The report analyzed and noted 鈥渋t stands out for its global, industry-specific solutions, with a focus on 麻豆原创 S/4HANA integration鈥� and 鈥湷Т”殊�檚 strategy of integrating applications, data, and AI shows its commitment to unifying data into a single source of truth accessible across the enterprise.鈥� The 21 scoring criteria employed by Forrester Research covered two categories: Current Offering and Strategy.

The Forrester report states that 鈥溌槎乖� offers remarkable data privacy, security, and global compliance with natively supported governance functions.鈥� And it further points out that 鈥渢he introduction of its AI copilot [Joule] indicates 厂础笔鈥檚 direction toward embedding generative AI across its platform for improved quality, adoption, and management.鈥�

“In the context of 麻豆原创 business applications, 麻豆原创 Master Data Governance can offer much more then integration. We have shown this with scenarios embedded into 麻豆原创 S/4HANA, or with federated master data governance deployments across an application landscape, or with integrated end-to-end scenarios for supplier management across 麻豆原创 Master Data Governance and 麻豆原创 Ariba Supplier Lifecycle and Performance,鈥� says Markus Kuppe, vice president and chief product owner of 麻豆原创 Master Data Governance. 鈥淲hen we look at 麻豆原创 Business Data Cloud, which provides semantically rich data from various data sources, we see master data often as the most critical data asset. 麻豆原创 Master Data Governance curates this master data towards a trustful and high-quality treasure and feeds into 麻豆原创 Business Data Cloud as a data product.鈥�

麻豆原创 Master Data Governance allows organizations to create a unified, trusted view of their business to help enable them to work more efficiently and make better decisions. The application is available on-premise as well as in the private and public cloud with support for consolidation, central governance, and data quality management. Customers can establish a cohesive and harmonized master data management strategy across all master data domains to help simplify enterprise data management, increase data accuracy, and reduce total cost of ownership.

To learn more about 厂础笔鈥檚 ranking among top vendors, .

Kaiser Larsen is vice president for Product Marketing, Data & Analytics at 麻豆原创.

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester鈥檚 objectivity .

Behind the scenes, retailers struggle to deliver these experiences due to fragmented, outdated, and incomplete data that makes real-time decision-making nearly impossible and hampers engagement, operational efficiency, and, ultimately, profitability.

The hidden costs of disconnected data

When retailers鈥� data exists in silos, the problem is compounded from all angles. With sales, inventory, marketing, and customer engagement data living in separate systems, retailers lack the clear view of customer behavior and business insights they need to respond with critical actions in real time. Lack of context within the data means businesses struggle to extract meaningful insights.

Consider the impact:

• Limited inventory visibility leads to stockouts and overstocks, frustrating customers and eroding profits.
• Lack of real-time insights hinders personalized customer engagement, diminishing loyalty.
• Disconnected operations make omnichannel fulfillment鈥攕uch as buy online, pick up in-store (BOPIS) or hassle-free returns鈥攄ifficult to execute smoothly.

At a moment when retailers must optimize every facet of their business to remain competitive, a unified data strategy isn鈥檛 optional鈥攊t’s essential.

A data-driven future: Turning insights into action

To break these silos, retailers need a unified data foundation鈥攐ne that consolidates insights across all customer touchpoints, enabling real-time intelligence and business agility. 麻豆原创 Business Data Cloud (麻豆原创 BDC), as recently announced, is an integrated solution that can bring data together from all sources, owned and external, to help create a single, trusted source of truth.

With 麻豆原创 Business Data Cloud, retailers can have the total picture of data from sales, inventory, marketing, loyalty, service, and near-real-time statuses of third-party logistics.

With this holistic view, retailers can:

• Enable seamless cross-channel fulfillment, such as buy online, pick up in-store or return anywhere.
• Optimize operational efficiency for everything from intelligent sourcing and promotional planning to inventory visibility and availability across sales channels.
• Personalize customer engagement by leveraging data-driven insights to boost loyalty and increase revenue.

By shifting to a data-first approach, retailers can move beyond managing transactions to driving intelligent, customer-centric experiences for long-term loyalty and growth.

Why physical stores still matter鈥攎ore than ever

Despite the rise of e-commerce, more than 80% of retail interactions still take place in physical stores. Brick-and-mortar locations remain central to the retail journey, yet, as retailers鈥� largest cost center, they also encompass the biggest operational challenges鈥攆rom inventory carrying costs to labor and store operations.

Although today鈥檚 consumers are fluid in how they shop鈥攔esearching products across multiple platforms or buying online and picking up in-store, for example鈥攖hey still expect accurate, real-time visibility into inventory wherever they engage. In this landscape, data is the lifeblood that allows retailers to orchestrate orders, manage workflows, and ensure that customers can trust the information they see. Yet, according to , 51% of U.S. brands say their organization suffers from “dark data,” which is data that is collected but not effectively used.

To remain competitive, retailers must harness real-time transactional insights to optimize store efficiency, maximize revenue, and provide seamless customer interactions.

Bringing it all together: Intelligent order management

Retailers don鈥檛 just need data鈥攖hey also need actionable, real-time intelligence that helps them drive smarter decision-making. That鈥檚 why 麻豆原创 is integrating advanced order management capabilities as part of our broader data-driven customer experience strategy. 麻豆原创 has a long history of helping thousands of retail and B2C customers manage vast amounts of data. Today we鈥檙e tailoring this expertise, trusted by market leaders worldwide, to help meet the scale, flexibility, and time-to-value required by fast-growing organizations.

As part of the bundle, we are launching the 麻豆原创 Omnichannel Sales Transfer and Audit solution today at in Las Vegas, Nevada. This modular, cloud-native solution can empower retailers with real-time visibility into transactions and inventory, helping to reduce friction and improve customer satisfaction. 麻豆原创 Omnichannel Sales Transfer and Audit can unify POS data from multiple systems, process high-volume transactions in real time, and help ensure inventory accuracy across all channels to improve stock availability, financial reporting, and customer engagement鈥攚ithout the burden of complex, custom-built integrations.

Apart from omnichannel sales and audit capabilities, the 麻豆原创 Order Management Services bundle also includes additional modular, cloud-native capabilities including and the . The 麻豆原创 Order Management Services bundle is natively connected with 麻豆原创 S/4HANA, which can enable retail and consumer products organizations and other consumer brands to unlock real-time inventory visibility, streamline fulfillment, and reduce operational costs without complex and costly custom integrations. And, integrated with 麻豆原创 S/4HANA Cloud Public Edition, retail, fashion, and vertical business, announced at NRF earlier this year, the cloud-native capabilities of the 麻豆原创 Order Management Services bundle can be even more scalable, secure, compliant, and affordable, enabling retailers to realize value more quickly than ever before.

Other benefits of 麻豆原创 Omnichannel Sales Transfer and Audit include:

• Seamless POS integration can connect multiple POS systems with different data structures, working to eliminate silos and ensure data accuracy.
• Real-time inventory updates help keep omnichannel inventory accurate so customers can trust what they see online matches what’s available in-store.
• Smarter data processing and configurable data transfer and aggregation help update inventory, financials, and even loyalty programs effortlessly.
• Optimized sales data validation process can automate checks that are executed through configurable workflows.

By embracing a unified data strategy, retailers can eliminate complexity, reduce costs, and unlock new opportunities for growth鈥攁ll while delivering the frictionless experiences today鈥檚 consumers expect.

Hornbach: The future of omnichannel retail in action

For Hornbach, one of the largest DIY stores in Germany, . It needs to be able to add new channels quickly鈥攁nd to maintain a seamless customer experience over all channels. Hornbach adopted 麻豆原创 Order Management Services as a foundation for this vision, enabling the flexibility to address new markets quickly, connect new systems, process orders rapidly and efficiently, and adopt new innovations. With the addition of 麻豆原创 Omnichannel Sales and Transfer Audit, the Hornbach team expects to get more visibility in day-to-day operations, like checking fraud detection and the completeness of transactions.

鈥淭he most exciting thing will be the combination of all these new technologies we鈥檙e seeing: artificial intelligence, event-driven architecture, as well as native cloud solutions,鈥� said Carsten Mueller, head of Enterprise Architecture and Security, Hornbach. 鈥淭he combination will give Hornbach great power in the next year.鈥�

The future of retail is data-driven

The retail industry is evolving at an unprecedented pace, with AI redefining how businesses operate and interact with customers. According to the same 麻豆原创 Emarsys report, 89% of U.S. consumer product marketers believe AI will be essential for engaging new customers. However, the effectiveness of AI hinges on the reliability and accuracy of the data it processes.

Retailers that embrace AI-powered data intelligence will lead the next era of omnichannel excellence. The future isn鈥檛 just about connecting data鈥攊t’s about activating it in real time to drive seamless customer interactions.

To stay ahead, retailers must:

• Invest in AI-driven analytics to predict demand, optimize pricing, and personalize engagement at scale.
• Implement intelligent order and transaction management to automate fulfillment, reduce friction, and improve supply chain agility.
• Leverage AI-powered customer insights to create hyper-personalized experiences that drive loyalty and lifetime value.
• Enable real-time inventory intelligence to ensure products are available where and when customers need them.

As omnichannel complexity grows, brands that fail to unify their data risk falling behind. 麻豆原创 Business Data Cloud and intelligent order management solutions can provide the foundation for a future-proof transformation. As AI continues to evolve, retailers must shift from reactive decision-making to proactive, predictive commerce, where every transaction is optimized for efficiency and profitability.

The future of retail is here. Those who harness AI to unify, analyze, and act on their data will define the next generation of customer experience and retail success. I鈥檓 excited to partner with companies navigating this transformation and empower them to seize new opportunities for success.

Want to learn more? Stay tuned to see how leading retailers are leveraging 厂础笔鈥檚 data-driven approach to optimize their operations and stay ahead of the competition and learn more about .

Balaji Balasubramanian is president and chief product officer for 麻豆原创 Customer Experience and Consumer Industries.

But what exactly is data federation? And why does it hold so much promise for customers in Saudi Arabia and elsewhere?

To counter the ever-present threat to global supply chains posed by disruption鈥攚hether arising from geopolitical conflict, labor unrest, financial crisis, natural disaster, or other upheaval鈥攂usinesses are turning increasingly to cloud-based solutions to extend visibility and instill resilience across their operations and those of their trading partners, particularly when managing supply chains, logistics, and dispersed capital equipment or other mission-critical assets. Yet just as businesses must assess risk on an international scale to stay competitive, they also must comply with a burgeoning set of regulations around the world requiring operational data to reside physically within a nation鈥檚 borders. By applying cloud-based solutions, businesses can transact commerce through global digital networks while adhering strictly to regional data residency requirements through an approach known as data federation.

Data federation permits operational information from disparate sources to be accessed and updated as though it resided in a single, unified location. Instead of moving or copying data from one system to another, federation provides users with real-time access unburdened by duplication.

Federation becomes crucial when an organization must unify its data across different storage platforms while ensuring the integrity and security of the underlying operational sources. This becomes particularly vital for companies with complex data architectures, whose data may reside in 麻豆原创 systems, cloud data lakes, or third-party applications. Data federation brings multiple advantages, especially in hybrid or multi-cloud environments, including global access, cost efficiency, unified governance and security, and faster time to insights.

