Data Warehousing and SAP BW

enerally, 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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