and the are showcasing how modernisation programmes built on 麻豆原创 technologies are helping organisations move beyond fragmented systems and legacy processes toward more unified, scalable and intelligent operating models.

At this year鈥檚 flagship 麻豆原创 麻豆原创PHIRE event held in Madrid between 19 and 21 May, both organisations shared insights into their modernisation efforts and the impact of initiatives such as RISE with 麻豆原创 to fast-track digital transformation and unlock business outcomes.

, Managing Director for Southern Africa at 麻豆原创, says: 鈥淢odernisation is no longer only about replacing legacy systems. It is about building the digital foundations that allow organisations to simplify complexity, improve efficiency and unlock new value from cloud, data and AI. Whether in the public sector or global industry, 麻豆原创 is helping customers create more agile, intelligent and future-ready organisations.鈥�

City of Madrid advances digital public administration

The Madrid City Council is collaborating with 麻豆原创 Spain on the comprehensive modernisation of its internal management through 麻豆原创 software. The objective is to digitalise procedures, improve efficiency and deliver better services to municipal employees and citizens in finance, revenue management and human resources.

The City Council has worked with 麻豆原创 software for two decades, beginning in 2004 with solutions in finance and HR. In 2020, it launched its public administration modernisation project with the migration to the private cloud. This process is now advancing with the adoption of and .

The challenge was to move beyond traditional models based on fragmented systems, paper-based procedures and isolated developments. In public administration, this fragmentation can slow processes, duplicate data, limit visibility and make it harder to manage revenues, budgets and human resources in an integrated way.

The solution has been to consolidate a new public management model based on unified management, real-time information and digitalised processes. RISE with 麻豆原创 provides the foundation for the move to the private cloud, while 麻豆原创 Business Technology Platform provides the platform for integration, extension and application development.

The transformation has had a significant impact in the tax domain, where 麻豆原创 tax and revenue management solutions are being integrated into the city鈥檚 financial platform. This enables municipal revenues to be managed as a natural extension of the financial system, supporting an end-to-end view of the full cycle from taxpayer registration and assessment to collection and inspection.

Currently, two-thirds of the City Council鈥檚 tax revenues are already managed within this environment, including Property Tax, the Urban Waste Tax for Business Activities, Capital Gains Tax and the Terrace Tax. The next step will be to incorporate the Motor Vehicle Tax and the Economic Activities Tax.

The project has also focused on data quality. During the first year, the City Council carried out a cleansing and harmonisation of master data from previous management systems, generating taxpayer 鈥淕olden Records鈥� and enabling an efficiency rate of 98.02% for Property Tax in 2024.

, IT Manager of Madrid City Council, says: 鈥淭his project marks a paradigm shift: we are moving from managing paper files and isolated systems to managing information and processes in an integrated and intelligent way, with a 360-degree view.鈥�

The impact is being felt across internal management and citizen services. The project supports end-to-end process digitalisation and a 鈥減aperless鈥� administration model, while automation, AI capabilities and robotic process automation are helping reduce manual workloads, minimise errors and improve decision-making through real-time analytics.

Prysmian builds an AI-ready global platform

Prysmian, a global leader in cable solutions for energy and telecommunications, is demonstrating how modernisation can create the foundation for broader business transformation.

The challenge for Prysmian was to strengthen its digital core as it evolved from a cable manufacturer to a global provider of solutions supporting the energy transition and digital transformation. With 鈧�20 billion in revenue, 34 000 employees across more than 50 countries, 109 manufacturing plants and 30 R&D centres, the company needed a unified, resilient and AI-ready platform to support its next phase of business evolution.

Prysmian completed the evolution of its digital infrastructure through RISE with 麻豆原创 in just four months, creating a unified, resilient and AI-ready cloud platform. Through the integration of , , and 麻豆原创 Business Technology Platform, the company built an intelligent platform designed to improve operational efficiency, accelerate decision-making and enhance predictive capabilities.

, Group CIO and Digital Officer at Prysmian, says: 鈥淩ISE with 麻豆原创 provided us with a global ERP foundation, 麻豆原创 BTP connected engineering and business, while embedded AI transformed the way our employees interact with data, redefining how Prysmian operates at scale.鈥�

The impact has been significant. Prysmian has achieved 70% automation of repetitive activities through embedded AI, an 80% reduction in the implementation time of new innovative solutions, and a 50% acceleration in time-to-market for new products.

The company has also introduced concrete AI use cases across business processes, including intelligent customer order automation, automated payment reconciliation and smart expense management. At the same time, Prysmian is using 麻豆原创 BTP to build an advanced cable design platform connecting engineering and business functions, standardising rules, processes and bills of materials to accelerate product development and increase competitiveness.

