3 of 7

Write now Article Tools

If you hear the phrase "data warehouse" does it conjure up visions of a large room filled with rows of computers spitting out ticker tapes chock full of information? If so you are not alone. A common perception is these computers produce tons of paper which falls into piles to be sorted through and compiled.

Although this visualization is not exactly correct, theoretically it's not far off because

data warehousing is a method used to collect and store massive amounts of data. Data warehousing is a compilation of information, but without the paper mess. Housing vast amounts of data is a highly implemented procedure used in many organizations today.

What is data warehousing?

By definition a warehouse is a large storage facility. In the case of data warehousing it is a database comprised of a collection of information extracted from numerous other databases and stored in one storage area. It is a specialized database which is maintained separately from regular transaction processing; instead its job is to collect read-only "snapshots" of data to collect histories of transactions instead of accepting concurrent and continuous updates. The data warehouse is also fed data from many sources, including both internal and external resources, making it an integrated repository of data.

Why is data warehousing useful?

Data mining software, which are automated tools that search for hidden patterns, are typically used in conjunction with data warehousing. The information extracted from data mining is useful in making predictions (i.e. customer buying habits). Online Analytical processing (OLAP) are software tools utilized with data mining that help simplify analyzing and are specially designed to support this specialized process.

The data warehousing process aids in managerial decision making. Since it's heavily indexed, it allows the database to easily and rapidly retrieve information to be analyzed. Many organizations find housing data is a vital and useful way to evaluate statistical information which enables well-informed decisions to be made.

It is a valuable asset for many reasons; it allocates rapid retrieval of data, has high performance, and completes thorough processes such as data cleansing. All this works to ensure there is an optimal level of data integrity. Cleansing data means to "clean" the data of any inconsistencies and ensure accuracy. This process entails making sure all of the data is formatted the same, and this results in lower redundancy and higher precision.

• 1
• 2
• next page >>

Add your voice

Know something about A guide to data warehousing?
We want to hear your view. Write now!