Last week SAP AG announced at the company I work for as a consultant, their AI Innovation strategy. This is the latest addition to come into an Innovation and Transformation program that started with a simple with moving into Hana Databases, and thus seeking seemless integration between applications at a higher speed and with full business process visibility via embedded standard LIVE analytical apps. Think pervasive technology and then, think further.
Where before code in the form of ABAP, or classic BW was used, we now had SAC or SAP Analytics cloud running LIVE on top of S4 systems with full open data concepts. Where data access silos were the law, democratization of data was the new guideline. Business warehouse Cloud (Datasphere) was launched in 2023, with enhanced integration and data modelling capabilities, with it came the power of integration 3rd party digitalization as well as robotic solutions . This data enablement allowed for the generation of LIVE Data and Meta data, and the use of LIVE data as interfacing and intelligence enabler; Law of Amara passed. Nowadays, SAP Joule is embedded atop apps for predictive analytics in Operations, Logistics, Finance, SCM, FSCM, etc. SAC is given a new spotlight and enhanced with full AI capabilities including natural language usage to drive analytical reporting and predictions. that aid in critical and live decision making. Data Products or fit to purpose data sets take over and are used preferably over code as they facilitated interpretability and reusability and are even used to connect as a huge data net or mesh as Datasphere enables a Data Fabric concept with Lakehouse capabilities coming soon.
All carefully done in layers with the data carefully curated, quality controlled and validated to cover industry specifics, with the higher effort being convincing others that this was the right and consistent way to go, and to urge those others to think wiser in terms of perceiving data as a product; be it Raw, Interim or Finished product, though data is always evolving and transforming as it moves through the many layers of an IT and/or digital ecosystem, becoming each time closer to consumer needs. And as all products, data requires to be carefully catalogued to facilitate its identification, acqusition and consumption by end users, intelligence enablers and data scientists alike. The approach is pervasive, innovative and truly transforming.
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