But the advantages extend still further. With the launch of our KSA data center, 麻豆原创 Business Network core services have been deployed. This includes multilingual support, such as proficiency with languages read right-to-left like Arabic, and a Federated Trading Partner Index Service for routing transactions between different data centers. Saudi customers can thus adhere to local data privacy regulations while retaining the ability to collaborate and transact with trading partners around the world.

Why Is This Important?

With the deployment of 麻豆原创 Business Network in the KSA data center, public sector or critical national infrastructure (CNI) customers and prospects in KSA can rest assured that regulations have been followed strictly, allowing these organizations to transact on 麻豆原创 Business Network for Logistics and 麻豆原创 Business Network Asset Collaboration. Data federation helps ensure that trading partners can find each other, regardless of where they may be registered.

What鈥檚 Next?

The deployment of 麻豆原创 Business Network for Logistics and 麻豆原创 Business Network Asset Collaboration for Saudi customers in the public and critical national infrastructure sectors, for whom data federation is crucial, marks only the initial step. Later this year, both products will become available for private-sector customers in KSA as well. and will also be deployed in the KSA data center in coming quarters. Meanwhile, 麻豆原创 will continue to expand its data center footprint and data federation program across the globe, with the expansion of 麻豆原创 Business Network capabilities throughout 2025 and beyond.

For information on 麻豆原创 Business Network and how we are equipping enterprises with business AI and related capabilities needed to instill resilience, counter disruption, and foster collaboration, visit and .

J枚rn Keller is chief product officer for 麻豆原创 Business Network.

Manufacturing-X was launched as part of the Industry 4.0 platform, with the aim of promoting digital ecosystems and establishing an international standard for data exchange. It is an industry-wide initiative of the German government with various projects for different industrial sectors.

“The realization that the digitalization of industry is inevitable has become the norm over the past few years,” says Georg Kube, head of Industry Data Ecosystems at 麻豆原创 SE. “A variety of use cases for different industries and new business models have been developed. They are successful 鈥� but only as long as companies work with other companies with which they already have a close partnership.”

“The most well-known of the [Manufacturing-X] projects is certainly Catena-X for the automotive sector,” Kube says. “The common aim of all these projects is to establish a new form of data exchange.”

For example, an automaker that wants to digitally integrate its direct suppliers typically requests all the data about the supplied parts from its partners, and the suppliers usually feel comfortable providing this data because of the trust that has grown over the years between the partners.

But it鈥檚 different when data is needed from companies without a direct business relationship. “A typical example is the determination of a vehicle’s CO2 footprint,” Kube says. “Suddenly, information about the CO2 footprint of the smallest plastic parts is needed, which may come from companies in the supply chain with which a company has never had direct contact. It’s not easy to access that data.”

Click the button below to load the content from YouTube.

Always allow YouTube

Trust Is the Catalyst

Companies are often very hesitant to share data freely. And for good reason: potential inferences about their cost structure or the nature of their production can be drawn from the data.

“On the one hand, as companies, we hesitate to give out our data. But on the other hand, we rely on the data of others in order for digitalization scenarios to be successfully implemented,” Kube explains. “We want to address this problem within the framework of Manufacturing-X through a new [approach to] industrial data sharing.”

“The promise,” Kube continues, “is that the digitalization, which we can currently complete up to 70%, can be fully implemented.”

Information Transfer 鈥� But Secure

“What companies lack the most today is knowledge,” Kube says. “We constantly hear from 麻豆原创 customers that they would pay to find out what their own customers are doing with the products they have sold to them.”

For example, a manufacturer of robot grippers receives few insights after selling its product about where the grippers are located and what they are used for. If this were not the case, the manufacturer could make much more informed decisions about which generation of products the market needs, or whether a completely new model needs to be developed.

However, customers have concerns that this information could lead to inferences about the nature of their production and the finished product, or that this type of application might be prohibited.

With Manufacturing-X, a scenario has been created in which data sovereignty remains with the owner of the data, but the data can be provided within a narrow framework with a legal and technical structure that prevents abuse. This is the essence of a whole range of use cases in areas such as manufacturing-as-a-service, sustainability, and others.

“These use cases basically exist independently of Manufacturing-X,” Kube explains. “Most of them are neither new nor original. They just could never be fully implemented because trust in data exchange was lacking 鈥� and Manufacturing-X finally creates the conditions for this.”

厂础笔鈥檚 Role

As an enterprise software company, 麻豆原创 has a strong interest in completing the digitization of its customers.

“The digitalization of industry works very well with 麻豆原创 products,” says Heiko Flohr, head of Product Management, 麻豆原创 for Discrete Industries & Industry Networks, at 麻豆原创 SE. “Most of the world鈥檚 leading companies use 麻豆原创 in some way to digitize its next-generation processes. Therefore, it is clear from our perspective that we must support and drive this emerging industry standard for data exchange.”

Kube notes that medium-sized companies in particular often suffer from the unavailability of data. “For this customer group, we offer a comprehensive, easily consumable application portfolio with ,鈥� he says. 鈥淭he goal is to establish industrial data sharing according to Manufacturing-X standards as a solid part of this portfolio and enable our customers to collaborate more effectively and trustfully with their supply chains.”

Within Manufacturing-X, new sovereign data exchange formats are to be created for the industry, based on European Union values such as transparency, controllability, portability, and interoperability. “We work very collaboratively and with a focus on implementation in various industry-specific initiatives to make this vision a reality,” says Mirko Paul, head of Industry Cloud Architecture at 麻豆原创. “Based on state-of-the-art, cloud-based architectures and the scalable technology standard of 麻豆原创 Business Technology Platform, we ensure that these new standards are compatible with 麻豆原创 applications from the outset and pre-integrated for relevant business processes.”

At the same time, 麻豆原创 opens its own products and applications that are already on the market. Products and solutions such as and products in the areas of supply chain and sustainability are to be equipped with connectors that will allow them to work with this new standard.

Here, she shares about how the pair work together to help supercharge customers鈥� digital transformations.

Q: Can you give a little background on 麻豆原创 Business Transformation Center?

A: 麻豆原创 Business Transformation Center was envisioned as a one-stop shop for customers that want to transition from 麻豆原创 ERP Central Component (麻豆原创 ERP) 6.0 to 麻豆原创 S/4HANA. The challenges to such a transformation are, of course, numerous and daunting. Customers need to cull current data, pull together fragmented tool sets, line up the right human resources, and keep an eye on time to value.

With 麻豆原创 Business Transformation Center, we鈥檝e done our best to bring together the latest functionality and expert guidance to smooth the way 鈥� in a single, powerful software-as-a-service (SaaS) offering. And 麻豆原创 Business Transformation Center is easily accessible, deployed on 麻豆原创 Cloud ALM atop 麻豆原创 Business Technology Platform (麻豆原创 BTP). It comes with any implementation of RISE with 麻豆原创 or any cloud solution from 麻豆原创 and can be ready to use in less than half an hour.

Q: Where can customers go for further details?

A: The support materials at include a quick summary of features and benefits, along with the .

Q: What does 麻豆原创 see as the core mission of 麻豆原创 Business Transformation Center?

A: Kilian Carolan from the Premium Hub 鈥� CoE Ireland Data Management has described the mission this way: 鈥淭o play an active part in the 麻豆原创 S/4HANA adoption journey by supporting key data management and data migration topics and to serve as the trusted advisor for our customers.鈥� He continues to explain that we do this through end-to-end support, including hands-on execution, optimization, transformation, upgrade, and migration of Big Data and data platforms. In short, we apply our vast portfolio of enterprise information management and landscape transformation tools, methodologies, and processes to the customer鈥檚 unique transformation scenario.

Q: Where are we in the ongoing evolution of 麻豆原创 Business Transformation Center?

A: Our first step was to help customers fully understand the structure of their 麻豆原创 legacy systems through the digital blueprint. This supplied the background they needed to begin scoping the transformation project. And now we鈥檝e completed the second step for moving data across to the target system 鈥� with lean selective data transition for 麻豆原创 S/4HANA.

Q: What exactly does the lean selective data transition for 麻豆原创 S/4HANA do?

A: Data transformation is traditionally a highly complex undertaking, and we鈥檝e made a huge dent in that complexity. Right at the start, lean selective data transition for 麻豆原创 S/4HANA helps radically reduce the decision-making efforts involved in choosing data to migrate. The underlying principle is to provide smarter suggestions and fewer difficult choices through market-leading services and tools 鈥� and end-to-end advice on making the most of them. That approach helps customers ensure that they only move data that will continue to be useful, reducing the volume of data for the testing and go-live phases and accelerating the transition exponentially.

With lean selective data transition for 麻豆原创 S/4HANA, customers can pare down 麻豆原创 legacy data and bring the target system live with a clean data foundation. In combination with the digital blueprint, lean selective data transition for 麻豆原创 S/4HANA can give 麻豆原创 Business Transformation Center the power to do all the heavy lifting of accessing source systems; extracting, transforming, and loading relevant data; and validating data for completeness, consistency, and correctness.

Q: What types of data can customers choose to exclude from the transfer?

A: For example, they could decide to completely ignore obsolete company codes, such as data for companies they have since divested or which are no longer in use.

Q: What does the wider market see as the single most revolutionary aspect of lean selective data transition for 麻豆原创 S/4HANA?

A: For the very first time, 麻豆原创 provides standard functionality not only for complete rebuilds, greenfield implementations, system conversions, or brownfield implementations, but also for projects somewhere in the middle. This is a third path, if you will, and it鈥檚 a holistic approach to the big transformation from 麻豆原创 ECC 6.0 to 麻豆原创 S/4 HANA Cloud Private Edition.

Q: Can you take us a little deeper into how lean selective data transition for 麻豆原创 S/4HANA works and how customers can benefit?

A: With the 麻豆原创 Readiness Check tool for 麻豆原创 ERP usage and data profiling, we can collaborate with the customer to read the data from the source system and identify legal entities that are no longer in use or will soon be obsolete. 麻豆原创 Business Transformation Center then can propose that these entities and the associated data are “removed from the scope” before starting the data transition and can provide clear instructions on how to do this. It can also help to identify customer-specific data in the 麻豆原创 legacy system. Here, too, the customer has the option of leaving this data behind on the way to 麻豆原创 S/4HANA to support its clean core strategy and move closer to the standard again.

Both these jobs would previously have meant time-consuming manual work for the solution architect 鈥� and higher costs and longer time to value for the customer. With the addition of lean selective data transition for 麻豆原创 S/4HANA to the already popular functionality for digital blueprinting, 麻豆原创 Business Transformation Center can now provide optimal support and transparency in each phase of the transformation project. It helps customers analyze the source system, define migration scope, create migration cycles, and finally transform the leaner body of data they鈥檝e elected to move across. From strategy to execution, we serve as a trusted partner, helping to ensure that every step of the way leads to meaningful insights and sustainable results. And that lowers both total cost of implementation (TCI) and total cost of operation (TCO).

Q: What have customers been saying about lean selective data transition for 麻豆原创 S/4HANA?

A: Long-term partner BMW Group, for example, has told us, 鈥淭his feature significantly speeds up our evolution into an intelligent enterprise by applying sustainable and efficient solutions and methodologies.鈥�

Karin Baeumler is part of Go-to-Market, Business & Data Transformation Solutions, at 麻豆原创.

