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Explain Data Warehousing

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Introduction
Data warehousing acts as a great facility for the various users, as it consists of some tools that are very effective in the storage of the summarized information from multiple, heterogeneous databases in a single repository. In today’s corporate world, the organizations are able to generate data in a very large amount during the day to day business activities. This data acts as a very strong plus point for an organization but only if this data is able to provide very good information and is not just a collection of data. In such a scenario, where it is required to get valuable and important material extracted from a collection of data, data warehousing play a very essential and crucial role.

W.H Inmon is considered as the “father of data warehousing” and according to him data warehouse ‘is a subject – oriented, integrated, time – varying, non – volatile collection of data in support of the management’s decision making processes.’

Evolution of Data Warehousing
A typical data warehouse, in the starting evolves as a very large database (VLDBs) – consisting of data records in a very large amount. As a process, this technology develops gradually within an enterprise and the longer a data warehouse is used, the more it evolves. In the beginning, data warehousing was generally used in the processes like generation of reports, answering predefined queries etc. but now data warehouse finds its use not only in these operations but also in the analyzation of the data.

Then in the next step or phase, data warehouse found its use in the various strategic activities – helping in performing the multi dimensional analyzation along with the “slice and dice operations”. Then after this step, data warehouse was used in the processes like the discovery of knowledge, strategic decision making etc.

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The various categories of data warehousing tools can be summarized as –
1. Access tools.
2. Retrieval tools.
3. Database reporting tools.
4. Data analysis tools.
5. Data mining tools.

Role of a Data Warehouse
1. Provides tools which help in satisfying the needs for information of any organization.
2. Helps in integration of data from different sources.
3. Helps in the improvement of the optimization efforts via consolidation, conversion etc.
4. Helps in the storage of summarized information in a single repository.
5. Allows creation of enterprise wise integrated database of summarized information and hence acts as a critical supporting factor in decision making processes.
6. Data Warehousing helps in saving the time and also provides better improved information by supporting good and better decisions.
Development of the Data Warehouse (mistakes to be avoided)
During the implementation of the data warehousing in a successful manner it is very important to avoid committing certain factors or mistakes, which in turn helps in the proper development of the data warehouse.

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The various data warehousing mistakes which should be avoided can be summarized as follows –
1. Use of an untrained or an inexperienced person.
2. Poor design.
3. Uncleaned data.
4. Wrong approach of working.
5. Working on expectations.
6. Non implementation of the Meta Data strategy.
7. Non deployment of the central warehouse administrative tool.

This article has been written by KJ Singh a MBA Graduate from a prestigious Business School In India
Article Published:August 4, 2010

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