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Introduction and overview of SAP Business Warehouse

Hello Everyone,

In this article, let’s look at Introduction and overview of one of the major Data Warehousing system in the industry i.e. SAP Business Warehouse.

What is a Data Warehouse?

A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process (as defined by Bill Inmon).


What is Data Warehousing?

The process of designing, building, and maintaining a data warehouse system.

Tools available in the Market:

Some of the data warehousing tools available in market are SAP BW, Informatica, hyperion, datastage, cognos and Teradata


SAP Business Warehouse (also known as SAP NetWeaver Business Warehouse or SAP BW) is  an Enterprise Data Warehouse solution of SAP and runs on standard RDBMS and recent SAP’s HANA in-memory DBMS.

SAP BW is capable of performing ETL (Extract, Transform, and Load) operations along with Dimensional Modelling and Reporting capabilities.


SAP released the first version of BW in 1998. Let’s see the evolution of BW versions vs. Year:



From version of 7.4, BW is optimized for SAP HANA. It enables the use of SAP HANA as the underlying database and facilitates the optimization of applications for SAP HANA. It also includes new and changed features for the Application Server ABAP, connectivity, UI technologies, SAP Business Warehouse and security.

SAP BW Architecture:

                The below figure gives us an architectural overview of typical BW system:


SAP BW – Layers & Data Flow:

The below figure shows the data flow through different layers of SAP BW system:


SAP NetWeaver BW offers flexible ways of integrating data from various sources. Depending on the data warehousing strategy data can be extracted from the source and load it into the SAP BW system, or directly access the data in the source, without storing it physically in the Enterprise Data Warehouse. (In this case the data is integrated virtually into the EDW. Sources for the EDW can be operational, relational datasets (for example in SAP systems), files or older systems.) Transformations allows us to run a technical cleanup and to consolidate the data.

Proceed to the next page to continue reading…

By | 2016-03-22T04:34:15+00:00 June 29th, 2015|BW|0 Comments

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