Most have been in this situation before: one of the providers or services we use is a victim of a data breach and we want to determine if our personal user data has been impacted. This is where fully homomorphic encryption (FHE) comes into play. With FHE, the encrypted, personal password is compared against the data set of stolen user data and potential matches are identified without ever revealing the user鈥檚 password.

Use cases for this type of privacy-enhancing technology (PET) are numerous. They range from applications in medicine, where third-party service providers can analyze health data without compromising a patient鈥檚 privacy, to performing machine learning and AI algorithms on encrypted data, allowing organizations to derive insights from sensitive data sets without exposing the data to potential breaches or privacy violations.

How It Works

Fully聽homomorphic聽encryption聽allows calculations to be performed on encrypted data without having to decrypt it first. Confidentiality is maintained, as even the results are encrypted and can be viewed only with the appropriate decryption key. Further techniques for processing encrypted data are multi-party computation (MPC) and trusted execution environments (TEE).

Mathias Kohler, research manager at 麻豆原创 Security Research, outlines the differences: 鈥淲hile FHE is the most known of the encryption technologies, MPC is the ideal candidate if working with several parties exchanging encrypted data across company borders. And it can be substantially faster than FHE.鈥� While both are software-based technologies, TEE is hardware-based, which makes it the fastest choice. The downside: TEEs, unlike MPC and FHE, require decrypting the data for processing. While decryption happens in a trusted hardware environment isolated from the operating system, it can allow data leakage via side-channel attacks. Notably, PETs do not need to be considered in isolation and can augment each other. For example, MPC can encrypt and distribute an FHE decryption key, protecting the FHE key and ensuring no single party can decrypt everything.

Why It鈥檚 Relevant

There is a demand for this kind of technology. By 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing, according to .

Fully homomorphic encryption has numerous applications, especially in scenarios where privacy and security are paramount, such as secure computation in the cloud, privacy-preserving data analysis, and secure outsourcing of computations. As long as one party is performing the data processing centrally, FHE is the encryption method of choice. FHE enables organizations to share encrypted data with partners or third parties for analysis or monetization purposes while maintaining data confidentiality. This is particularly relevant in industries such as advertising and market research.

Interesting use case scenarios from 厂础笔鈥檚 perspective could be secure benchmarking and predictive maintenance.

Secure Benchmarking

Companies often assess their competitiveness relative to industry peers and compare business-relevant KPIs, such as automation rate or return rates, with peers and even competitors. With fully homomorphic encryption, all participating parties can share encrypted KPIs without revealing individual data. As a result, they learn about relevant statistics, such as averages or medians, to assess their relative competitiveness and decide where to improve and invest.

Predictive Maintenance

Predictive maintenance is a machine learning technique to forecast demand for maintenance or spare parts based on historical data. “In certain industries, required data, such as usage patterns and failures, is considered sensitive and is not easily shared with data scientists or maintenance operators,鈥� says Anselme Tueno, senior researcher at 麻豆原创 Security Research. By computing on encrypted data, however, no sensitive information is revealed while still allowing for the required insights to be gathered for prediction tasks.

Carbon Footprint Calculation with Multi-Party Computation

While it is early days from a product availability perspective, 麻豆原创 is working on potential use cases with customers and partners. One key example is calculating carbon footprints of products.

Prime examples for complex collaborations are today鈥檚 supply chains, intricate networks that encompass various levels of suppliers, manufacturers, and processed goods. Unfortunately, there is often a lack of comprehensive visibility across the entire process 鈥� either for technical reasons or because businesses are often reluctant to share sensitive data across supply chains that often include direct competitors.

However, to accurately assess and disclose a product鈥檚 carbon footprint, sensitive production details and associated carbon costs for production-relevant parts and materials are required. Here, MPC can reveal only the required carbon footprint without disclosing associated, proprietary manufacturing details with other supply chain participants.

Currently, 麻豆原创 is working with Bosch on cloud-native software for secure multi-party computation called .

鈥溌槎乖� participates in this open-source project and supports the development of Carbyne Stack’s storage and processing services and the deployment of Carbyne Stack on Amazon Web Services (AWS),鈥� Kohler explains. 鈥淔or Bosch, Carbyne Stack is a type of cloud-native operating system for MPC workloads that manages resources to run as efficiently as possible in multi-cloud deployments.鈥� This effort can help 麻豆原创 in the long run to integrate MPC as technology into 麻豆原创 solutions and services while running in a cloud-native environment.

What鈥檚 Next?

Despite all the benefits around processing data, encryption introduces significant computational overhead due to the complexity of performing operations on encrypted data. Slow processing speeds, especially for complex operations and large data sets, makes fully homomorphic encryption impractical for real-time applications or large-scale data processing. Although the performance of FHE has greatly improved in recent years, its practical adoption is still limited due to the processing overhead and performance considerations. Ongoing research is focused on the design of FHE-specific hardware accelerators.

鈥淧ETs for computing on encrypted data have the power to amplify data-driven business collaborations and reshape the future of cloud computing,鈥� explains Jonas B枚hler, senior researcher at 麻豆原创 Security Research. By safeguarding data, they enable access to previously untapped information while minimizing privacy risks and thwarting data breaches. The future of computing is encrypted.

麻豆原创 Datasphere can offer that path. Its native connectivity to 麻豆原创 BW means customers can reuse up to 80% of existing 麻豆原创 BW content, retaining value while adding cloud speed, scale, and interoperability and avoiding costly and unnecessary rework. 

Delivering meaningful data to every data professional requires a comprehensive cloud data service. With 麻豆原创 Datasphere, organizations can:  

• Access authoritative data, accelerating time-to-value by automatically reusing the semantical definitions and associations from 麻豆原创 applications.  
• Enrich all data projects, harmonizing heterogeneous data into a business semantic model of their diverse data landscapes.   
• Simplify the data landscape, accessing all their data across hybrid and cloud environments no matter where it resides. 

麻豆原创 has also partnered with an open data ecosystem of leading technology vendors to provide tailored integration between 麻豆原创 Datasphere and their solutions. The first set of industry-leading data and AI vendors includes Collibra, Confluent, Databricks, DataRobot, and Google Cloud. By closely integrating their data and AI platforms with 麻豆原创 Datasphere, organizations can access their mission-critical business data across any cloud infrastructure. 

Flexible Paths to the Cloud  

Many 麻豆原创 BW users have always-on projects that depend on 麻豆原创 BW data and objects, which requires flexibility in modernizing to the cloud.  

麻豆原创 offers flexible paths. Whether you’re moving directly or integrating 麻豆原创 Datasphere as part of your data landscape to enhance your 麻豆原创 BW deployment, there’s a strategy:  

• Gradually transition functionality over time using to reuse and integrate 麻豆原创 BW objects. 
• Leverage 麻豆原创 BW data ingestion and staging to accelerate the move or, for 麻豆原创 Business Suite customers without 麻豆原创 BW, move directly to 麻豆原创 Datasphere. 
• In some cases, migrate 麻豆原创 BW systems to 麻豆原创 Datasphere for a complete transition. 
• Modernize with a combination of 麻豆原创 Datasphere and 麻豆原创 HANA Cloud to benefit from the capabilities of both solutions. 麻豆原创 Datasphere can provide the foundation for a business data fabric, while 麻豆原创 HANA Cloud enables the development of intelligent data applications.   

The goal is to provide options to fit each customer’s unique environment and timeline. With the right approach, the move to 麻豆原创 Datasphere can be straightforward while optimizing previous investments. 

Our experienced 麻豆原创 partners understand the importance of flexible paths. They work with our customers to outline customized modernization paths that can safeguard their technology and fit their goals.

鈥淲e are excited to help 麻豆原创 BW customers experience the power of 麻豆原创 Datasphere. We鈥檝e already seen multiple customers take this modernization approach and it鈥檚 the ideal modernization path to protect the customer鈥檚 existing 麻豆原创 BW investments.鈥�

Deepu Sasidharan, Vice President, Analytics, Applexus

No matter which path a customer takes, they can always progress to 麻豆原创 Datasphere. Technically, this can be achieved with the support of 麻豆原创 Datasphere, 麻豆原创 BW bridge and modernization tools. That鈥檚 why customers like chose 麻豆原创 Datasphere.

鈥溌槎乖� Datasphere, 麻豆原创 BW bridge is a complete game changer. The cloud architecture allows us to simplify our landscape. We are also seeing significant improvements in our performance.鈥�

Iaroslav Korzh, 麻豆原创 Technology Manager, Nipro Europe Group Companies 

New Professional Readiness Assessment 

Whether you鈥檙e starting fresh or modernizing an existing system, having a solid plan is key for a successful move to the cloud. 

麻豆原创 is now offering a limited-time, complimentary 麻豆原创 BW system assessment to help you optimize your transition to 麻豆原创 Datasphere. Through this assessment, you can gain insight into your 麻豆原创 BW environment and learn which objects are active and frequently used and whether they can be migrated.  

This assessment helps deliver a reliable basis for an actionable modernization plan. With the right information, you can modernize on your terms. Get started today by applying for your complimentary . 

Get Started  

Visit our for the latest modernization tools, including our , , and .听

麻豆原创 BW customers moving to 麻豆原创 Datasphere may also qualify for exclusive incentives. Contact your 麻豆原创 representative before this limited-time opportunity expires. 

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

To achieve true digital transformation, organizations must have seamless access to their mission-critical business data no matter where it resides. Yet with data landscapes distributed among different applications and systems both in the cloud and on premises, organizations spend countless resources extracting, rebuilding, and integrating their data.

By leveraging the right data integration tools and strategies, organizations can easily discover, connect, integrate, govern, and orchestrate their data assets. Data integration offerings from 麻豆原创 deliver trusted, relevant, and timely information to enable customers to simplify their data landscape and unleash the power of business data. Our primary solutions include , Cloud, , and . These offerings are part of (麻豆原创 BTP).

Gartner evaluated 21 vendors and named 麻豆原创 a Leader based on our 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision.鈥� We believe this recognition serves as acknowledgment of 厂础笔鈥檚 continued commitment to providing our customers with world-class data integration tools.

Unleash the Power of Business Data

Data integration is necessary for customers to gain intelligent, relevant, and contextual insights for better decision-making. However, without the right data management approach and technology, companies can face an uphill battle in integrating, processing, curating, governing, and augmenting 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.

It eliminates the need to recreate the business context that was lost from extracting and replicating data. This 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 鈥� and 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 semantical 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.

Since the launch of 麻豆原创 Datasphere, we have seen tremendous growth of customers innovating with this technology. For example, Messer CIO David Johnston describes his experience with the solution this way:鈥淭he business data fabric architecture enables us to bring 麻豆原创 and non-麻豆原创 data together in the seamless and self-service way we’ve been envisioning. 麻豆原创 Datasphere provided us with a solution to build a harmonized layer, or business data fabric, across 麻豆原创 and non-麻豆原创, cloud or on-premise data sources, making the best use of our existing investments in 麻豆原创, Microsoft Azure, Salesforce, and Oracle.鈥�

Next Steps

For over 16 years, data integration tools from 麻豆原创 have enabled our customers to turn disjoined data assets into actionable business insights at scale. Take the next step and begin your business data fabric journey today:

• Visit the
• Try the free
• Read the

Kaiser Larsen is vice president of Data and Analytics at 麻豆原创.