Pillay adds: 鈥淭he City of Madrid and Prysmian show how modernisation creates measurable value when it is connected to clear organisational priorities. By integrating processes, improving data quality and building intelligent cloud platforms, organisations can improve how they operate today while preparing for the next wave of innovation.鈥�

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The comments were made by Sunil Geness, director of global government affairs and CSR at 麻豆原创 Africa, and Sergio Maccotta, senior VP and GM for 麻豆原创 Middle East and Africa 鈥� South.

Geness and Maccotta said businesses that can sense change, make decisions and act with minimal human intervention are reshaping how companies operate and compete. According to 麻豆原创, autonomous operations 鈥� where nearly half of all business processes run independently and most operational work is听automated听or AI-augmented 鈥� are being deployed across finance, supply chain and human resources in industries including energy, retail and manufacturing.

鈥淭his is made possible through AI embedded within enterprise resource planning processes, from finance and procurement to supply chain and HR systems, that understand context and act autonomously,鈥� said Maccotta. 鈥淪elf-optimising systems that learn, improve and adapt in real-time are matched to clean-core ERP architecture to give organisations simplified, cloud-based systems that drive profitability, reduce risk and enhance decision-making.鈥�

麻豆原创 cited data from听听indicating that the global autonomous enterprise market is projected to grow from about $49 billion in 2024 to more than $118 billion by 2030, with adoption accelerating across Europe, the Middle East and Africa.

The company said while few surveys use 鈥渁utonomous enterprise鈥� as a formal category, data on AI, ERP and AI agents reflects technologies underpinning autonomous models.

Recent data for the Middle East and Africa region indicates a market size set to grow at a compound annual growth rate of 8.7%, reaching $10.2 billion by 2032.

鈥淎I is enhancing efficiency and fostering innovation across industries, from automating routine tasks to enabling complex data analysis and providing predictive insights, while also improving decision-making and optimising business operations,鈥� Geness said.

麻豆原创 added that some analysts estimate AI could contribute $1.5 trillion to Africa鈥檚 economy if the continent captures 10% of the global AI market by 2030.

Data sovereignty

麻豆原创 executives said Africa鈥檚 digital transformation continues, with data sovereignty emerging as a key factor.

鈥淔or multinational organisations and technology companies, success depends on the ability to localise without losing global efficiency, to build trust while maintaining innovation, and to invest strategically in infrastructure and partnerships that align with both regulatory demands and customer expectations,鈥� Maccotta added.

The company said Africa鈥檚 data centre market is projected to exceed $9 billion by 2029, although it remains a small share of the global total.

Executives said autonomy does not eliminate human roles but changes them, shifting employees from managing repetitive processes to supervising systems and making strategic decisions.

Maccotta advises business leaders seeking to build autonomous enterprises to start by modernising the core and fixing the data foundation for AI-driven innovation.

鈥淩emember that technology is only part of the story, and that the strategy, people and partners that businesses choose are as important to building a truly connected autonomous enterprise. Focus then on automating processes that protect revenue, improve cashflow or unlock capacity first, and take care to prepare people by prioritising reskilling and upskilling.

“Finally, collaborate with technology partners that act more as advisors than vendors, and can guide the process of redesigning core business processes for the AI era. True transformation happens when businesses combine intelligent systems with visionary leadership, skilled people and trusted partnerships.鈥�

This article first appeared in .

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Many companies sit with years of technical debt, complex hybrid environments, disconnected听systems听and inconsistent metadata that make it difficult to build a reliable view of the听business. Businesses still grapple with ageing applications that cannot integrate with cloud platforms, while siloed departmental听systems听prevent teams from accessing the full picture needed for AI-driven decision-making.

The result is predictable: stalled AI听projects, unreliable outputs, and limited return on investment.

The need for a unified data foundation

The typical South African enterprise runs a mix of cloud听services, on-premises applications and bespoke听systems听that were built years ago to solve specific operational needs. While these听systems听may still work, they often lack the interoperability required to support modern AI initiatives. Data is stored in inconsistent formats, lack proper metadata, and often depend on manual extraction processes that strip away the听business听logic that AI models need to understand the context of the data and what it really represents.

This fragmentation affects everything from听financial听reporting to customer experience. Without a single, trusted view of data, predictive models become unreliable, automated processes fail, and teams lose confidence in machine-generated insights. For AI to scale, data must be complete, consistent, governed and accessible across the organisation.

An IDC report commissioned by Seagate previously found that听up to 68% of available enterprise data goes unused.

Modern data platforms address this by connecting all enterprise听systems, preserving听business听context, enabling real-time data access and allowing organisations to integrate with other providers. The outcome is a unified data fabric that supports analytics, applications and AI at scale.

Preparing听business听data for AI

Building听an AI-ready data foundation doesn鈥檛 happen by accident. It requires a deliberate, structured approach, following these five steps:

1 Assess the current data landscape

The first step is understanding what exists today. This means cataloguing data sources, identifying owners, documenting quality issues, and assessing integration gaps. It also involves mapping AI use cases to data requirements so that data preparation can be prioritised and aligned to real听business听needs.

