduct studies at global pharmaceutical companies and clinical research organizations in a variety of therapeutic areas such as neurology, respiratory illness, oncology, and dermatology.

Running on , the solution captures and analyzes historical and updated clinical trial data in one system. This includes patient information indicating initial eligibility to participate in a clinical trial and progress monitoring through rigorous statistical analyses at trial completion for regulatory submission. The tool captures and analyzes electronic data from anywhere, such as a patient鈥檚 activities tracked on a mobile device or artificial intelligence (AI)-based imaging that shows medical progress.

鈥淚f you鈥檙e starting a lung cancer study, you can easily find out disease prevalence rates and research histories by geography, experience of the investigators, availability of skilled coordinators or pharmacists, and other factors. Our solution brings this data together for informed planning that leads to more efficient execution,鈥� said Janapareddy. 鈥淥nce the trial is underway, our easy-to-use solutions help researchers accurately track patient recruitment, study progress, make necessary amendments to the clinical study on the fly, and conduct any other activities.鈥�

Time-Saving Clinical Data Analytics

According to Janapareddy, the solution gives clinicians cost-savings foresight and flexibility. Built-in algorithms automatically monitor data, for example, rejecting potential patients who don鈥檛 fit certain parameters based on gender, age, or certain health and lifestyle conditions. Real-time data saves time in data clean up at the project completion stage.

Customers have reduced clinical trial setup and completion timelines by 20%. Some have saved up to 30% wastage of drug supplies during the trial manufacturing phase. One customer saved thousands of dollars using the solution to calculate the number of patient volunteers, as well as the number of drugs and testing kits required to meet randomization objectives with greater precision.

鈥淲ith real-time data and built-in algorithms, companies can quickly adapt protocols in response to continuous patient recruitment,鈥� she said. 鈥淩esearchers can conduct interim analyses at any time before study completion, adjusting drug dosages, delivery mechanisms, and packaging quantities. The system automatically incorporates protocol adjustments and amendments, sans any downtime and without jeopardizing overall study timelines.鈥�

Working with 麻豆原创 Labs India

While most of 厂测惭别迟谤颈肠鈥檚 customers are based in the United States and India, Janapareddy has set her sights on Europe, inspired by the strength of 麻豆原创鈥檚 innovation ecosystem. An alumni of 麻豆原创 Startup Studio at , Janapareddy appreciated the design thinking workshops her team used to develop use cases from their collective experiences. She also valued the co-innovation relationships her startup has forged with other members of the program. These include biopharmaceutical companies, medical device manufacturers, and cosmeceutical and nutraceutical manufacturers.

鈥淲e have a shared passion with 麻豆原创 for the power of life sciences and integrated enterprise resource planning (ERP) data on a single platform 鈥� where every company becomes an ,鈥� said Janapareddy. 鈥溌槎乖� is a global leader in life sciences including pharmaceuticals, manufacturing, and ERP, and its leaders generously share their expertise with us. We also appreciate the significant exposure to 麻豆原创 customers from this partnership.鈥�

SyMetric Trial Analytics and the SyMetric Clinical Trial Platform are available on .

Connected Clinical Trial Supply Chain

Before she founded SyMetric, Janapareddy held leadership positions at an international non-profit organization that provided funding, education, and other opportunities for underprivileged women. She developed the concept for SyMetric with input from her family and friends at 麻豆原创 and in the life sciences industry.

鈥淚 wanted to do something big in life, contributing to the community in a way that would have lasting impact,鈥� she said. 鈥淭here was no integrated system for clinical trials anywhere in the life science industry, so I founded SyMetric to help manage the entire supply chain for people-centric research.鈥�

From Data-Centric to Patient-Centric Trials

Janapareddy envisioned a fully interconnected data platform for everyone involved in life sciences clinical research and manufacturing.

鈥淭he industry is looking ahead to patient-centricity, where people can control their data using the latest technologies to share information and act on it on secure, compliant cloud-based platforms,鈥� she said. 鈥淚t began with informed consent and now connected data brings researchers and patients even closer together.鈥�

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But as economies have digitized, business leaders now recognize that data is at the heart of digital businesses. It fuels differentiation, strategy, rapid innovation, and other important elements of running a successful business. Moreover, truly data-driven companies tend to generate 8% to 10% more profit and are 23 times more likely to acquire new customers 鈥� which fuels significantly higher market valuation 鈥� compared to their peers.