Gartner, Magic Quadrant for Data Integration Tools, Ehtisham Zaidi, Robert Thanaraj, Sharat Menon, Thornton Craig, Roxane Edjlali, Michele Launi, 4 December 2023
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.

As the NHL continues to grow, the League continues to prioritize technology adoption to help advance the game and provide more engagement opportunities for fans.

Chris Foster, NHL vice president of Digital Business Development, explains: 鈥淎s our relationship with 麻豆原创 grows and technology advances, we pivot quickly to meet new demands and address our challenges with intuitive technology through 麻豆原创 Preferred Success services.鈥�

Unlocking the Power of Data with Partnership

The NHL is a rich tapestry of unforgettable moments, legendary players, and enduring passion that has captured the hearts of fans worldwide. To inspire and keep generations of new fans entertained and engaged, the League understands the importance of continuously innovating the experience in the arena and through its national broadcast partners.

鈥淥ur digital transformation efforts are not only boosting fan engagement across NHL platforms, but also increasing parity among our 32 clubs,鈥� Foster says. 鈥淲e are looking at data differently, ensuring it reaches the right people 鈥� our fans, players, coaches, and clubs.鈥�

This mindset on finding opportunity in data launched a series of innovations focused on enhancing the game and improving venue sustainability. With 麻豆原创 Preferred Success, to implement a platform that jump-started its ability to build and expand use cases over time to help meet changing business dynamics and objectives.

鈥溌槎乖� Preferred Success is instrumental in making all this work,鈥� Foster underscores. 鈥淎ccess to personalized, prescriptive recommendations from subject-matter experts and quality reviews enables us to create a customized and personalized solution.鈥�

Connecting Fans with Their Favorite Clubs

The first project the NHL delivered in collaboration with 麻豆原创 was transforming 鈥� creating a definitive destination for hockey analytics. Last season alone, more than 100 million data-hungry NHL fans engaged with the site’s intuitive dashboards and filters to analyze the performance of their favorite clubs and players and compare them to past NHL legends.

鈥淲e saw the potential to create a one-stop shop that uses stats to better connect our audiences with their favorite players and teams, understand the strategy of the game, and see trends more broadly across the League,鈥� Foster shares.

Working with 麻豆原创 Preferred Success, the NHL tapped into a database that has evolved into to help store and manage data points like never before. The effort digitalized more than 100 years of historical hockey data and introduced new and enhanced statistics in a way that enthusiasts can find visually appealing.

Foster adds: 鈥淭here are also unlimited storytelling opportunities as we provide our fans with a personalized and interactive experience.鈥�

Elevating Plays with Data Intelligence

Following the digitalization of its stats, the NHL co-developed one of the most significant technologies resulting from its partnership with 麻豆原创 Preferred Success 鈥� the , which runs on the League鈥檚 iPads. 麻豆原创 HANA Cloud again serves an integral role as the processing power that helps translate all in-game hockey data from the arena and the NHL’s system to the mobile app.

鈥淎s the fastest game on ice, there are millions of data points to be collected and analyzed every second across our 32 clubs,鈥� Foster says. 鈥淲e knew we needed to deliver a tool that could serve every club with very different expectations, different coaching staff structures, and different responsibilities.鈥�

Equipped with the advisory checks introducing development and administration readiness, capability advisory, and design discovery that 麻豆原创 Preferred Success offers, the NHL increased developer productivity for the mobile app development. Making real-time, customizable player statistics and data visualizations accessible during the game allows coaching staffs to adjust in-game tactics and achieve new levels of individual player and club performance.

For example, the data tiering functionality of the 麻豆原创-NHL Coaching Insights mobile app on the League鈥檚 iPads differentiates between in-game and past seasons’ NHL EDGE Puck and Player Tracking data. In-game data is analyzed in real time with the quick in-memory processing of 麻豆原创 HANA Cloud, processing puck and player position coordinates every 30 milliseconds. Meanwhile, gigabytes of NHL EDGE Puck and Player Tracking data are archived instantly, stored cost-effectively and securely, and reactivated readily and swiftly for further analysis.

Throughout this use case, 麻豆原创 Preferred Success helped the NHL better understand the stability of the system to reduce data duplication and storage while still providing a powerful processing engine that brings accurate data to the user rapidly. The services also helped deliver security and connectivity reviews and performance optimizations to help ensure the NHL coaching staffs have the best possible experience. In fact, with visualizations made possible by the solution, the League can review each clubs鈥� app usage to improve the app further and tailor it to their evolving needs.

Going Green with NHL Venue Metrics

In addition to elevating the fan experience and enhancing the game on the ice, the NHL is also working to reduce its ecological impact while preserving the sport’s roots for future generations. The League developed to collect, process, and report energy and water consumption, waste generation, and recycling frequency across NHL clubs and arenas 鈥� which plays a key position in its NHL Green platform.

The end-to-end, cloud-based application is the NHL’s latest and extended use of 麻豆原创 Business Technology Platform (麻豆原创 BTP), delivered through the prescriptive guidance of 麻豆原创 Preferred Success. Data is processed through 麻豆原创 HANA Cloud and visualized with 麻豆原创 Analytics Cloud, helping give venues the insights to embed sustainability best practices into their business operations wherever possible.

鈥淭he development of NHL Venue Metrics enables us to define new sustainability goals and standards as a League,鈥� Foster remarks.

Building a Future of Game-Changing Outcomes

A critical lesson the NHL learned throughout its experience with 麻豆原创 Preferred Success is the value of expert guidance and support 鈥� fast-paced innovation enabled through skillful teamwork. Each step in the League’s innovation journey progresses with best practices, targeted learning, in-depth release guidance, and prioritized incident handling 鈥� all aimed at evolving and improving the overall growth of the game.

鈥淲e certainly have clear goals and specific objectives for the future of the NHL. But it’s equally important to have in-depth expertise to ensure business solutions are doing all they can to help us reach our vision. It takes experience in seeing what others have done, what’s worked well, and what you should avoid,鈥� Foster reflects.

By working with 麻豆原创 Preferred Success, the NHL gained a trusted partner that helps it map out and provide prescriptive advice on configuration steps, modeling, performance testing, and more. All this work culminates in a smooth rollout and adoption experience across NHL club coaching staffs.

Foster concludes: 鈥淥ur collaboration has allowed us to continue to evolve and deliver additional stable and reliable applications that increase productivity, improve efficiency, and reduce costs.鈥�

To learn more about the value of 麻豆原创 Preferred Success and how the NHL is innovating, look at the following resources:

Amit Lodhe is global solution owner of 麻豆原创 Preferred Success for 麻豆原创 BTP at 麻豆原创.

Top image courtesy of the NHL

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.”

Click the button below to load the content from YouTube.

Always allow YouTube

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.

Now, by harnessing the power of 麻豆原创 Business Technology Platform (麻豆原创 BTP), the Association — which joined me on stage during our 麻豆原创 Sapphire event a few months ago — aims to optimize its rich array of data sources, paving the way for more informed decision-making and elevated experiences for players, fans, and the game of tennis.

Click the button below to load the content from YouTube.

Always allow YouTube

Having watched the Wimbledon finals, I am mesmerized by how players make split-second decisions in such a fast-paced game and hit almost every ball perfectly. The pressure on the center court is definitely immense!

During the course of the match, players take many shots, and every single one matters. How can players react so quickly and apply all their experience and training to their actions on the court? They need a winning strategy, confidence in their strengths, and the 鈥渕uscle memory鈥� built from continuous training. This allows them to perform on the court and react to the opponent鈥檚 ball in split seconds.

As a hobby tennis player myself, I love the feeling of landing a perfect shot; that is, when I know the shot is going to be a winner as soon as it comes off my racket. My serve is not too bad either. As a chief technology officer, I can also draw analogies to my other passion: data — and winning good insights from it.

Wouldn鈥檛 it be perfect if executives could make decisions like professional tennis players? With confidence in their winning strategy, and equipped with corporate muscle memory built from years of experience and practice to enable them to be both proactive and reactive in their day to day work?

Just like tennis players, companies need to test their strategy and feed their muscle memory again and again — based on trusted data insights. And like the tennis players on the court, executives need to have a vision coupled to a winning strategy, and the ability to make quick decisions that are based on real-time information. Data plays a key role in this: having data in one place and accessing it whenever it鈥檚 needed is essential for effective decision-making.

We at 麻豆原创 are equipping organizations to do just that with new tools like the “Just Ask” feature in 麻豆原创 Analytics Cloud, which applies generative artificial intelligence (AI) and foundation models to search-driven analytics. This is also where 厂础笔鈥檚 more than 50 years of experience in technology and our solutions come in, which enable companies to win in their own competitive environments.

I could not be more thrilled that the WTA and 麻豆原创 are celebrating the Women鈥檚 Tennis Association鈥檚 50th anniversary together and are joining forces to transform the way data is managed and applied in women鈥檚 tennis.

This latest collaboration between 麻豆原创 and the WTA marks a significant milestone in our partnership as the WTA embraces a data-driven approach to shape the future of the game.

Congratulations WTA, to your 50th anniversary. I think we make perfect doubles partners. Game, set, match!

Learn more about the WTA鈥檚 .

Juergen Mueller is CTO and a member of the Executive Board of 麻豆原创 SE.

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.

Learn more about .

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.

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.

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.

One company with extensive expertise in ESG reporting is , the world鈥檚 largest brewer. The company鈥檚 strategy for growth through the digitization of its ecosystem 鈥� which includes 200 breweries, 6 million customers, and over 2 billion consumers, generating over 10 million weekly transactions 鈥� involves a lot of data.

The Right Data

鈥淏rewing requires the best ingredients, which requires a healthy environment. We are an agribusiness. We see the far-reaching implications of climate change in our operations and sourcing regions,鈥� said Ezgi Barcenas, chief sustainability officer, Anheuser-Busch InBev. 鈥淲ith operations in over 50 countries, we鈥檙e looking at many metrics. Just inside our walls, we have 400 operating practices for tracking efficiency, water, energy, maintenance, and sourcing, to name a few.鈥�

Barcenas explained that as the company looks at its supply chain, it must think through the environmental and social impact up- and downstream, from the smallholder farmers down to the half million SMEs that are its customers selling its products around the world, all the mom-and-pop shops as well as the big chains.

鈥淭hat鈥檚 a lot of data,鈥� she said. 鈥淣ow add all your research and innovation data, security data, and ideas about the future of packaging and logistics. The point is, sometimes you need better data, not more. You need to ask yourself: is this data useful for making decisions? Does it help drive the right actions through the business?”

Another data-heavy company participating in the discussion was Schneider Electric SE, a French multinational specializing in聽digital automation and energy management for buildings, data centers, infrastructure, and industries. By 2025, thanks to its energy and sustainability services and green product innovations, it will have and avoid 800 million tons of CO2.