For South African organisations with complex legacy environments, this assessment is essential to uncover hidden dependencies and address high-risk limitations early in the process.

2 Establish clear data governance and quality standards

Reliable data requires strong governance. Organisations should define roles, responsibilities and policies governing data access,听security, metadata and quality. This includes setting measurable standards for completeness, accuracy and consistency, supported by automated profiling tools. Metadata management is particularly critical: without clear definitions and lineage, teams cannot trust or effectively use the data.

Governance should also reflect South听Africa鈥檚 regulatory听environment, including POPIA requirements around privacy and听security.

3 Integrate and unify disconnected data sources

The next step is breaking down silos. Modern integration tools such as those built into 麻豆原创听Business听Data Cloud allow organisations to connect 麻豆原创 and non-麻豆原创听systems, unify data across cloud and on-premises environments, and maintain the听business听meaning of data as it moves.

This unified layer eliminates duplication, reduces manual extraction processes, and ensures teams work from a consistent, shared version of the truth. Real-time integration capabilities are especially important for AI models that need up-to-date information to make accurate predictions.

4 Clean, enrich and transform data

Raw data is rarely ready for AI. It must be cleaned, enriched and transformed, including correcting errors, removing duplicates, filling missing values and standardising formats. Organisations should also create new features that allow AI models to identify patterns more effectively and incorporate additional context from internal or external sources.

South African businesses with extensive unstructured data, such as PDF reports, invoices or call centre notes, should prioritise converting this content into structured formats for easy ingestion into AI models.

5 Validate, monitor and maintain data听pipelines

Even the cleanest dataset will deteriorate if not continuously monitored. Organisations should validate data before it feeds AI models, track data quality in real time, and monitor for drift or anomalies that can degrade model performance.

Automated governance tools help maintain data integrity, while clear documentation ensures teams understand how data is sourced, processed and used. Regular monitoring is essential in environments where听systems, processes and regulations frequently change.

Getting the data foundation right is a technical requirement and a strategic imperative. The organisations that prioritise data quality, integration and governance today will be the ones that scale AI confidently tomorrow, reducing risk, improving performance and unlocking new opportunities for听innovation听in an increasingly competitive market.

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The era of digitisation is giving way to something more profound: the Autonomous Enterprise听鈥撎�a business that can sense change, make decisions and act with minimal human intervention, all while empowering people to pursue revenue-driving strategic activities.

Autonomous operations are already being deployed across finance, supply chain, human resources, an in Industries like Energy, Retail and Manufacturing. In 2026, they will separate the most resilient and profitable businesses from the rest.

An Autonomous Enterprise goes beyond automating individual tasks by integrating autonomous ERP, business AI and clean data into the core of business operations. More than 50% of business processes run independently, and up to 80% of operational work is automated or AI-augmented.

This is made possible through AI embedded within enterprise resource planning processes, from finance and procurement, to supply chain and HR systems, that understand context and act autonomously. Self-optimising systems that learn, improve and adapt in real time, are matched to clean-core ERP architecture to give organisations simplified, cloud-based systems that drive profitability, reduce risk and enhance decision-making.

Crucially, autonomy does not remove humans: it redefines and empower their work. Employees move from managing repetitive processes to supervising intelligent systems, making strategic decisions and creating new value throughout the business.

2026 鈥榓 tipping point鈥�

The year ahead will be critical for organisations across Europe, the Middle East and Africa. In Europe, business leaders face an ageing workforce, complex supply chains, regulatory pressure, and the push for sustainability and data sovereignty. Middle Eastern nations are already deploying national AI strategies and sovereign cloud infrastructure as part of a rapid diversification from the energy sector. And despite inflation and debt pressures, a world鈥檚 fastest-growing digital economy and most youthful workforce are emerging in Africa.

While the challenges in each region are unique, at their core every organisation is seeking the same capabilities: faster decision-making, greater profitability, improved resilience, and sustainability at scale.

Businesses that fail to build these capabilities, and instead rely on manual processes, disconnected systems and spreadsheets, face growing risks: slower reaction time, shrinking margins, and higher operational costs.

This is why the business opportunity for Autonomous Enterprises is significant. The global Autonomous Enterprise market is expected to grow from听, and adoption is accelerating across EMEA.

听Global partner for business transformation

While I can see the scale of the challenge businesses face to transform into autonomous enterprises, I am equally excited at bringing 麻豆原创鈥檚 strengths in this arena to bear. Through our flagship 鈥� now more accessible than ever thanks to the RISE with 麻豆原创 initiative 鈥� we equip businesses with modern, clean core ERP systems that are upgrade-safe and AI ready.

, 麻豆原创鈥檚 generative AI copilot now supports 11 languages and features more than 400 embedded AI use cases across 26 industries, while the enables extensibility, data orchestration and clean core innovation for the world鈥檚 most critical industries.

