It would not be hard to imagine how a daunting the task would of wanting to retrieve a data from the vast repository of data inside the data warehouse. The data warehouse is the main repository of all company data including historical data which may include those from several years past and the current transactional data which are being used in the present business operation. With today’s data driven business environment where information is might, it is not surprising to see how data could grow exponentially within a few hours.

Having filters in a data warehouse can greatly help in data management particularly in the area of data insertion and retrieval. Having filter is could be some sort of subdividing a large data warehouse into smaller sections for easy management. It should be noted that a data warehouse does not just store data.

It also shares data consumers, the business intelligence system and the many data sources which may be of disparate platforms resulting in having disparate data. Dealing alone with disparate in the process of extracting, transforming and loading (ETL) is already a labor intensive job for a data warehouse, how much more if there are simultaneous data retrievals with no filtering mechanism being employed.

Filters can be set by the data consumer during the time he wants to retrieve very specific information from the database. A data consumer querying the database may create and save as many filters as he wishes. For example, supposed a secretary was tasked by her boss to get the names and addresses of all companies that they have sold at least five hundred thousand dollars worth of goods during the last year and that during the last year, the number of companies that had been sold sums up to 1000.

The secretary would have to filter out the companies based on the criteria that it should have bought good of at least five hundred thousand dollars during the last year instead of getting the names of al 1000 clients and crossing out those which did not qualify. This mean a lot of time saved for the secretary. In fact, some filters can be done. For instance, the secretary might only want all the names of the companies that had purchased at least five hundred thousand dollars but the companies should fit into the category of having less than 20 employees.

Filtering can have many advantages. In statistical analysis, it would be near impossible to get good figures without having to employ filters on the database. In a large university data warehouse for instance, it would be a lot easier to know very specific information like how many students aged 20-23 are taking up a degree in mathematics; or how many students are coming from a family of an income bracket of $10,000 – $25,000 per year.

Filters belong to the most commonly used functions in databases and data warehouses. They make querying very fast and efficient and they can be configured to filter any set of data even up to the atomic level. Implementing a filter may vary in complexity depending on the kind of information being retrieved from the database.

Filter when used in database are usually inserted into structure query language (SQL) making the SQL statement even more complex with issued with several filters. But with today’s increased use of graphical software applications, dealing with SQL and filters have become a lot easy. With a few clicks or entering of data in the text boxes, it would be fast and easy to retrieve specific filtered information.