WHY DATA WAREHOUSE?

WHY DATA WAREHOUSE?

You wish to achieve the goals of your company. You want to know your (potential) clients, their demands and needs. Furthermore you want to know your present and future competitors, and what they are doing to meet your clients needs.

Having established your goals, you want to monitor them, in order to determine to what extent they are being achieved.

You do suspect that the management information you need is available somewhere within your company, but you don’t know where. When you ask your analysts, they come up with different results.

In Decision Making, managers  have a big business need for timely management information. It is vital to have a proper structure in the whole compilation of data within your company. In many organizations however, the current structure blocks effective and efficient use of existing data. Most problems are caused by the fact that the required information is stored in different systems, using different definitions or different formats. This frustrates a consistent overall view on how your company is doing.

The creation of an integrated source of data may enhance the performance of your decision support system, being specifically designed to provide information in support of the decision making process, business wide analysis and performance monitoring. This is what we call a data warehouse.

Characteristics of a Data Warehouse:  

• Subject Oriented: data is organized around the subjects of interest to managers, such as clients, markets, products, suppliers, etc.
• Integrated: data from different sources is harmonized and uniquely coded;
• Time Dependent: all data is stored together with a date/time stamp;
• Consistent: data is uniquely defined, its description (location, meaning, ownership) is stored in a metabase;
• Nonvolatile and Historical Integrity: data is periodically refreshed, re-aggregated as required, but in principle not changed.

By means of a data warehouse, it helps making available the information you need.

The Benefits of a Data Warehouse: 

• Data derived from different sources can be retrieved in an integrated fashion;
• Due to the subject oriented design, data can be approached from (a combination of) different angles or dimensions, enabling multidimensional analysis.
• Reports are reliable and verifiable: you are able to search through the metabase to determine the source of the data and the rules which were used to produce it;
• Analyses produced in different parts of the organization are consistent and are reproducible;
• The number of interfaces to be maintained between transaction processing systems and decision support systems is minimal;
• Due to the fact that historical data is maintained, it becomes possible to carry out analyses over periods of time and to do datamining;
• Because transaction processing systems are separate from the data warehouse, it becomes possible to perform complex analyses without affecting the performance of these systems

Data Warehouse Architecture

SOURCE:http://www.breteler.com/DWH.htm