SAP Datasphere running on Business Data Fabric Architecture

SAP Datasphere

SAP Shaping the Data-Driven Business World

We are three months into 2024, and SAP has made it yet again by presenting to the world “SAP Data Unleashed 2024”. This time, SAP’s focus is on how the future of global businesses can establish seamless connection between disparate data silos and get reliable data output from AI. The event was packed with full of tangible promises showcasing how SAP Datasphere and SAP Analytic Cloud (SAC), along with its open data ecosystem partners, can transform the way businesses use data. 

SAP Datasphere, an Overview

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Image: High-level Architecture View of SAP Datasphere

One of businesses’ prime objective is to provide meaningful data to its consumers depending on business context while leaving the business logic intact. SAP Datasphere’s business fabric architecture lays the foundation for seamless data management across different SAP and non-SAP systems.  

Business fabric architecture helps businesses address one critical challenge, access to insights regardless of where their data is, as data is distributed among different applications and systems in cloud and on-premise environments. 

SAP Datasphere, along with the data and AI capabiliites  of open data ecosystem partners, can: 

New Capability Enhancements to SAP Datasphere

Since its release in 2023, SAP Datasphere has been the go-to guide for businesses involved in instant data-driven decision making. 

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SAP Datasphere Knowledge Graph

Last year marked the introduction of analytical model in SAP Datasphere to allow a multi-dimensional and semantically rich analytical model. Adding to this layer of analytical model, this year, SAP has introduced the SAP Datasphere Knowledge Graph.  

This new feature captures the rich and complicated relationships existing across the enterprise by combining business data with relational meta data. Now, businesses can have clarity around the data that are being fed to AI, and help those systems address any business context-driven questions. 

As a crucial component in business AI applications, this helps businesses to analyze the data usage patterns and find trends or potential issues. Juergen Mueller, CTO of SAP SE, said that a latest survey in the technology fraternity stated, knowledge graphs are more accurate than vector engines when dealing with structured data in the context of Large Language Models (LLMs). 

Collibra and SAP Datasphere

Last year, the partnership between Collibra and SAP Datasphere introduced end-to-end data governance to help SAP customers get the most out of their data. SAP believes to be future ready, governing AI-generated data is a must. Enterprises of every size are showing greater interest in using AI in their businesses. Through this collaboration, SAP wants to ensure that the regulatory compliance and privacy policies of their business customers are met by delivering trusted data and AI governance.

Unifying Several Planning Processes into One

Globally, CFOs are looking strenuously to create a data-driven culture that in turn helps them create a fully harmonized enterprise planning platform. However, a general planning platform needs to take data from several different departments or business sources, and this has its own limitations. The business data fabric architecture in Extended Planning and Analysis (xP&A) helps organizations address this gap by weaving together data from SAP S/4HANA, SAP line of business applications, and third-party sources.  

This feature builds on the robust functionalities of data and analytics platform, effortlessly integrating with different lines of businesses. Now, businesses can find the right strategy to adapt to changing market dynamics. Adding to this, planners can now leverage the potential of SAP Generative AI Copilot Joule to create and develop business plans with SAC. 

SAP Analytic Cloud Affirming Cloud Transition

In a move to affirm its cloud transition, SAP is closely monitoring the infrastructure costs incurred in the form of data center costs. Now, SAP has a solid infrastructure demand plan interlinked with capacity plan of data centers. This will help SAP to avoid shortages or excess capacity reserved by SAP at hyper-scalers. This feature takes shape through SAC, ensuring every information is reflected on P&L planning. 

Conclusion

All-in, the underlying business data fabric architecture helps CIOs across the globe implement a holistic data and analysis strategy. With business AI becoming the new frontier, data management, AI, and planning must be woven much better than ever to manage big datasets of the future. And it’s no doubt that SAP Datasphere is on track to this plan. 

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