My advice, to leaders seeking throughout the region to build Autonomous Enterprises, is to start modernising the core and fix the data foundation for AI-driven innovation. Remember that technology is only part of the story, and that the strategy, people and partners that businesses choose are as important to building a truly connected Autonomous Enterprise.

Focus then on automating processes that protect revenue, improve cashflow or unlock capacity first, and take care to prepare people by prioritising reskilling and upskilling. Finally, collaborate with technology partners that act more as advisors than vendors, and who can guide the process of redesigning core business processes for the AI era. True transformation happens when businesses combine intelligent systems with visionary leadership, skilled people and trusted partnerships.

In 2026, the most successful companies will go beyond digital transformation to achieve faster decision-making, greater operational certainty, and the ability to unlock new forms of growth and innovation.

This article first appeared in .

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鈥淯ncertainty is not going away,鈥� says , BTP product management at 麻豆原创. 鈥淵ou need to think about how you can transform your business for the years to come.鈥�

At the same time, artificial intelligence (AI) is revolutionising decision-making, redefining efficiency, and helping make it easier to run the business, he adds.

鈥淭he pace of change is accelerating, and businesses are asking how they can stay ahead of the change; how they can build business that don鈥檛 just keep up with change, but thrive on it.

鈥淭he ability to adapt, to innovate, to seize opportunities is no longer an advantage, but a necessity,鈥� Winkler says.

He believes that, to be resilient and navigate uncertainty, companies need to embrace entrepreneurial skills.

鈥淲e believe that in this time of change and technology disruption, entrepreneurial skills are more relevant than ever in small or corporate organisations.

鈥淭he first key skill is courage,鈥� Winkler says. 鈥淭his is about being adaptable, having no fear, and moving forward in a focused and lean way.鈥�

The second is resourcefulness. 鈥淓nsure you have the right resources in place, to accomplish a lot with few resources, and to execute on anything.鈥�

The third key skill needed in this fast-changing world is self-discipline. 鈥淏e self-driven,鈥� Winkler says. 鈥淭hink about transformation from a technology point of view, but prioritise what is important for the business.鈥�

At the same time, organisations need to be very clear about the way they want to go forward, Winkler adds. 鈥淐larity is needed now more than ever 鈥� not as a choice, but a necessity. Be clear about your transformation and about what you want to achieve.鈥�

Winkler explains that is the foundation on which the company has built its technology and transformation ecosystem.

As the foundation that underpins Business Suite, Business Data Cloud, and Business AI, BTP allows organisations to integrate and extend business applications faster; create business-relevant apps; and innovate and accelerate with AI.

Winkler points out that it is a unified platform available as public cloud or multi-cloud that harmonises 麻豆原创 and non-麻豆原创 applications, empowering customers and partners to innovate.

BTP is powered by more than 90 applications and services.

There are currently 33听000 customers on 麻豆原创 BTP, including 66% of the largest companies in the market.

New on 麻豆原创 BTP is better integration between 麻豆原创 Build and 麻豆原创 S/4 HANA. The company has also introduced additional AI features with Joule for Developers.

In addition, 麻豆原创 is continuously adding BTP to new data centres and regions. It has already built out to seven new regions this year, with more on the cards.

There is more functionality for users and more AI available for 麻豆原创 S/4 HANA Cloud.

More features are available in 麻豆原创 Business Data Cloud (BDC), and 麻豆原创鈥檚 Integration Suite makes it easier for customers to bring their ecosystem together.

The new releases are especially relevant for developers.

麻豆原创 Build now offers the ability to create Joule Skills and AI Agents 鈥� Joule Skills where the process path is known, and AI Agents where it isn鈥檛.

鈥淣ow, developers are able to enhance Joule鈥檚 out-of-the-box capabilities to support organisation-specific workflows,鈥� Winkler says. 鈥淭hey can deploy, monitor and manage their own Joule Skills in 麻豆原创 Build. 鈥淎nd, with the agent builder in Joule Studio they can build their own customised AI Agents.鈥�

There are also new features to help ABAP developers 听improve their efficiency. 鈥淚n the ABAP cloud environment, we have released intelligent features that help developerss with testing, and Joule will even offer recommendation to improve code.鈥�

Further enhancements improve developer efficiency in 听麻豆原创 HANA Cloud, helping them to make smart decisions while handling large amounts of interconnected data to achieve meaningful outcome.

鈥淏TP addresses the challenges of digital transformation and helps to accelerate customers鈥� move to the cloud,鈥� Winkler says. 鈥淚t helps customers to optimise and integrate processes so they can innovate while keeping the core clean.

鈥淭his empowers them to unlock the power of business data and AI.鈥�

This article first appeared on .

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This is because, today, technology is transforming transformation, says , vice-president and global innovation analyst at 麻豆原创.