鈥淲e need to triple our speed to avert climate disaster. Reporting scope 3 emissions is extremely important, because we can only track what we measure and we can only improve if we measure,鈥� said Michael Lofty, senior vice president, Power Products, Schneider Electric. The good news is that about 70% of Schneider Electric鈥檚 revenue already comes from green solutions. The company invests heavily in innovation. 鈥淎ny innovation coming from Schneider Electric is a sustainable offer,鈥� he explained. 鈥淓ach product is more sustainable than the one before it, and metrics are key proof points.鈥�

At Schneider Electric, the main challenge was to get suppliers on board the sustainability journey. The company launched a Zero Carbon Project to help 1,000 suppliers responsible for 70% of its upstream carbon emissions become more sustainable. 鈥淭his is a movement and it鈥檚 a must-have movement, because we are only as strong as our smallest supplier,鈥� said Lofty. The project aims to quantify supplier emissions to establish a baseline and identify key sources of emissions. This enables data-driven prioritization of intervention and road map creation.

ESG Reporting

Most people assume that ESG investing is designed to reward companies helping the planet. According to a by the Harvard Business Review, however, ESG ratings that underlie ESG fund selection are based on materiality, an accounting principle stating that all items likely to impact investors鈥� decision-making must be recorded in detail in a business鈥檚 financial statements using聽.

Some businesses are already linking materiality to their own fortunes and that of the planet. A revealed that a significant minority of respondents say sustainability is already financially material to their businesses and a larger group believes it will be imminent in the near future. Companies like Anheuser-Busch IN Bev and Schneider Electric are finding ways to make that link pay off with the help of data.

鈥淥ne change we鈥檝e seen over the last few years is that investors have a better understanding of which data is material to the business, and they ask more questions around it,鈥� said Barcenas. 鈥淲e鈥檙e increasingly trying to provide more context around our data.鈥�

Providing accurate data is the only way to really demonstrate the impact of the changing world on a company鈥檚 profits and losses. Having one global framework and mandatory reporting would certainly help address the data challenge, but that won鈥檛 happen in the near future.

鈥淲e still need to progress on some of the standards and regulations before we can make them mandatory,鈥� said Gunther Rothermel, senior vice president, head of Sustainability Engineering, 麻豆原创. 鈥淲e need to look at the common denominator underlying the regulations and cover that level first, and then grow this common denominator as the regulations mature and become accepted.鈥�

Companies like 麻豆原创, he said, with products that also need to meet standards, will, at least for now, have to serve numerous frameworks. In the meantime, 麻豆原创 solutions help organizations of all sizes and industries achieve their zero emissions, zero waste, and zero inequality goals through ESG data transparency across crucial business processes, business networking, and a large ecosystem of partners.鈥�

鈥淲e believe that embedding sustainability at the core of business strategy can help drive operational efficiency, innovation, employee engagement, supply chain resilience, risk mitigation, improved sales, and other strategic business benefits,鈥� said Rothermel.

Having the right data proof points will help companies better understand the return on their sustainability investment (ROSI) and the materiality underlying investor decision-making, resulting in shareholder returns and long-term benefits to the environment and society.

For more information on how 麻豆原创 helps companies record, report, and act on their sustainability goals, visit .

Digital transformation has changed the conversation about data; it is a shift from 鈥渄ata is not my problem鈥� to 鈥渄ata is everyone鈥檚 opportunity.鈥� Organizations are looking for ways to embrace the opportunity — specifically, by exploiting their data as a strategic enterprise asset.

By leveraging the right data quality solutions, organization can create the data excellence and discipline needed to drive better business outcomes, going beyond just fixing data to helping solve the data challenge. Data quality solutions from 麻豆原创 provide data profiling and monitoring, metadata management, data cataloging, data cleansing and enrichment, and information policy management capabilities. They helps improve collaboration among data workers, business users, and IT while equipping them to understand, analyze, and quantify the impact of data — and data quality — on enterprise processes, analytics, and governance initiatives. Solutions include , , , and .

Gartner evaluated 16 vendors and named 麻豆原创 a Leader based on its 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision.鈥� We believe this recognition serves as acknowledgment of our continued commitment to providing customers with world-class data quality solutions.

Data is the lifeline of business today. It is critical to not only manage data quality proactively to eliminate the risk to operations and analytics, but also look for opportunities to create organization-wide data excellence and discipline. The 麻豆原创 portfolio of data management solutions improves the quality of data across the enterprise, delivering trusted, relevant, and timely information to drive better business outcomes and help customers on their path to becoming intelligent enterprises.

Leading integrated business conglomerate set out to build a foundation for centralized data management across its business. The company is using 麻豆原创 Data Services and 麻豆原创 Information Steward software for regular data validation and enrichment in order to support a single source of truth based on high-quality data. This outcome gives employees the visibility and insights they need to make in-the-moment decisions confidently and supports better quality data with regular data validation, consistent data definition, and internal quality checks.

As part of聽, the helps customers to optimize analytics, achieve new insights, and improve business outcomes. Users can proactively govern data across the organization to help ensure trustworthy information for smarter decision-making.

Data quality solutions from 麻豆原创 help businesses discover, understand, and manage multifaceted data. Companies can profile, cleanse, enrich, and match customer, product, supplier, material, and other data — driving more accurate, trustworthy, and timely information.

Mike Keilen is global vice president for 麻豆原创 BTP Integration and Data Management Marketing and Solutions.

Today, data has become an engine of value creation. Organizations are forging new data strategies to derive meaningful insights and accelerate their innovation. Yet, many organizations struggle to derive value because their data is siloed across heterogeneous and distributed environments.

By leveraging the right data integration tools, organizations can easily discover, connect, integrate, govern, and orchestrate their data assets. 厂础笔鈥檚 data integration offerings deliver trusted, relevant, and timely information to drive better business outcomes for our customers. Our solutions include , , , , and integration capabilities of the . These offerings are part of (麻豆原创 BTP).

Gartner evaluated 18 vendors and named 麻豆原创 a Leader based on our 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision.鈥� We believe this recognition serves as acknowledgment of 厂础笔鈥檚 continued commitment to providing our customers with world-class data integration tools.

Turn Data Chaos into Data Value

Data integration is necessary for customers to gain intelligent, relevant, and contextual insights for better decision-making. However, without the right data management approach and technology, companies can face an uphill battle in integrating, processing, curating, governing, and augmenting their data.

厂础笔鈥檚 vision is a data fabric approach, which enables organizations to orchestrate highly distributed data, metadata, and processes while delivering data quality, security, and automation at speed.

, the data fabric layer of 麻豆原创 BTP, is a powerful solution that transforms distributed data sprawls into vital data insights. This technology combines data discovery, data preparation, data integration, data processing, and data connection across multiple endpoints and workflows.

麻豆原创 Data Intelligence Cloud helps customers:

• Integrate and orchestrate massive data volumes and streams at scale
• Streamline, operationalize, and govern innovation driven by machine learning
• Optimize governance and minimize compliance risk with comprehensive metadata management rules

Since the launch of 麻豆原创 Data Intelligence Cloud, we have seen tremendous growth of customers innovating with this technology. For example, Jesse Slocum, cloud engineer at , describes using 麻豆原创 Data Intelligence Cloud as 鈥渢he most robust data fabric solution that connects, manages, and analyzes large amounts of data unlike other tools.鈥� Comparatively, he goes on to say, other tools 鈥渙nly analyze small amounts of data, [and] fail to integrate with a wide range of cloud and on-premise applications.鈥�

Next Steps

For over 15 years, 厂础笔鈥檚 data integration tools have enabled customers to turn disjoined data assets into actionable business insights at scale. If you鈥檙e ready to unlock the full potential of your data, take the next step with the following resources:

• Visit the
• Get started at
• Read the 2022

JG Chirapurath is chief marketing and solutions officer for 麻豆原创 Business Technology Platform.

Gartner, Magic Quadrant for Data Integration Tools, Ehtisham Zaidi, Sharat Menon, Robert Thanaraj, Nina Showell, 17 August 2022
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 and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is .

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 厂础笔鈥檚 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.

It is well known that more diverse teams bring creativity and innovation, and diverse organizations are more likely to be profitable than their competitors. According to Gartner, diversity, equity, inclusion, and belonging (DEIB) has been ranked among the for HR Leaders in 2022.

But as we know, simply recognizing the importance and value of DEIB is not a solution 鈥� and making meaningful change is difficult. For strategic DEIB initiatives to succeed, organizations need data, and this is where many struggle. The data dilemma is two-fold: obtaining the right data about their people and being able to manage and interpret it properly. By rethinking when and how to ask for data, organizations can gain a clearer sense of who is in their workforce and how they can continuously improve their experiences surrounding DEIB.

DEIB data collection is a sensitive issue because employees may want to keep certain aspects of their identity private. The potential consequences of revealing one’s identity 鈥� particularly what may not be apparent to others, such as sexual orientation or religion 鈥� vary across time and place. Employees may face insensitive questions, microaggressions, outright prejudice, or even discrimination as a result. When employees anticipate these consequences, they feel less comfortable taking the risk of sharing their identity, and this lack of psychological safety leads to less self-reporting. The result is that leaders lack access to DEIB data to understand and improve the organization and, most importantly, the employee experiences of their people.

At 麻豆原创 SuccessFactors, we talked to globally on the scarcity of personal data and our findings show the issues are structural. Employees do not understand why some personal data is being collected or how it鈥檚 being used. To avoid bias and discrimination, they refuse to share this personal information.

So, what are the structural issues and how can they be addressed?

Using employee onboarding as an example, think about the data often requested on day one: name, date of birth, address, bank details, gender, marital status, along with potentially detailed identity data.

This is a lot of personal information to give an organization that an employee does not yet know or trust. Asking them only in the initial stages of joining an organization makes little sense and ignores the fact that identities can change over time. Instead, organizations need to earn the trust of employees and be strategic about when and how often they ask employees for social identity data.

Transparency Is Key: How to Help Employees Feel Comfortable with Sharing Their Identities

Organizations should think of addressing the various aspects 鈥� like demographics 鈥� of an individual’s identity, timing the reporting process, and, most importantly, ensuring trust among the individuals that their data will be used constructively and privately.

Transparency here is key. Employees need to know who will have visibility into their personal data, to what extent, and for what purposes. They also need to understand how technology systems will use the data, which requires organizations to be clear about their strategies and policies on managing bias.

Maybe organizations want to identify and support underrepresented groups or improve employee experiences in targeted areas. Specificity is also key. These noble intentions must come to fruition with clearly communicated programs and results tracking to gain the trust of employees and make them feel confident that their details are in safe hands. The more information employees are willing to self-disclose, the more organizations will be able to improve and individualize their experiences in return.

To recap, changing when and how organizations ask for personal data can result in greater self-reporting.

• Start with the less sensitive data you already have, like date of birth, place of birth, and current location.
• Gain employee trust by clearly communicating the benefits of self-disclosure and where and how their data will be used.
• Collect data on a regular basis, particularly after , to better understand changes in identity.
• Communicate to employees how this data has informed the development and execution of the DEIB strategy.

The journey to address DEIB within an organization cannot be completed overnight. Intentionally and intelligently collecting and using data can help employees feel comfortable bringing their whole selves to work. On the other hand, by knowing their people better, organizations can explore ways to foster .

Amy Wilson is SVP of Products and Design at 麻豆原创 SuccessFactors.

The Forrester report states: “麻豆原创 stands out on semantic data modeling, data catalog, governance and security, connectivity, discovery and classification, semantic data integration, data quality, data transformation and lineage, data events and transactions, data access and delivery, and deployment options. One customer reference called out that, ‘All in all, it鈥檚 easy to say that we could not have met our requirements without 麻豆原创 Data Intelligence.'” 厂础笔鈥檚 enterprise data fabric solution consists of capabilities from , including 麻豆原创 Data Intelligence Cloud, 麻豆原创 HANA Cloud, and 麻豆原创 Integration Suite.

