Item: SAP HANA Cloud
Rating: 9
Author: Verified User

Overall Satisfaction with SAP HANA

Use Cases and Deployment Scope

We used to SAP HANA to build a decision support system for retailers offering perishable goods. The core of the system is a machine learning algorithm that provides demand forecast based on transactional data (POS data) in real-time that are required for daily ordering decision as well as intra-day shelf replenishment. Thus, the provided demand forecasts are mainly used by store managers and clerks. However, we also implemented reports for the different management levels (e.g. store, region).

Pros and Cons

Pros

Real-time OLAP queries on transactional data.
Integrated application layer (XS/XSA).
RServe support

Cons

PAL offers only basic algorithms.
Exception handling in SQLScript is limited.
Multi-threading in SQLScript is not possible.

Return on Investment

Decision support leads to better inventory management of perishable items.
Provided demand forecasts lead to time savings for operational staff.
Better product availability caused increased revenues.

Alternatives Considered

SQLServer

MS SQLServer is an alternative if the data foundation is not very big and a separate application layer or Excel can be used for reports.

Other Software Used

Oracle Java SE, RStudio, Microsoft SQL Server

Likelihood to Recommend

SAP HANA is an appropriate choice if an analytical applications is based on a (very) large data foundation that needs to be accessed and aggregated (OLAP queries) in real-time. It also provides an application layer that allows to build web-based front-Ends using SAP UI5.

If the data foundation is not very large or real-time queries are not required SAP HANA is likely not be an appropriate choice given its pricing model.

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SAP HANA for real-time Decision Support in the Retail Industry