And today, transformative technology is all about artificial intelligence (AI).

鈥淓xperts agree that AI is the third great wave of technology after the personal computer (PC) in the 1980s and the Internet in the 1990s,鈥� Elliott says.

鈥淏ut if you are not careful, waves can come crashing down on top of you. AI is very powerful, and can have unintended consequences.鈥�

Although it is most obvious in the visual context, AI is progressing in all directions, Elloitt points out. 鈥淭he process of rapid technological change and disruption is coming to your industry and your line of business.鈥�

Today, what鈥檚 holding up AI disruption is the fact that the rest of the ecosystem isn鈥檛 able to change as quickly.

鈥淚t鈥檚 a bit like parachuting a Formula 1 car into a medieval village. You can鈥檛 use the technology because the rest of the ecosystem isn鈥檛 there.

鈥淚n fact, if AI stopped progressing right now, we couldn鈥檛 use it to its full potential for 10 years.鈥�

For this reason, Elliott says AI could be taken to stand for accelerate innovation. 鈥淲e should use AI to adopt AI.鈥�

Today, a lot of AI and innovation in general is handmade, with developers all starting from scratch and working on one thing.

鈥淭o accelerate the adoption, we need to move to modern assembly lines, so we can use the AI faster,鈥� Elliott says.

He adds that 麻豆原创 provides the machines to build the technology.

鈥淲e offer things like the S, where customers create data that is harmonised in the Business Data Cloud, used to ground AI, which then goes to making a better application. And, as you create applications, you can add customisation.鈥�

麻豆原创 embeds AI in all its applications, and these are available to customers right now, Elliott adds.

鈥淏ut innovation is not actually about technology,鈥� he explains. 鈥淲hat is holding us back is the time, skills, and resources needed to exploit the technology.鈥�

Again, the 麻豆原创 Business Technology Platform can help, with 麻豆原创 Build offering aided innovation 鈥� another possible use for AI 鈥� for agile application development and customisation.

鈥淲e have the resources that can multiply efforts, let developers do more, faster, with customisations and extensions in the cloud.

鈥淎nd now you can do it in natural language, because it is designed for professional developers and also business users.鈥�

AI could also stand for automated identity, Elliott says.

And it could represent automatic integration as well. 鈥溌槎乖� Integration Suite is about AI-powered connections. It will do most of the heavy lifting in connecting system to one another.鈥�

Meanwhile, the 麻豆原创 BTP AI Foundation is a generative AI (GenAI) hub that gives customers everything they need to orchestrate customised AI, with a wide choice of models, grounding, data masking, filtering, prompt management, and lifecycle management.

At the core of any transformation is data, which is everyone recognises is important. 鈥淚n fact, it is really important,鈥� Elliott says. 鈥淚t is the essential input for AI in particular.

鈥淪o AI has to stand for accurate information. AI is useless without accurate information in realtime.鈥�

But there isn鈥檛 a company on the planet that doesn鈥檛 have a data quality problem, he adds.

鈥淚t is not a new problem, we know it鈥檚 hard to get budget to fix data. But this is an opportunity to ask for money to do just that. Now is a great time to establish governance, data ownership, and all the things you have wanted to do for years.鈥�

The second big problem is integrating data 鈥� which is also not a new problem.

鈥淭his is where comes in,鈥� Elliott says. 鈥淎nd we offer it as a service, so we can do more of it for you 鈥� integrate data from 麻豆原创 applications and also external data.鈥�

The helps with relationship extraction. 鈥淵ou already have this information, now we are gathering it and exposing it, and putting it in a format that you can use for your AI,鈥� Elliott explains.

AI could also represent analytics improved, which is why 麻豆原创 Analytics Cloud has the GenAI-powered Just Ask feature.

鈥淚n analytics, there is a dream of total situational awareness. Of bringing in data from all sources, but having overall vision. AI can be used to connect data and deal with fuzziness.鈥�

AI could also stand for agents incoming. 鈥淭his is the next generation of AI, moving along from the current efficient processes with pre-defined steps. But these processes can鈥檛 deal with ambiguity. Agents, on the other hand, can reason through what it needs to do next. So the processes and data can be a lot more unstructured than before.鈥�

Another interpretation of AI could be agents for business, Elliott adds. 鈥淭his is the next evolutionary step 鈥� in fact, some companies are already doing it 鈥� using AI to get rid of a lot of manual work.鈥�

AI could be used for automatic innovation. 鈥淲e have incredible amounts of information and amazing intelligence,鈥� says Elliott. 鈥淪o why not let the systems tell us what we should do next?

鈥淲e are starting to get there, and you can already get great automated system insights. And 麻豆原创 also has best practices, so we can provide customers with that out of the box.鈥�

Once that is in place, and customers need to implement their systems, automated implementation could be the final meaning for AI.

