Introduction to Data Warehouse

The term "Data Warehouse" was first coined by Bill Inmon in 1990. Accordingly Dw is

“A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process.”

·         A data warehouse is a database, which is kept separate from the organization's operational database.

·         There is no frequent updating done in a data warehouse.

·         It possesses consolidated historical data, which helps the organization to analyze its business.

·         A data warehouse helps executives to organize, understand, and use their data to take strategic decisions.

·         Data warehouse systems help in the integration of diversity of application systems.

·         A data warehouse system helps in consolidated historical data analysis.

An Environment, Not a Product

A data warehouse is not a single software or hardware product you purchase to provide

strategic information. It is, rather, a computing environment where users can find strategic

information, an environment where users are put directly in touch with the data they need

to make better decisions. It is a user-centric environment.

• ·         An ideal environment for data analysis and decision support
• ·         Fluid, flexible, and interactive
• ·         100 percent user-driven
• ·         Very responsive and conducive to the ask–answer–ask–again pattern
• ·         Provides the ability to discover answers to complex, unpredictable questions

CHARACTERS of DW

• ·       Subject-Oriented: A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject.
• ·       Integrated: A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product.
• ·      Time-Variant: Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse. This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a data warehouse can hold all addresses associated with a customer.
• ·    Non-volatile: Once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered.

Types of Data Warehouse

Information processing, analytical processing, and data mining are the three types of data warehouse applications that are discussed below:

•       Information Processing - A data warehouse allows to process the data stored in it. The data can be processed by means of querying, basic statistical analysis, reporting using crosstabs, tables, charts, or graphs.
• ·  Analytical Processing - A data warehouse supports analytical processing of the information stored in it. The data can be analyzed by means of basic OLAP operations, including slice-and-dice, drill down, drill up, and pivoting.
• ·  Data Mining - Data mining supports knowledge discovery by finding hidden patterns and associations, constructing analytical models, performing classification and prediction. These mining results can be presented using the visualization tools.

Need for Data Warehouse

·         Provides an integrated and total view of the enterprise

·         Makes the enterprise’s current and historical information easily available for decision making

·         Makes decision-support transactions possible without hindering operational systems

·         Renders the organization’s information consistent

·         Presents a flexible and interactive source of strategic information

Advantages of DW

Retail

 Customer Loyalty

 Market Planning

Financial

 Risk Management

 Fraud Detection

Airlines

 Route Profitability

 Yield Management

Manufacturing

 Cost Reduction

 Logistics Management

Utilities

 Asset Management

 Resource Management

Government

 Manpower Planning

 Cost Control