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German software giant SAP Pushes the bar on the front of the data to supply the use cases of the new generation of AI. The company today presented Business Data Cloud (BDC), a new SaaS product that embraces Lakehouse architecture to help teams enrich the data from their SAP ecosystems with external data assets from different source systems and drive long -term value.
The product is the result of historical collaboration with the major data ecosystem. Essentially, SAP BDC incorporates the capacities and data of the data intelligence platform of Databricks. This removes the need to create and maintain complex pipelines and creates a harmonized database for advanced AI agents and analytical workloads.
Several companies, including Henkel, use BDC to feed their AI projects. SAP itself uses BDC enriched to feed a new era of Joule agents focused on specific areas such as finance, service and sales. Development makes SAP another notable actor, a bit like Microsoft and Salesforce, strengthening its data platform to lay the foundations for AI.
Foundation of SAP Reworked Data
Over the years, SAP has established itself as one of the main players in business resources planning (ERP) with S4 / Hana Cloud and several critical applications for finance, the supply chain and management of the human capital. These applications produce data on the level of petacts with the commercial context and have fueled AI and the analytical value for teams, via the business technology platform (BTP).
Until now, SAP BTP has had a `datasphere ” which allows companies to connect SAP data with information from non -SAP systems and possibly link it to SAP Analytics Cloud and other internal tools for applications downstream. Now, the company is evolving this unified BDC experience, natively fueled by data data.
What SAP Business Data Cloud offered
This means that SAP adopts the architecture of Lakehouse, creating a unified foundation which combines all SAP Data products – finance, expenditure and supply chain data in SAP S / 4HANA and SAP ARIBA, to learning data and talents in SAP Successfactors – with structured structured and unstructured data from other various but commercial scientific systems, stored in Databricks.
Once the data is unified (via zero copy, bidirectional sharing), SAP BDC can take advantage of specific capacity to Databricks for workloads such as data warehouse, data engineering and AI, all governed by the data unit catalog.
“We take all these different data products, which are provided and managed by SAP … and we will persist in the Lakehouse of Sap Business Data Cloud, in a harmonized data model,” said Irfan Khan, President and CPO for data SAP and SAP analyzes, said Venturebeat. “This Lakehouse will have data capabilities on users on which users can rely.”
Previously, said Khan, users who had a large percentage of their data in data data and SAP in S4 or BW had to build and manage complex pipelines and reproduce all data of data on the SAP platform while Reconstructing all semantics and basic basic data model at the same time. The approach has taken time and forced them to keep their pipelines up to date with the modification of the data. However, with the native integration of Databricks, users have access to everything in one place and can directly carry out data engineering, data science and other tasks above BDC.
“In Datasphere, you had a way to do a similar thing, but these are all data managed by the customer,” said Khan. “So you had to access the data platform, select data sources and create data pipelines. Then you had to understand what to reproduce. Here, everything is managed by SAP. »»
What it means for businesses
Basically, this product fueled by Databricks gives teams a faster and easier way to unify and mobilize their commercial data assets locked in SAP and Databricks environments.
The combined and semantically improved data will open the way to the creation of new generation AI applications aimed at different use cases. For example, a team could use the capabilities of the Databricks mosaic AI to develop AI agents specific to the domain that could use the context from SAP commercial data as well as specific databricks external data to automate certain functions human capital management or supply chain.
In particular, SAP itself uses this improved data foundation to feed the ready-to-use joule agents aimed at automating tasks and accelerating workflows through the sales, service and financing functions. These agents deeply understand the processes from start to finish and collaborate to solve complex commercial problems.
Beyond that, BDC will have an “insight apps” capacity, which will allow users to connect their data products and their AI models with real-time external data to provide advanced analyzes and planning between commercial functions .
More upcoming data partners
Although the partnership highlights a major decision for Databricks and SAP, it is important to note that the major data led by Ali Ghodsi will not be the only one strengthening BDC.
According to Khan, the sharing of data and the opening of the ecosystem are the first principles of design of the company – and they will extend to other data platforms via their partner connection capacities. This means that a business user will be able to choose the platform he prefers (or that it is locked) and to share the bidirectional data for targeted use cases.