鈥淥f course, technology is not everything,鈥� Elliott points out. 鈥淵ou need to get people to adopt new ways of working 鈥� and AI is good for adoption optimisation and change management.鈥�

In conclusion, Elliott believes that AI today is like a staircase. 鈥淵ou have to take one step after the other. But in the future it will be more like an escalator.鈥�

The key to successful AI adoption lies not in the technology he adds, but in the people, culture, and organisation.

鈥淣o matter how much you have invested in adoption, culture, and change management 鈥� invest more.鈥�

This article first appeared on .

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麻豆原创 SE听(NYSE: 麻豆原创) announced that VFS Global, the world-leading provider of visa, consular and technology services to governments and diplomatic missions, will leverage 麻豆原创 software to help it develop leading-edge AI-powered digital solutions for cross-border mobility and citizen services.

Cross-border mobility and citizen services are becoming increasingly digital, and governments are looking into the use of innovative technologies such as artificial intelligence to drive efficiency and sovereign security. To accelerate its innovation road map and help governments meet the increasingly complex needs of travelers and citizens, VFS Global is adopting 麻豆原创 S/4HANA Cloud Public Edition and other 麻豆原创 solutions.

“We take great pride in partnering with 麻豆原创 as a leading and trusted technology and AI company,” said Zubin Karkaria, founder and CEO of VFS Global. “By combining our deep expertise in visa, consular and citizen services with 麻豆原创’s world-class solutions, we empower governments to enhance efficiency, strengthen security and enable seamless mobility for millions of travelers around the world.”

“With 麻豆原创 solutions at its core, VFS will be able to leverage the latest innovations to become an even stronger partner for governments, travelers and citizens worldwide,” said Christian Klein, CEO of 麻豆原创 SE.

In line with its vision to embrace technological innovation to support governments and diplomatic missions worldwide, VFS Global has also chosen 麻豆原创 Business Technology Platform and the 麻豆原创 Business Data Cloud solution to deliver leading-edge and AI-powered solutions to its customers and to drive operational excellence across its global operations.

“By combining the strengths of VFS Global and 麻豆原创, we are elevating cross-border mobility and citizen听services to the next level”, said Michael Nilles, member of the VFS executive board and chief digital and technology officer. “Strategically, this positions us as a leading force in shaping the future of GovTech and TravelTech, powered by technology and AI innovations that benefit governments, travelers and citizens worldwide,” he added.

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Gaming is something that keeps inspiring me. I鈥檓 amazed by the speed, accuracy, and level of concentration of professional players. It鈥檚 impressive how this industry has evolved and grown over just a couple of decades.听

commands an imposing presence in the esports world, boasting over 160 professional players across more than 15 different games and a staggering fan base of over 10 million followers on various social media platforms. With more than 75 premier events won, Team Liquid is one of the most successful organizations in competitive gaming.听

The game with the highest viewership and extensive fandom is League of Legends. Team Liquid successfully competes with their League of Legends team, which recently won the League of Legends Championship Series (LCS) 2024 Spring tournament.听

In League of Legends, the goal is to create a strong and balanced team consisting of five characters, called 鈥渃hampions,鈥� in order to outplay and outsmart the opponents during the game by being one step ahead of competition.听

Teams participate in a pre-game draft process to select champions before a match. This involves banning and picking champions from a pool of 166 choices to create a strong team.听

Champions are the in-game figures controlled by each player. Each champion has particular skills and areas in which they excel. Putting the champions together allows the team to play in various strategic directions to win the match.听

After choosing five champions (鈥減ick鈥�), each team is also allowed to remove five champions from the pool (鈥渂an鈥�). Those players cannot be picked by either side. This can be utilized to remove specific parts that would otherwise counter a strategy or hinder the other team from playing their favorite style and/or composition.听

Esports teams and their analysts need to prepare for the draft process, as it requires knowledge of the opponent鈥檚 favorite picks and strategies. Imagine a five-a-side dodgeball match, but before the match begins, the five players from each team draw their champions from a pool of 166 individual champions.听

With bi-weekly updates to the game (鈥減atches鈥�), especially affecting the champions as well as indirectly teams practicing and developing new strategies, competitive League of Legends is an ever-changing game. It creates the need to constantly adapt your draft to a new environment, to analyze both your own and the opposing team鈥檚 behavior.听

Furthermore, the nature of the draft process and the varying strategies of opponents make accurate predictions difficult. Esports teams have only a week to prepare for the game and gather knowledge about the other team鈥檚 favorite champion picks, strengths, and weaknesses.听

Previously, Team Liquid coaches prepared draft scenarios based on manual analysis of the opponent team鈥檚 draft behaviors and champion preferences. However, the challenge was that manual analysis is done before the draft, with the best potential pick or ban changes based on the decisions of the other team. Additionally, the sheer number of potential matches to choose from and the different strategies employed by opponent teams make manual draft prediction very difficult.听