“At this time of geopolitical and business volatility, businesses acknowledge that world-class that ensure trusted information to find the right path forward have never been more important,” said Marc Hartz, vice president of Product Management, 麻豆原创 HANA and Analytics, Data Management. “As a leader in data management solutions, 麻豆原创 continues to innovate and bring improved data fabric capabilities to help our customers manage complex data environments with confidence and agility. We believe this recognition from Forrester validates the comprehensiveness of our end-to-end data management solutions and how we鈥檙e enabling customers to better connect and extract value and insights from data.”

麻豆原创 believes agile businesses need to pivot quickly to respond to changes in global conditions. By establishing an enterprise data fabric strategy, organizations can adapt to change faster. One of the key elements of the data fabric solution is 麻豆原创 Data Intelligence Cloud.

麻豆原创 Data Intelligence Cloud is a comprehensive data management solution that connects, discovers, and enriches disjointed data assets into actionable business insights at enterprise scale. The latest update to the solution is centered around connecting and integrating distributed data assets, increasing data literacy across the organization, helping customers rely on trusted data, and operationalizing machine learning. 麻豆原创 Data Intelligence Cloud can extend integration, complex data orchestration, data pipelining, data catalog, and machine learning services with enhanced connectivity, governance, and pipeline modeling features that support complex and distributed environments. The latest release helps ensure data pipelines can leverage validation and quality rules, increased public APIs for metadata exchange, and increased integration capabilities required for a robust data fabric.

Learn more about聽. Download a copy of the “The Forrester Wave: Enterprise Data Fabric, Q2 2022” report .

Lisa Hopkins is senior director of Solution Marketing at 麻豆原创.

It鈥檚 an ambitious goal that requires all companies to account for and disclose their carbon emissions. In 2022, the question is no longer if a company needs to do something; it鈥檚 how they can get started. Their role has drastically changed from observer to contributor.

Carbon accounting solutions that help companies measure how much carbon dioxide they emit are already available. But there鈥檚 another problem that currently isn鈥檛 addressed, and it鈥檚 much harder to solve: how can companies even obtain the data on their direct and indirect carbon emissions?

Referred to as聽, a company鈥檚 carbon footprint is complex. To measure it, companies currently turn to publicly available catalogs such as聽聽or the聽. These databases list certain types of materials and activities and match them against an average amount of carbon emissions being emitted.

鈥淲hile these catalogs provide an initial estimate of a company鈥檚 carbon footprint, they don鈥檛 reflect the individual status quo accurately,鈥� said Marcus Krug, head of 麻豆原创 Innovation Center Potsdam. 鈥淎s regulatory requirements across different regions are increasing, so is the need for companies to have accurate and verifiable numbers on their carbon footprint in their financial statements.鈥� In addition, many companies are evaluating new business models based on accurate and trustworthy sustainability data.

With big brands like聽听补苍诲听聽going green and integrating sustainable practices in their operations, reliable and verifiable numbers to back up these claims are essential to avoid a reputational and financial crisis. Solving this issue requires a standardized approach to calculate emissions from a variety of systems from different vendors and share them through the entire supply chain 鈥� from suppliers via shippers and manufacturers to retailers. It doesn鈥檛 stop at a company鈥檚 own border.

鈥淐ollaboration and data sharing are the orders of the day for companies when it comes to measuring and managing their carbon footprint,鈥� said Gunther Rothermel, senior vice president and head of 麻豆原创 S/4HANA Sustainability at 麻豆原创.

He and his team identify opportunities to expand the 麻豆原创 product portfolio to include new focus areas such as climate action, circular economy, or holistic steering and reporting.

鈥淎chieving sustainable business practices means embedding sustainable practices across processes, end-to-end,鈥� said Rothermel.

Solve Problems Collaboratively

Working with industry alliances like the聽聽(WBCSD) and聽聽as well as other software vendors,听聽is developing an interoperable carbon data network to allow customers to share their carbon emission data while preserving data sovereignty and preventing any vendor lock-in. Based on self-sovereign identity (SSI), this data foundation aims to help calculate a company鈥檚 carbon emissions so it can reduce or offset them.

鈥淯sing open standards was essential to get different vendors behind this project and excited to participate,鈥� said Krug. 鈥淛udging from the positive customer feedback so far, this open, interoperable, and decentralized network seems to fill an important gap. No one really wants to build costly, non-standardized, point-to-point integrations across the entire supply chain.鈥�

For companies, measuring their indirect Scope 3 emissions 鈥� the greenhouse gases emitted along their supply chains and in the use of their products 鈥� is particularly challenging.

鈥淲e know from our customers that managing Scope 3 carbon emissions and having impact at scale is a major challenge for them,鈥� said Jesper Schleimann, chief strategy and innovation officer for the EMEA North region at 麻豆原创. 鈥淭heir openness in sharing details and requirements have been crucial in designing an open solution with positive benefits for all stakeholders across the value chain and ensuring a successful adoption across the globe.鈥�

Building on the foundation for collaboration laid by聽, the carbon data network can provide value by tracking a product鈥檚 footprint from sourcing to the end consumer, for instance. With many different parties involved across the globe, the supply chain is usually complex and opaque.

For example, a fashion retailer sources garments from a textile manufacturer in India, which are shipped to Europe by a shipping company. The end consumer would like to know the overall carbon footprint of the garment they buy. Calculating this footprint depends on multiple factors, including the Scope 1, 2, and 3 emissions of the textile manufacturer, the shipping-by-ocean freight, the transport to the retail store, and potentially other intermediary parties.

In this difficult undertaking, the carbon data network can provide the needed transparency across all participants of the network.

Prioritize Access Over Ownership

For the past decades, proprietary solutions have shaped the enterprise software space. But as the world faces one of the biggest challenges, many companies have come to realize that certain issues can only be solved together. To be prepared for the future, a new layer of cross-company business collaboration is needed.

Decentralized approaches such as the carbon data network are open by nature and provide the technical foundation needed to share data across company borders and allow collaboration, for instance in supply chain or sustainable financing. It could also be used to improve the distribution, demand, and supply of water resources within an ecosystem.

鈥淲e are steering the market towards a more sustainable future, and we鈥檙e doing it collaboratively,鈥� said Krug. 鈥淭he decentralized network approach reflects the natural evolution of our business networks.鈥�

Corinna Schmidt is part of NVT Marketing & Communications at 麻豆原创.
.

厂础笔鈥檚 and solutions 鈥� as part of 鈥� enable our customers to give data purpose, connect and automate business processes, and ultimately accelerate innovation.

This is exactly what online reviewers had to say about our solutions. Megan Headley, VP of Research at TrustRadius, stated, “麻豆原创 Data Intelligence and 麻豆原创 Master Data Governance earned the Top-Rated awards as a direct result of user feedback. Reviewers value the flexibility of many data sources, modular architecture, and high-quality support team of 麻豆原创 Data Intelligence. And reviewers of 麻豆原创 Master Data Governance love the application’s bulk data loading features, workflow automation tools, and auditing capabilities.” Additionally, one reviewer, an engineer at a hospital and healthcare company of 5,001 to 10,000 employees, said, 鈥淏y implementing 麻豆原创 Integration Suite, we accelerated the overall process in the development cycle.”

We view this recognition as a testament to our customer-focused technology approach and validation that our solution strategy for聽,听, and will continue to deliver the next generation of world-class data management and integration capabilities for our customers.

helps pull together master data and manage it centrally. can transform distributed data sprawls into vital data insights. integrates applications and processes with pre-built content managed by 麻豆原创.

TrustRadius鈥� Top-Rated awards are the industry standard for unbiased recognition of the best technology products, helping to drive deep collaboration between technology providers, customers, and partners. We appreciate our passionate data and integration customers and their continuous feedback.

For more information on the awards, read the reviews:

Mike Keilen is global VP of Data Management and Integration at 麻豆原创.

Unfortunately, consequences can run deep when executives place insufficient importance on the value of data at strategic and operational levels. Organizations often become too stagnant to evolve with market dynamics and changing business needs to effectively challenge competitors and gain considerable market share.

I have experienced how the long-term success of a company begins with an executive-level commitment to become a data-driven business. By unifying every area of the enterprise with this foundational goal, organizations can collaboratively develop an outcome-driven data strategy that breaks down the enterprise strategy into measurable data key performance indicators (KPIs).

Setting the Foundation for a Data Culture

For many 麻豆原创 customers, 聽is a critical part of their transformation into a truly data-driven business. The opportunity to foster innovation, nurture ideas, and build a resilient infrastructure with supporting processes enables organizations to understand the value of data and apply it to resolve business challenges with less risk and cost.

One of the first steps that our advisory experts undertake is to help our customers establish the essential cornerstone of a data-driven business. They outline a framework of critical positions 鈥� which we call a 鈥渉ouse of roles鈥� 鈥� needed to support the data transformation of each organization.

Each role in the framework has a unique set of responsibilities to help ensure control over the data landscape in terms of quality, consistency, relevance, processing performance, regulatory compliance, security, and authorized access:

• The data owner (usually a level-one manager) is accountable for a specific subset of data and defines management goals.
• The head of master data management (MDM) or chief data officer oversees data objects within scope, defines objectives for data quality and specifications, and monitors respective service-level agreements and KPIs.
• The data steward defines governance rules and validates maintenance requests for specific data objects to help ensure business intelligence remains high in quality and integrity.
• The data architect designs master data processes and logistics for dependent systems and provides technical support, such as data-quality rules and analysis.
• The data requester (any employee) requests new data or changes in existing data.
• The data agent creates and maintains master data in consultation with a data requester.

When setting up the framework, conflicts may occur within it. For example, the head of MDM may want data agents to be responsible for maintaining a specific set of data, while business organizations may disagree.

麻豆原创 Advisory Services helps defuse such controversies by leading workshops that allow our customers to transparently define roles with the involvement of all relevant stakeholders. This exercise includes the appointment of employees to each position and a data domain for which they will manage communications and governance requirements.

Cultivating Pivotal Change

Data-driven businesses begin with a clear decision-making process that transforms the company into a culture that values data accountability and governance. Through the 鈥渉ouse of rules鈥� framework, 麻豆原创 Advisory Services can bring customers one giant leap closer to realizing this vision.

What does this mean for 麻豆原创 customers? A world of opportunity. In addition to having a complete foundation for correct, fact-based decision-making, they can open up new revenue streams through聽data monetization and uncover insights already existing in their business applications.

Jan Hoffmann is a business processes principal consultant at 麻豆原创.

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.

solutions from 麻豆原创 power 麻豆原创 Business Technology Platform (麻豆原创 BTP), delivering solutions that drive a data strategy and maximize the value of data. Combined with data management, 麻豆原创 BTP brings together database, analytics, integration, and extension capabilities with intelligent enterprise applications into one platform for both cloud and hybrid environments.

By making data management a priority, customers can take advantage of the volume and variety of data, successfully driving business processes and innovations. A data management approach helps your company drive success in the future.

