What data processing steps become obsolete when using SAP S/4HANA Analytics?

When using SAP S/4HANA Analytics, the processing of pre-computed aggregation views becomes obsolete due to the platform's advanced in-memory computing capabilities. Traditional data processing methods often relied on pre-aggregating data to enhance performance for reporting and analytics. However, SAP S/4HANA leverages real-time data processing and dynamic calculations, enabling users to access and analyze data without the need for these pre-computed structures.

In S/4HANA, the underlying columnar storage and in-memory processing allow for instantaneous data retrieval and processing, which significantly reduces the complexity and time associated with maintaining aggregation views. This capability enhances flexibility, as users can perform analysis on current, detailed data rather than on previously summarized information, ultimately leading to more accurate and timely insights.

The other processing steps, such as OLTP, OLAP, and ETL, still serve their purposes in the larger framework of data management and analytics, albeit with different roles or adaptations within the S/4HANA ecosystem. The elimination of pre-computed aggregation views is what sets S/4HANA apart, allowing for a more streamlined and efficient analytical process.