Home > HANA > Key Considerations for Building Successful Analytic SAP HANA Models

Key Considerations for Building Successful Analytic SAP HANA Models

Part 1 – SAP HANA Information Views

In this two-part blog series, I’ll discuss some key tips for building successful analytics models in SAP HANA. These considerations are specific to Information Views and Model Design.

In this post, I’ll describe SAP HANA Information Views and provide tips how to maximize their effectiveness.

What are SAP HANA Information Views? 

SAP HANA provides information views to construct basic logical multidimensional models to produce advanced data calculations. SAP HANA Information Views are designed to work with the different query engines available in SAP HANA.

There are three main types of Information Views – attribute, analytic and calculation. All three types of information views are non-materialized views. Any design produced in an SAP HANA Information View are entirely logical and the result set is materialized at run-time. This creates agility through the rapid deployment of changes since there is no latency when the underlying data changes.

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contributor_don_loden_lgAbout Don Loden
Don Loden is an information management and information governance professional with experience in multiple verticals. He is an SAP-certified applications associate on SAP EIM products. He has more than 15 years of information technology experience in the following areas: ETL architect, development, and tuning; logical and physical data modeling; and mentoring on data warehouse, data quality, information governance, and ETL concepts. Don speaks globally and mentors on information management, governance, and quality. He authored book SAP Information Steward: Monitoring Data in Real Time and is the co-author of two books: Implementing SAP HANA, as well as Creating SAP HANA Information Views. Don has also authored numerous articles for publications such as SAPinsider magazine, Tech Target and Information Management magazine.

Categories: HANA
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