We are honored that customers value our data passion and recently expressed their appreciation through , earning 麻豆原创 the Top Rated award in both the and the .

“Buyers have many options when it comes to selecting a master data governance solution,” said Megan Headley, vice president of Research at TrustRadius. “麻豆原创 Master Data Governance earned a Top Rated award based entirely on feedback from its customers. Reviewers on TrustRadius highlight the product’s high performance, ease of data management, and flexibility of integrations.”

鈥溌槎乖� Data Intelligence has earned a Data Fabric Top Rated award based directly on feedback from its customers,鈥� Headley continued. 鈥淩eviewers on TrustRadius value 麻豆原创 Data Intelligence features for transforming data, as well as its ability to accept data from a wide variety of sources.鈥�

This acknowledgement is a great honor for multiple reasons. Not only are the Trust Radius Top Rated awards the industry standard for unbiased recognition of the best technology products; more importantly, they are the direct result of our customer engagement. We view this recognition as a testament to our customer-focused data management approach, validating our solution strategy and vision for and to deliver next-generation data management capabilities for our customers.

TrustRadius helps drive collaboration with our customers and partners by continuously capturing and acting on customer input to drive relevant improvements. Listening to our data-passionate customers and focusing on active listening combined with effective feedback loops to drive solution improvements enables 麻豆原创 to better serve customer challenges and continuously deliver innovative industry solutions.

Read the reviews on for both and .

Andreas Wesselmann is senior vice president of 麻豆原创 HANA and Analytics, Data Management at 麻豆原创.

Moving to the cloud can be a cathartic experience for companies. Physical control of on-premise data centers, networks, and machines give way to a landscape of virtual systems and processes running in an environment that no one can touch or see. And while running operations in the cloud reduces costs and drives reliable business continuity, it can also bring unprecedented complexity when data is scattered and siloed.

The struggle to integrate data often cascades across the entire business, contradicting the cloud鈥檚 promises of flexibility, agility, and speed. Yet, 麻豆原创 partners 鈥� from software and service providers to system integrators and value-added resellers 鈥� are helping their customers break through this gridlock with a new cloud-based approach to data warehousing.

Rethinking the Relationship Between Integrated Data and Enterprise Applications

While the seemingly endless potential of the cloud is empowering, most companies are overwhelmed by the challenge of redefining their data management processes for software-as-a-service (SaaS) applications, cloud databases, and the cloud infrastructure. All too often, micro-silos of data are growing at such an exponential scale that users cannot get the complete view and insights they need to drive the bottom line.

It鈥檚 no secret that 30% to 80% of our customers鈥� data reside on 麻豆原创 solutions. But when a business鈥檚 intelligence is spread across a virtual landscape of on-premise applications, databases in the cloud and other sources such as spreadsheets, businesses cannot gain the speed, cost efficiency, operational flexibility, and innovation necessary to stay competitive.

So, how can companies centralize data from their enterprise application systems with micro-silos and scattered data locations across the cloud and get the right information to the right user?

A common misperception is the role of modern enterprise application systems when managing core data and delivering data intelligence. They鈥檝e historically served as a system of record in which core business processes operate. But as expands its reach across the enterprise, an array of transaction systems appears, resulting in hundreds and thousands of islands where data now resides. And so, businesses require an end-to-end data management solution that maintains security and trust and delivers contextual logic giving one view of the enterprise, combining all its critical data sources, in the cloud.

Remodeling Data Warehousing for a Cloud-Based World

By rethinking the importance of data warehousing during a move to the cloud, businesses can discover new ways to enhance existing data with related content, models, and analytics 鈥� and manage that intelligence to address unique needs. The advantages of remodeling data warehousing are especially critical when data is constantly changing and business needs are increasingly unique.

The solution, a component of (麻豆原创 BTP), automatically obtains and presents the latest and greatest data available 鈥� physically moving terabytes of information back and forth in the background. The solution is based on in-memory computing technology and comes with prebuilt models and templates to help simplify the user experience when setting up data analytics and share insights with greater ease. It establishes a virtual and federated approach to data management and enables users to load information into a data mart.

The business layer in 麻豆原创 Data Warehouse Cloud enables organizations to centrally define business semantics to hide any complexity in the underlying experience from their users. The layer quickly consolidates 麻豆原创 and third-party data sources on premise and in the cloud and establishes a single source of truth by defining and locating dimension definitions, measures, key performance indicators, and authorizations. Users can also quickly deliver stable and extensible semantic business models by creating complex queries based on 麻豆原创 and third-party data sets without replication.

By modeling in the data warehouse, without the requirement of migrating data first, partners can quickly help customers start using their data in a federated manner. Furthermore, they can leverage the prepopulated building blocks to rapidly innovate custom cloud capabilities to help deliver the outcomes that customers expect and business value that keeps them loyal.

Evolving Data Experiences Continuously with Ease and Speed

Suppose a utility business wants to standardize its analytics and gain new efficiencies with process automation and the use of a cloud-based data warehouse with a predefined model for metering analytics. By implementing 麻豆原创 Data Warehouse Cloud, the utility gains a solution that can help find related information, pull it into the data warehouse, and make that model available immediately to, for example, build data visualizations.

Another remarkable aspect of this approach is that 麻豆原创 partners are not starting from scratch to deliver these capabilities. In this case, smart meter data stored in 麻豆原创 for Utilities solutions at 15- and 30-minute intervals can quickly grow and become challenging to store cost-effectively. However, housing meter data in a within 麻豆原创 Data Warehouse Cloud can help the utility handle data volume growth and keep costs down.

To comprehensively analyze and report smart meter data, the utility business can leverage 麻豆原创 Data Warehouse Cloud and 麻豆原创 Analytics Cloud. With all data centralized in 麻豆原创 Data Warehouse, reporting can be extended to enable enterprise-wide detailed assessments.

Additionally, meter-to-cash scenarios can be set up quickly with the assistance of prebuilt . The content leverages service API extractors and core data services views, along with dashboards from 麻豆原创 Analytics Cloud and predefined models 鈥� enabling a utility company to accelerate time to value.

麻豆原创 Data Warehouse Cloud also integrates with the current landscape to help create one central data layer. Connections are available for all sources, including 麻豆原创 S/4HANA, the 麻豆原创 BW/4HANA solution, and the 麻豆原创 Business Warehouse application, as well as third-party sources and flat files. The solution can replicate and virtualize data from different sources, working to create one source of truth with complex data models that span multiple data sources.

Designing a Cloud Environment with the Customer in Mind

If there was ever a time for partners to play a key role in how people work, it鈥檚 now. From connecting various remote data sources to creating specialized analysis, they can empower organizations and their users to work better together by leveraging data across today鈥檚 complex virtual and physical workspaces.

Finding that critical path to customer success in the cloud has never been easier and faster. With a cloud-based data warehouse solution, such as 麻豆原创 Data Warehouse Cloud, and technology platforms like 麻豆原创 BTP, businesses can benefit from partners unifying data models and connections in one secured and governed place. And in return, they can make reliable decisions with confidence, producing the kind of outcomes that keep their brand moving forward for years to come.

Learn more about and , and if you鈥檙e a partner or interested in partnership opportunities with 麻豆原创, check out 麻豆原创 PartnerEdge 鈥� Build at . Or, read part one and part two in the CTO series to learn more about how partners are enabling customer success with a unified technology platform.

Jagdish Sahasrabudhe is CTO of the Global Partner Organization at 麻豆原创.

As B2B and B2C customers continue to shift more of their commerce transactions toward digital channels and engage in product-based digital services, the volume of master data is set to explode. predicts that the 鈥渁mount of digital data created over the next five years will be greater than twice the amount of data created since the advent of digital storage.鈥�

This growing trend is not only an opportunity, but also a challenge to how master data is managed. While considered a preparatory step for transitioning to the latest technologies, such as , MDM can also lay the foundation for future application development and business innovation.

Harmonizing Data to Drive Meaningful Transformation

While the pressure to innovate groundbreaking, sustainable value for customers and the business increases, many 麻豆原创 customers are solving unique challenges quickly with less cost and risk. The key to their success is聽, enabling a methodical, forward-thinking MDM approach to fostering innovation, nurturing new ideas, and building strong solutions.

By enhancing the quality of master data with the assistance of 麻豆原创 Advisory Services, our customers are overcoming significant challenges that many companies face in their MDM practices, including the following.

1. Turning a Lack of Commitment into a Shared Vision

Executive sponsors do not always connect how the benefits of an IT strategy can advance the overall business strategy, especially quick wins in MDM projects. Unfortunately, this level of detachment among decision-makers undermines the efforts of any solution implementation.

Consider an organization that purchased a solution license without setting aside the budget to support activities such as creating a master data team, staffing new roles, and setting up governance procedures. By not addressing errors made along the way and reconsidering the need for better MDM support, stakeholders likely feel frustrated once the project goes live because business needs were not met as expected. Worse yet, gaining the executive confidence and commitment needed for future projects become increasingly tricky as stakeholders feel their input will not make a difference in the outcome.

麻豆原创 Advisory Services help alleviate the situation by framing and solving various business and IT challenges and relaying how improved MDM processes can help. The organization can start its journey toward solution implementation by cultivating the business鈥檚 collective genius in an unconventional and creative atmosphere. This is accomplished with pragmatic design thinking workshops, pilots, prototypes, road maps, digital working models, and organizational expertise and enablement.

2. Strengthening Communication Between IT and the Business

IT departments typically lead MDM projects. However, users may still refuse to participate in the early discussions because they cannot see how the effort can benefit their business function. Over time, this lack of awareness turns into a lack of desire to fulfill MDM responsibilities, leaving behind any chance of leveraging data as a way to expand the company鈥檚 capabilities and help fuel revenue growth.

To overcome this bidirectional misunderstanding, 麻豆原创 Advisory Services help ensure that IT pays attention to the immediate needs of the business users and establishes MDM processes that are efficient and simple to maintain. Furthermore, the convenient delivery of training and timely knowledge allows closer collaboration between IT and the business and a better understanding of how the MDM project impacts the specific organization and overall business.

3. Establishing Governance and Common Data Definitions

When MDM tools and best practices are not implemented globally, individual organizations often feel compelled to act locally on their terms 鈥� limiting the visibility and consistency to make decisions at the corporate level. Meanwhile, users working with the same data sets have little idea of how they are being processed in other departments or whether decisions are based on the same understanding of what the data means.

Companies that rely on 麻豆原创 Advisory Services can employ universal governance of their master data processes at any point of their MDM project. Setting up a change management team and conducting an initial assessment early on improves organizational understanding of the level and magnitude of change needed to ensure MDM capabilities support the digital investment or transformation initiative. Plus, every user can access the proven knowledge, tools, and templates required to adapt and comply with data standards.

4. Speeding Business Optimization and Innovation

Although complex in theory, MDM is emerging as a critical part of digital readiness as companies recognize its long-term value and involve the right people to establish the right best practices. Even a standard approach to MDM can drive innovation when the right data strategy is in place and IT objectives are aligned with business strategies.

However, with 麻豆原创 Advisory Services, businesses can gain a more profound edge by using MDM to open the door to more accurate and consistent analytics tools. Data sets become more predictive and multidimensional by combining master data with , , graphical visualization, and other intelligent technologies. Different views on similar domains support the demands of various business groups on context-dependent insights.

