Data Warehousing and SAP BW

The basic criteria for the formation of data warehousing is to scrutinize data from diverse sources while taking decision-making. The objective of data warehousing is to scrutinize data from diverse sources to support decision making.

Poor Performance

Generally, data warehouse refers to storage of numerous data in it. It is not a quick process to retrieve data from the data warehouse for analysis purposes. To scrutinize the data, this data warehouse design uses a special process known as star schema. One finds difficult while extracting, transferring, transforming and loading data from diverse sources into a data warehouse. The Data must be analyzed properly before using. For the failures of many data warehousing projects ETTL has been frequently quoted. You also realize the problem if you started analyzing the data without SAP BW.

Today in large companies, SAP R/3 is used for management purposes. This SAP R/3 which is an enterprise resources planning system which is used business purposes. Before the introduction of the SAP BW, SAP R/3 was mainly used by the data warehouse. SAP BW is a business information warehouse which explains the needs of the business development. To mark your success in the market competition, you have to complete with the up-to-date development of your business environment. These challenges enable the business to take an appropriate decision with the available data. This decision enables you to make many successes in your business life.

Basic Concept of Data Warehousing

Data warehouse is a system, which contains its own database. This data warehouse collects data from various sources and it is planned to support while research has been taken place. For the purpose of analytical processing a special database technique called star schema is used.

Star Schema

Star schema is a new technique that is used by the business people for few years. This star schema has various concepts in it. Star schema is used for the data base by the following method.

This star schema is a graphical version. The name has been derived since it looks like a star. The table looks like a several dimension table. Since the table is very large, it is measured in the gigabyte. This table ensure with enormous useful data. The dimension table size will amount to 1 to 5 percent of the actual table size. This table does not require any normalization.

ETTL—Extracting, Transferring, Transforming, and Loading Data

One finds difficult while designing database, because building a data warehouse involve a significant task that do not arise OLTP system. It is difficult to extract, transform, transfer and load the data from the diverse source to data warehouse.

ETTL Process

1. While extracting the data, data has been transferred from the source system such as sap R/3 system. The purpose of this extraction is to identify the right data. A knowledgeable source system is essential for absolute accomplishment.
2. In transfer, we transfer a large number of data from different source systems to the data warehouse. Here the purpose is to plan a reasonable schedule and should have reliable and fast networks.
3. In data transformation, we design data to represent consistently in the data warehouse. The original data which exist in different databases may use different data types or different file formats. Some are case sensitive; others may not be.
4. In loading, we load data the actual tables appropriately and quickly. The purpose is to develop a complete procedure.

This ETTL is a complex and time-consuming task. Any error in it will put in to a risk at data quality, will affect business decision making. Due to this reason many data warehousing projects will try to complete their work in time. SAP R/3 is a good business functionality which leads to a complex database. Actually, it contains approximately 10,000 database tables. Sometimes the tables and columns may not have precise English descriptions. For years, due to the usage of SAP R/3 data for decision making, the business people face a continuous problem. After short listing the problem, SAP decided to develop a new data warehousing solution to help its users. The result they found is SAP Business Information Warehouse, or BW.

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SAP Data Warehousing Solution

SAP BW is a continuous data warehousing solution that uses former SAP technologies. This SAP BW is built on the Basis of 3-tier architecture and coded in the ABAP (Advanced Business Application Programming) language. This 3-tier architecture and code language uses ALE (Application Link Enabling) and BAPI (Business Application Programming Interface) to link BW with SAP systems and non-SAP systems.

BW Architecture The BW has three layers in it. The top layer is the reporting layer. This top layer may be BW Business Explorer (BEx) or a third-party reporting device. This BEx consists of two components: one is BEx Analyzer and other is BEx Browser.

BW Server is a middle layer that carries out three tasks: it administrates the BW system, stores data and retrieves the data. In The bottom layer it consists of source systems, which may be R/3 systems, BW systems, flat files, and other systems. In the source systems a SAP component called Plug-In must be installed. It contains extractors. An extractor is a set of ABAP programs, database tables, and other objects that BW uses, which helps to extract data from the SAP systems. This BW Server contain Administrator Workbench, Metadata Repository and Metadata Manager, Staging Engine, PSA, ODS and User Roles.

• This Administrator Workbench checks metadata and all BW objects. It has two components: one is BW Scheduler and other is BW Monitor. This component helps to load data and to monitor the data.

• This Metadata Repository contains information relating to data warehouse. Metadata Repository contains two types one is business-related and other is technical. Metadata Manager is used to maintain Metadata Repository.

• PSA (Persistent Staging Area) is also a BW server. This PSA stores data in the original format while being imported from the source system. It ensures quality check of data before they are loaded in their destinations, such as ODS Objects or Info Cubes.

• This ODS (Operational Data Store) Objects helps to build a multilayer structure for operational data reporting. It is used for detail reporting.
• Info Cubes is an actual table and they are the associated dimension tables in a star schema.

• The OLAP Processor is the analytical processing engine. It analyzes and retrieves data as per users' requests.
• Documents are stored in BDS (Business Document Services). The documents can appear in different formats like Microsoft Word, Excel, PowerPoint, PDF, and HTML.

BW Business Content The BW's most powerful selling is Business Content. It contains standard reports and other associated objects. For standard reports, BW use a function called Generic Data Extraction. This function is used to extract R/3 data.

Nowadays, BW is rapidly evolving. It helps to plan BW projects and their scopes.

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Ron Victor is a SEO copywriter for SAP Company . He written many articles in various topics in SAP Articles and SAP Training. For more information about sap information visit SAP Forums .Contact him at ron.seocopywriter@gmail.com