The document provides an overview of SAP BW (Business Warehouse), including its key components and architecture. SAP BW is a data warehouse system optimized for reporting and analysis. It includes preconfigured support for extracting data from SAP systems like R/3 as well as tools for extracting from non-SAP sources. The core components include the Administrator Workbench for managing metadata and content, data modeling tools, extraction and loading processes, the operational data store, and BEX reporting tools. Data is loaded from source systems into an in-memory database optimized for online analytical processing.
7. Business Content Financial Accounting General Ledger Accnts Receivable Accnts Payable Special Ledger Profitability Analysis Product Costing Overhead Costing Profit Center Accnt Controlling Sales Purchasing Inventory Management Production Project Management Logistics Time Management Training & Events Human Resources Payroll Accounting Fixed Assets Administration
8. Close the Loop Common Meta Data - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Transaction Processing OLTP Transformation DSS External Extraction Action Analysis Analytical Applications
9. Architecture Overview R/3 OLTP Applications OLTP Reporting Production Data Extractor Business Information Warehouse Server Business Explorer Analyzer (hosted by MS Excel) Browser Non R/3 Production Data Extractor Non R/3 OLTP Applications 3rd party OLAP client Data Manager InfoCubes Operational Data Store 3rd party OLAP client 3rd party OLAP clients Meta Data Manager Staging Engine Administrator Workbench Administration Scheduling Monitor OLAP Processor Meta Data Repository InfoCatalog OLE-DB for OLAP Provider Data Manager BAPI MDX
10. Staging Process Update Rules R/3 OLTP System Business Information Warehouse Server Source Systems Data extract Sales Europe R/3 standard extractor Transfer Structure Communication Structure Mapping & Transformation Rules Info Sources InfoCube Update Rules Non R/3 OLTP System Data extract Sales Americas 3rd party extraction tool Transfer Structure Update Rules Research Institute InfoCube Market Information Transfer Structure Communication Structure Mapping & Transformation Rules
11. DataSource and InfoSource Transfer Rules Update Rules InfoCubes Communication structure Transfer Structure Extract Source Structure Business Information Warehouse Server Staging Engine OLTP System 1 OLTP System 2 Extract Source Structure Transfer Structure Transfer Structure Transfer Structure Extract Source Structure Transfer Structure DataSource Transfer Structure InfoSource Transfer Rules Transfer Rules ( Replicated )
12.
13.
14. Persistent Staging Area OLTP System Business Information Warehouse Server InfoCube InfoSource InfoSource PSA Data extract Data extract Update Rules BAPI Validation
15.
16.
17.
18.
19.
20. BW Data Model InfoCube Time dimension T Period Fiscal year … 10 1997 ... Product dimension P Product # Product group … 2101004 displays ... Fact table C Customer # Region … 13970522 west ... Customer dimension P C T Quantity Revenue Discount Sales overhead 250 500,000 $ 50,000 $ 280,000 $ 50 100,000 $ 7,500 $ 60,000 $ … … … ... Customer # Name Location 13970522 Brightview, Inc. Palo Alto Master data
21.
22.
23.
24. InfoCube: Example Customer group Region Division Dept. Stores Wholesale Retail Glass- Ceramics Plastics Pottery Copper Pewter ware North South East
25. InfoCube: Multi-dimensional analysis 1 Region North South East Glass- ware Ceramics Customer group Division Retail Wholesale DeptStores Analysis of Ceramics division Analysis of Plastics division Analysis of Plastics division and Southern region Region North South East Glass- ware Ceramics Plastics Customer group Division Retail Wholesale DeptStores Region North South East Glass- ware Ceramics Plastics Customer group Division Retail Wholesale DeptStores 2 Region North South East Glass- ware Ceramics Plastics Customer group Division Retail Wholesale DeptStores 3 Product group Customer group Division Area Company code Region Period Profit Center Bus. Area Plastics Characteristics: Query Cache InfoCube
26.
27.
28.
29. Reporting Architecture Query OLAP server Database OLAP Processor operates on ... InfoCube stored in Aggregates Database stores ... Business Explorer Analyzer defines ... Star Schema
30. Reporting Architecture Query OLAP server Database OLAP Processor operates on ... InfoCube stored in Aggregates Database stores ... Business Explorer Analyzer defines ... Star Schema Business Explorer Analyzer shows ... Query View stored in Excel Workbook
Flexible set of ETL capabilities: a company can apply the various forms of ETL capabilities to its specific situations (flatfiles, DB connect, XML erläutern) Open to third party ETL-tools: ETL tool vendors have strength and weaknesses. We have build a tighter integration with Ascential Datastage, because many companies want an out-of-the-box integration with an ETL tool vendor. We have also packaged it. But all ETL tools have strength and weaknesses. Seamless, semantic integration to SAP applications. to provide the customer with a set of capabilities that he can tailor to his needs and situation To get a complete view of the business: information islands (not consolidated and linked to each other) can not provide a 360 degree view