Realizing the Full Potential of MDM Advancements

From the viewpoint of the business, MDM is valuable when cost reduction and closer cross-departmental collaboration are achieved. IT organizations can deliver on those expectations by implementing solutions successfully on the first attempt, harmonizing the way technologies and people work, and avoiding any misunderstandings along the way.

麻豆原创 Advisory Services enable IT and non-IT organizations to maximize the potential of their digital transformation by creating a master data foundation that drives greater visibility, agility, and focus. The service portfolio establishes emerging technologies and draws on the latest innovations, industry experts, and ecosystem of innovators from 麻豆原创. And for the business, this means an opportunity to further optimize operations and initiate change 鈥� faster and with less risk.

Stay in the conversation by following the 麻豆原创 Services and Support offerings on , , , and .

Gelena Artemenko is a business enterprise consultant for CPG & Retail Industries at 麻豆原创.

From Data to Value

Every business knows that data drives success. They鈥檙e accustomed to measuring key performance indicators (KPIs), reviewing quantitative trends, and using data to inform decision-making.

There鈥檚 no disputing the importance of facts and figures, but not everyone realizes the true potential of data. Businesses especially need to recognize not only what data they have, but how to create value with it.

We鈥檝e learned that聽having聽data isn鈥檛 enough. Businesses need to assess what data is and what it means to them before they can use it. That means seeing data not as a by-product of business operations, but as a driver of value propositions.

麻豆原创 Data and Analytics Virtual Forum

We know that the challenges of today aren鈥檛 the same as the challenges of tomorrow. What鈥檚 important is being ready for any situation, being agile, and being able to provide your business with the necessary insights.

The is designed to help your organization understand the full value of your data. We will show you how to with our unified data and analytics strategy. Discover how to manage data through its entire lifecycle. From initial storage to real-time analytics, you鈥檒l be able to quickly harness the power of information.

Learn from Data and Analytics Leaders

During the event, thought leaders, business professionals, and industry experts from data and analytics fields will discuss how to power data and analytics to help you drive stronger insights, intelligence, and impact for your organization.

Join Irfan Khan, president of Database and Analytics at 麻豆原创, and his guests to:

• Learn how 厂础笔鈥檚 data and analytics portfolio helps you get a consolidated view across your data 鈥� regardless of where it sits 鈥� and make real-time decisions.
• Hear about the experiences of 麻豆原创 customers, including , Max Planck Institute, and Quadpack.
• Dive deep into selected data and analytics cloud solutions from 麻豆原创.
• Explore how the new RISE with 麻豆原创 offering can accelerate your cloud journey.

Learn from Use Case Scenarios

In addition, the event offers the option to explore specific use case scenarios in a choice of breakout sessions:

Proactive 麻豆原创聽S/4HANA Decision-Making with Data and Analytics
Finding聽and implementing a proactive financial strategy to meet聽today鈥檚聽on-the-fly reporting demands isn鈥檛 easy, but it is possible with the right technology. Discover how complementing your 麻豆原创 S/4HANA investment with 麻豆原创 data and analytics cloud solutions can support your finance and planning goals. 鈥�

Building a Hybrid Data Strategy with 麻豆原创
Data is scaling in size and becoming more complicated. At the same time, organizations depend on IT to unlock the full value of this data. As organizations look to chart their journey to the cloud,听a hybrid data strategy offers the best of the both worlds 鈥� leveraging on-premise investments and gaining new cloud capabilities. Learn how you can maximize the impact of a聽hybrid data strategy.听Geberit, a European leader in sanitary products, will share how it successfully streamlined its data landscape through cloud solutions from 麻豆原创.听鈥�

麻豆原创 HANA Cloud 鈥� Brand New Tools Making the Impossible Possible
With the introduction of several new services in 麻豆原创聽HANA Cloud already in 2021, the capability to deliver on new, and sometimes previously impossible, use cases is now a聽reality. Hear all about the capabilities of the new cloud services for 麻豆原创 Adaptive Server Enterprise, 麻豆原创 IQ, 麻豆原创 Replication Server, and more. You鈥檒l hear directly from聽users聽of the new聽services聽and explore opportunities for your organization to聽gain more value from your data.听鈥�

and reserve your place today. If you cannot make the virtual event on May 11, you will receive the replay in your inbox.

The report recognized 麻豆原创 as a leading provider based on its 鈥渁bility to execute鈥� and 鈥渃ompleteness of vision,鈥� after evaluating 厂础笔鈥檚 metadata management solutions, including , software and , which are all part of .

According to Gartner: 鈥淩equirements and market demand have expanded for metadata management solutions to address a new population of users leveraging a variety of data and analytics initiatives. This research will help data and analytics leaders find the most suitable vendor and solution for their organizational needs.鈥�

鈥淢etadata is the backbone of every critical business-oriented and technical project in a company,鈥� said Andreas Wesselmann, senior vice president, 麻豆原创 HANA & Analytics, Data Management at 麻豆原创. 鈥淥ur metadata management solutions are crucial to building a trusted data foundation to run intelligent operations and analytics to drive better business outcomes for our customers. We believe that this latest recognition from Gartner shows that 麻豆原创 understands the importance of enterprise metadata management for the intelligent enterprise.鈥�

support capabilities to understand, integrate, cleanse, manage, associate and archive data to optimize business processes and analytical insights.

Access a

Visit the . Follow 麻豆原创 on Twitter at .

Media Contact:
Julia Fargel, +1 (650) 276-8964, julia.fargel@sap.com, PT
麻豆原创 麻豆原创 Room; press@sap.com

*Published November 11, 2020, by Analysts Guido De Simoni, Mark Beyer, Ankush Jain, Alan Dayley.
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 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.

Any statements contained in this document that are not historical facts are forward-looking statements as defined in the U.S. Private Securities Litigation Reform Act of 1995. Words such as 鈥渁nticipate,鈥� 鈥渂elieve,鈥� 鈥渆stimate,鈥� 鈥渆xpect,鈥� 鈥渇orecast,鈥� 鈥渋ntend,鈥� 鈥渕ay,鈥� 鈥減lan,鈥� 鈥減roject,鈥� 鈥減redict,鈥� 鈥渟hould鈥� and 鈥渨ill鈥� and similar expressions as they relate to 麻豆原创 are intended to identify such forward-looking statements. 麻豆原创 undertakes no obligation to publicly update or revise any forward-looking statements. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. The factors that could affect 麻豆原创’s future financial results are discussed more fully in 麻豆原创’s filings with the U.S. Securities and Exchange Commission (“SEC”), including 麻豆原创’s most recent Annual Report on Form 20-F filed with the SEC. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates.
漏 2020 麻豆原创 SE. All rights reserved.
麻豆原创 and other 麻豆原创 products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of 麻豆原创 SE in Germany and other countries. Please see for additional trademark information and notices.

Organizations are looking for more flexible solutions to manage their data assets and cloud solutions are, more often than not, part of the equation for new data management investments. However, for 麻豆原创 customers, it is about more than just where the data resides. It is first and foremost about how to derive business value from that data.

We are proud to share that Gartner has recognized 麻豆原创 as a Leader in the 2020 Magic Quadrant for Cloud Database Management Systems (DBMS) report. This is the first Gartner report to cover both operational and analytical database management requirements in the cloud. 麻豆原创 [HANA Cloud] was ranked second highest across all four of Gartner鈥檚 Use Cases for Critical Capabilities for Cloud Database Management Systems for Operational Use Cases: Traditional Transactions, Augmented Transactions, Stream/Event Processing, and Operational Intelligence.*

In our opinion, the Gartner report evaluates completeness of vision and ability to execute, where the cloud DBMS market is defined as a fully provider-managed public or private cloud software system that manages data in cloud storage. These management systems include specific optimization strategies designed for supporting traditional transactions and/or analytical processing covering one or more of the following seven use cases: Traditional Transactions, Augmented Transaction Processing, Data Warehouse, Logical Data Warehouse, Data Science Exploration/Deep Learning, Operational Intelligence, and Stream/Event Processing.

Devising a Data Management Strategy that Works for Businesses

Gone are the days when business functions could operate in silos and decision-makers could wait for days for the next business report. Customers need real-time updates across their operations to help them to respond to changing customer behaviors and disruption in their supply chains.

Ten years ago, we introduced , developed based on the bold new vision that our customers should be able to run analytics on live transactions. Answers should be instantly available and always up to date without the need to export data and run parallel systems to manage transactional workloads and operational reporting.

麻豆原创 has continued to build on that vision to account for the significant increase in data volume and variety and the proliferation of hybrid deployments. Making the transition to the cloud is at the forefront of our customers鈥� minds.

Gartner states that 鈥淏y 2022, 75% of all databases will be deployed or migrated to a cloud platform, with only 5% ever considered for repatriation to on-premises.鈥�** Moving to the cloud can help companies easily and cost-effectively scale to meet their needs.

However, the path to the cloud for many organizations is less clear. Some customers want to go to the cloud right away. Some still want or need to say on premise, and some are beginning to extend their on-premise solutions with hybrid scenarios.

We want to enable customers to move to the cloud at their own pace. The result of our focus on these trends and supporting our customers is an ecosystem of cloud-native offerings centered on , which provides a single gateway to all data, no matter where that data is stored. 麻豆原创 HANA and 麻豆原创 HANA Cloud are at the center of our intelligent enterprise vision and the foundation of (麻豆原创 BTP). Additionally, we have been working with our cloud line-of-business applications to support them in their , and the majority of them have completed their migration projects.

By positioning 麻豆原创 in the Leaders quadrant of the Magic Quadrant for Cloud DBMS report, we believe it highlights not only our track record, but also the steady adoption of 麻豆原创 HANA, the breadth of functionalities, cloud database presence, and infrastructure choices, which are all essential aspects of our goal of guiding customers on their journey to becoming intelligent enterprises.

Embracing Data Management in the Cloud to Achieve Business Outcomes

The breadth of functionality is essential to account for today鈥檚 complex data landscapes and the pivotal role that data has in every activity a company undertakes. Users may need to capture transactions, apply machine learning to incoming data streams, analyze diverse, distributed data in context, predict outcomes, and provide instant responses to users across various devices. 麻豆原创 has this covered.

To address our customers鈥� top data management priorities, we have complemented 麻豆原创 HANA and 麻豆原创 HANA Cloud with other solutions in 麻豆原创 BTP. For example, we know that shortening time to insight is essential for our customers, but this cannot be achieved at the expense of establishing trust in the data or complying with data privacy regulations. This is why our solutions are designed to empower business users within an IT-governed environment. is the innovative solution designed based on this vision.

厂础笔鈥檚 cloud database presence and infrastructure are essential to helping our customers make the journey to the cloud at their own pace, as well as allowing them to benefit from the unique capabilities of 麻豆原创 HANA without being locked-in to a specific vendor with multi-cloud, hybrid, and various on-premise deployment options, including appliance, hyperconverged systems, virtual machines, and bare-metal installations from a large variety of vendors.

For more detailed information, read the .

Bar茅 Said is head of Database for 麻豆原创 HANA and Analytics at 麻豆原创.

* 24 November 2020 by Merv Adrian et al, Gartner.
**Gartner The Future of the DBMS Market is Cloud, June 2019, Donald Feinberg, Merv Adrian, Adam Ronthal
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 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.