In the meantime, organizations struggle to unite and access real-time data. Companies generate a lot of data, and while they have good intentions to use that data, it鈥檚 stuck in siloes. That makes it hard to leverage data to optimize business processes across the organization. According to research firm, , 鈥淏etween 60% and 73% of all data within an enterprise goes unused for analytics.鈥�

Below are some suggestions for customers embarking on an enterprise data strategy that will help bring data of all kinds together, allowing companies to turn data into business value.

Leave Your Data Where It Is

Too often companies try to centralize data via a large, top-down project where data from across the organization must be brought into a central repository. The problem with this approach: by the time you bring together data from across different parts of an organization into one place, it鈥檚 outdated.

People need to shift their mindset to connecting 鈥� rather than collecting 鈥� data. When you consider your data strategy, prioritize a digital business platform that can automatically pull data from wherever it resides 鈥� whether that鈥檚 your supply chain or finance teams鈥� applications or somewhere else. Doing that helps ensure your employees can work with real-time information from across the company.

Make Sure You Can Handle All Data Types

Organizations generate all kinds of data 鈥� structured, unstructured, relational, and geospatial, to name a few. Too often organizations approach each type of data differently and separately, which replicates the problem of unconnected data that doesn鈥檛 come together in one holistic picture.

Select a platform with data capabilities that can analyze and knit together these different types into a unified whole. Businesses need a modern platform that treats data as multimodal and multidimensional. By looking at the multiple facets of data, business leaders can make new correlations that help to make better decisions while accurately anticipating future opportunities and threats.

Harness Data to Drive Automation

The real power of data kicks in when you can use it to drive automation and machine-augmented decision-making. There鈥檚 no reason to maintain so many manual processes, like invoice reconciliation or handling basic customer complaints in call centers. If you can harness data appropriately, many types of tasks can be automated 鈥� freeing employees to do more strategic work.

Automation also augments employees鈥� on-the-spot decision-making capabilities. For example, a consumer packaged goods company could use data from cameras and machines to help a quality control manager determine whether to approve a certain batch of products. can process varied pieces of information, such as the Internet of Things (IoT) data or bill-of-material changes, faster than a human, providing an extra level of support on the front lines.

To advance automation, you need a platform that allows you to embed machine learning and artificial intelligence (AI) into your business applications 鈥� and one that can handle varied data sources in real-time.

Democratize Data

While data used to be the preserve of elite analysts and data scientists, now it鈥檚 a priority to democratize data. Information needs to be easily accessed not just by executives but by people on the front lines so they can use it to make decisions. Enabling self-service access to data also reduces the time IT departments spend on manual work, like running reports.

Your platform must make it easy for everyone to access and analyze data, so be sure to evaluate the usability of your data management solutions. Ask questions such as: Is it user-friendly and intuitive? What kind of training is involved to empower people with self-service analytics tools?

Protect Your Data

Related to access is the importance of security. One of the hallmarks of digital business is the ability to seamlessly connect across your organization but also externally to your customers, partners, and suppliers. But this is fraught with risk 鈥� especially in this day and age of ransomware.

Your data platform must take into account any areas of exposure or vulnerability and build in the right security, access controls, and governance to protect your data 鈥� and information shared across your network.

Finally, remember how you use your data will make the difference between success and failure in the next decade. It鈥檚 the foundation of digital transformation and will help launch new digital business models that go beyond automation 鈥� and truly redefine how companies operate and differentiate themselves. provides a platform with database and data management, analytics, and intelligent technology 鈥� like embedded AI 鈥� solutions that customers around the world are already using.

So choose wisely. Because with the right platform, your company will be poised for success now and in the future.

To learn more about this topic, attend the “麻豆原创 Data and Analytics Forum: Accelerating Outcomes,” which will be held virtually from September 14 to October 7. .

Raghu Ramanathan is chief revenue officer for Platform and Technologies at 麻豆原创.