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SAP Business Warehousing/Business Intelligence (BW/BI) Introduction

SAP Business Intelligence (BI)

SAP is full formed as Systems, Applications and Products in Data processing and SAP’s Business Intelligence (BI) or SAP Business Warehousing(BW) is basically a SAP’s module which is created in order to analyze and to create reports on the basis of data from different heterogeneous data sources. SAP Business Warehouse (BW) integrates data from different sources, transforms and consolidates the data, does data cleansing, and storing of data as well. It also includes data modeling, administration and staging area.

SAP BI/BW is a technical module created by SAP, previously it was named as Business Information Warehousing (BIW), after then it became Business Warehousing (BW) and then again Business Intelligence, currently it is known as SAPBusiness Intelligence (BI) also it is a very vast module of SAP, as it requires the designing of the database which is considered to be one of the hardest task to be done. As being a technical module, it is somewhat different from other modules of SAP. 

The data in SAP BW/BI is managed with the help of a centralized tool known as SAP BI Administration Workbench. The BI platform provides infrastructure and functions which include: 

  • OLAP Processor,
  • Metadata Repository,
  • Process designer and other functions.

Transaction code for this is RSA1.
The Business Explorer (BEx) is a reporting and analysis tool that supports query, analysis and reporting functions in BI. Using BEx, we can analyze historical and current data to different degree of analysis.
SAP BW/BI is known as an open, standard tool which allows us to extract the data from different systems and then send it to the BI system. It also evaluates the data with different reporting tools and you can distribute this to other systems.
Conceptual layers of data warehousing is given below in a diagram:

Persistent Staging Area (PSA)

The data extracted from the Source Systems first enters into the Persistent Staging Area. The data at this layer is the raw data which is in unchanged form. Data is consolidated and cleansed only in the next layers.
Staging area is a temporary table that holds the data and connects to work area or fact tables. In the absence of staging area the data load will have to go from the OLTP (Online Transaction Processing) system to the OLAP (Online Analytical Processing) system directly which hamper the performance of OLTP system.     

Data Warehouse Layer (DWH Layer)


Data from the Persistent Staging Area is loaded into the Data Warehouse Layer. It has corporate information repository. Data in this layer is stored for a longer period i.e., entire History data (for example, last 5 years data) is stored here in this layer. No aggregation of reporting-relevant data; the granularity of the data stored in this layer is at line-item (detailed) level.


Operational Data Store Layer

Data is loaded to an Operational Data Store Layer very frequently on a continuous basis from the source systems. Hence the data in this layer contains all the changes to the data that was done throughout the day. Data from Operational data store later can be loaded to the Data warehouse layer at particular timings (say end of the day) to update the date in Data warehouse Layer. This Operational Data Store Layer can also be used in case of any emergencies when the data in the data warehouse and data mart layers are lost. In such situations data can be loaded from the Operational Data Store layer to the Data Warehouse Layer and Data Mart Layer. ODS is not based on star schema model but they are in a flat files format.

Architected Data Mart Layer

Architected Data Mart Layer also known as Info cube. It is designed to store summarized and aggregated Data for long period of time.  Data from the Data Warehouse Layer is loaded into the Architected Data Mart Layer. It is used in Analysis and reporting. The data is at a high level relevant for creating reports displaying these data. Data manipulation with business logic is done at this layer. It consists of a central fact table (Key Figures) surrounded by several dimension tables, it is used to support BW queries.
Key Components of SAP BI System:

Business Intelligence is a core component of SAP Net Weaver. The figure below shows the key components of a BI system.

·        Data warehousing

This is mainly to Extract, Transform and Load data from source systems that is to perform the ETL process.

·         BI platform –

The BI platform layer contains BI services to support complex analysis tasks and functions. It contains the Analytic Engine, which processes the data requested through BEx analysis navigation. Its interface allows entry and manipulation of data as part of BI Integrated Planning. It also has special analysis tools such as the Analysis Process

Designer (APD) and the Data Mining which provide analysts at your company with the tools to merge, mine, pre-process, store, and analyze data.
·    BI Suite – These tools helps in creating reports for analysis purposes. It contains the Business Explorer (BEx) which provides flexible reporting and analysis tools.            The following areas in the Business Explorer can be used for Data Analysis:

1   – BEx Analyzer (Microsoft Excel-based analysis tool with pivot-table-like features).
     – BEx Web Analyzer (Web-based analysis tool with pivot-table-like features)
     – BEx Web Application Designer (customer-defined and SAP BI Content provided)
     – BEx Report Designer (highly formatted Web output).

SAP BI/BW Architecture:
SAP BI/BW has a three tier architecture:

Database Server: 

This is the server where data gets physically stored. (ODS, PSA, Info cube and metadata repository).

Application Server: 

The application server is based on the OLAP processor. It is used to retrieve data stored in the database server.

Presentation Server: 

The presentation server is the one that manages reporting and data access.

1   –  Data is extracted from the Source Systems.2   –  Data is staged at the Persistent Storage Area (PSA). This holds Source like data.3   –  Data is cleansed, loaded and stored in Data Store Object.4   –  Data is viewed at multiple dimensions in the Info cube.5   –  Data is available by the OLAP processor to the Business Explorer to display data   as    per the requirement analysis of the business.6   –  Data can be made available to SAP/Non-SAP, Data Marts by the Open Hub Service         (Info spoke).

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