麻豆原创 Helps Change the Game听

What if Team Liquid could analyze in seconds the best choice for upcoming drafts, including picks and bans, while considering more than 6,000 professional esports matches from the past year? What if the analysis would also consider the impact of game patches from the publishers by taking an additional 1.6 million amateur matches into account to assess changes in the power attributes and strengths of the champions? With 麻豆原创, this is now a reality.听

By using 麻豆原创 AI Core to train a generative AI model that takes data from past matches and puts them into context of the upcoming game, Team Liquid gets suggestions of the best draft picks and bans to maximize the chances to win.听

The solution is built on 麻豆原创 Business Technology Platform (麻豆原创 BTP), and the data is stored in 麻豆原创 HANA Cloud to cope with the 1.6 terabyte game data from past games. The result is an intelligent draft bot training, an application that runs on 麻豆原创 BTP, visualizes the predictions, and provides Team Liquid with the current winning probability after each pick and ban.听

Manual Analysis Is a Thing of the Past听

With the AI draft bot, Team Liquid can train for draft situations against any professional team they face in a matter of seconds. This is achieved by incorporating multiple influencing factors based on an unprecedented number of matches. The coaches and players benefit from the opportunity to conduct what-if analyses and derive valuable knowledge from the data to simulate new strategies. This is also reflected in the time saved compared to the previous manual analysis: Team Liquid saves approximately 10,000 hours per year per year with the solutions from 麻豆原创.听

Relying on 麻豆原创 BTP and 麻豆原创 HANA Cloud, 麻豆原创 Business AI provides Team Liquid with the opportunity to further improve their game by leveraging data to make more informed decisions. Here is where fun and business meet.听

This is how the power of business AI is made tangible in a perfect way 鈥� not just for gamers.

This article first appeared on the 麻豆原创 News Center.听

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The post Esports Powerhouse Team Liquid Wins Big with 麻豆原创 Business AI appeared first on 麻豆原创 Africa News Center.

By examining innovative solutions, such as and the concept of a data fabric, we uncover how organisations can transcend traditional barriers, harness the full potential of their data assets, and pave the way for enhanced efficiency and competitiveness.

has seamlessly implemented Datasphere at clients and a highly-effective data-driven strategy, which has already demonstrated its immense impact and power.

As businesses aim to implement data-driven strategies, it is crucial to break down the silos that exist between different data sources. Doing so will unlock the full potential of their data assets and give them a competitive advantage in today鈥檚 digital world. With the plethora of tools available today, it is easier than ever to extract valuable insights from your own data.

For clients with multiple data hubs on heterogeneous cloud environments, including investments, the business data fabric can now help eliminate silos and lead to more significant efficiency gains.

The business data fabric provides great value to customers by simplifying the delivery of accurate data in business terms, even when dealing with highly-distributed data landscapes. This means that business innovation is no longer limited by the location of data, slowed down by the creation of new data staging plans, or hindered by incomplete business context.

A data fabric is an advanced data management architecture that allows organisations to integrate large volumes of data from various sources. It provides a consistent and reliable way to access, analyse and share data across the organisation.

With a data fabric, users of all skill levels can easily access and make sense of complex data sets, enabling them to make informed decisions based on accurate and relevant information. This can lead to improved business outcomes, increased productivity and gain a competitive advantage in the market.

Integrating AI in business operations will undoubtedly prove to be a game-changer. By offering rapid insights and enabling prompt decision-making, AI has the potential to revolutionise the way businesses operate.

The power of AI in the world of data warehousing is truly awe-inspiring, as it offers unparalleled insights on the fly. Think of it as a copilot that can assist you in determining, guiding and achieving your goals.

The new AI copilot, , in and , as well as the , enables users to find hidden insights and patterns in complex data.

It is a platform designed to be open and flexible, allowing for seamless integration with a diverse range of sources and technologies. 麻豆原创 has announced partnerships with , , , and to simplify customers鈥� data landscapes.

By integrating their data and AI platforms with 麻豆原创 Datasphere, organisations can now access their mission-critical business data across any cloud infrastructure in an open data ecosystem.

麻豆原创 Datasphere is a comprehensive data management platform that provides a centralised solution for all your data-related needs. With 麻豆原创 Datasphere, you can easily access, integrate and analyse your data in a single location, without the need for managing multiple silos. This means that you no longer need to spend countless hours tracking down information from disparate sources, but instead can focus on deriving insights and making data-driven decisions.

The ability to access data in real-time, integrated across various business functions, has been a crucial development in advancing global business innovation. Our clients can now work seamlessly with 麻豆原创 Datasphere and make the most of our existing portfolio of data platforms, business intelligence, and planning analysis solutions. This enables them to move beyond manual and siloed analysis processes and optimise their target revenue and GP, sales goals, and operational capacity requirements. With this approach, they can effectively harness their data to achieve their business objectives.

Contact Decision Inc. today to explore how the 麻豆原创 Datasphere Platform can empower your organisation’s growth journey.

The post Paving the Way for Data Management Through 麻豆原创 Datasphere appeared first on 麻豆原创 Africa News Center.

鈥淐apturing data to make better decisions is an enterprise technology imperative that鈥檚 become increasingly critical as AI 鈥� which relies on quality data 鈥� revolutionizes every aspect of business,鈥� said Juergen Mueller, 麻豆原创 Chief Technology Officer and member of the Executive Board. “Our newest 麻豆原创 Datasphere innovations, as well as an expanded partnership with Collibra, represents a quantum leap in our ability to help customers drive intelligent business transformations through data.鈥�

At the heart of these announcements is the business data fabric, an architecture that helps ensure data is not just an asset but also the core underpinning of strategic initiatives. The innovations and partnership announced today equip organizations to deliver meaningful data to data consumers 鈥� with business context and logic intact.

“We have decided to leverage 麻豆原创 Datasphere for a modern business data fabric architecture in conjunction with our 麻豆原创 S/4HANA landscape. It allows us to effectively establish a modern data analytics platform that enables a business self service capability on the basis of trusted data and data models,鈥� said Achim Welter, Senior Director ERP, Digital & IT Strategy, Hershey鈥檚.

Today鈥檚 麻豆原创 Datasphere innovations help customers achieve a unified data view that simplifies their data landscapes while retaining context and logic 鈥� enabling them to adapt faster to market changes and make more-efficient decisions. From new copilot and vector database capabilities that help ensure business context remains constant in generative AI outputs to a new knowledge graph that helps uncover insights and patterns in complex data, 麻豆原创鈥檚 data innovations help ensure customers have the full power of their data at their fingertips.

Today鈥檚 key innovations include:

Generative-AI Copilot and AI Governance

麻豆原创鈥檚 generative-AI assistant, the copilot, is now coming to the 麻豆原创 Analytics Cloud solution to automate the creation and development of reports, dashboards, plans and more. This automation is enabled by the 麻豆原创 HANA Cloud vector engine capabilities, which combine the power of large language models with the relevant data of your organization 鈥� helping ensure business context is a constant for generative-AI outputs.

Incorporating generative AI across the business isn鈥檛 possible without trusted and governed data. To provide organizations with a solution to govern the policies, processes and practices of AI, 麻豆原创 is announcing an expansion of our partnership with Collibra to integrate Collibra鈥檚 AI Governance with 麻豆原创 data assets. This can help provide transparency and accountability for organizations and help ensure regulatory, compliance and privacy policies are met.

Discover Hidden Insights and Patterns with Knowledge Graph

With the new 麻豆原创 Datasphere knowledge graph, organizations can discover hidden insights and patterns across their applications and systems. This enables both technical and business users to deeply understand the relationships between data, metadata and business processes, as well as boost the effectiveness of machine learning and large language models.

Unified and Advanced Planning and Analytics

The new 麻豆原创 Datasphere integration with 麻豆原创 Analytics Cloud offers a single data management system and advanced analytics to power cross-organizational planning. Planners can leverage a single flexible model to break down silos between planning using one tool for data preparation, modeling and planning.

Additionally, business users can use the new compass capability in 麻豆原创 Analytics Cloud to realize better outcomes in planning and analytics through data-driven simulation. It enables organizations to run complex simulations using a chat interface to evaluate predictive outcomes and continually adjust controllable variables to find the optimal plan.

This supports customers to transform their planning by unifying financial, operational, supply chain and workforce planning with native connection to 麻豆原创 applications and third-party data.

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About 麻豆原创

麻豆原创鈥檚 strategy is to help every business run as an intelligent, sustainable enterprise. As a market leader in enterprise application software, we help companies of all sizes and in all industries run at their best: 麻豆原创 customers generate 87% of total global commerce. Our machine learning, Internet of Things (IoT), and advanced analytics technologies help turn customers鈥� businesses into intelligent enterprises. 麻豆原创 helps give people and organizations deep business insight and fosters collaboration that helps them stay ahead of their competition. We simplify technology for companies so they can consume our software the way they want 鈥� without disruption. Our end-to-end suite of applications and services enables business and public customers across 26 industries globally to operate profitably, adapt continuously, and make a difference. With a global network of customers, partners, employees, and thought leaders, 麻豆原创 helps the world run better and improve people鈥檚 lives. For more information, visit .

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This document contains forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations, forecasts, and assumptions that are subject to risks and uncertainties that could cause actual results and outcomes to materially differ. Additional information regarding these risks and uncertainties may be found in our filings with the Securities and Exchange Commission, including but not limited to the risk factors section of 麻豆原创鈥檚 2022 Annual Report on Form 20-F.

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