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Data scrubbing is the process of finding and correcting errors in a database, which can be caused by human error, merging databases, or outdated data. Specialized software can be used to cleanse the information, but it requires customization and can be expensive. Skipping this step can lead to inaccurate data in a data warehouse.
Data scrubbing, sometimes called data scrubbing, is the process of finding and removing or correcting any information in a database that has some sort of error. This error may be due to the fact that the data is incorrect, incomplete, incorrectly formatted, or is a duplicate copy of another entry. Many data-intensive business sectors such as banking, insurance, retail, transportation, and telecommunications can use these sophisticated software applications to cleanse information from a database.
Database errors can be the result of human data entry errors, two databases merging, lack of company or industry data coding standards, or due to old systems containing inaccurate or outdated data. Before computers had the ability to sort and clean data, most cleanups were done manually. Not only was this time consuming and expensive, but it often led to even greater human error.
The need for data scrubbing is made clear when one considers how easily mistakes can be made. For example, in a database of names and addresses, one name might be BobJohnson of Needham, MA, while another is Bob Johnson of Needham, MA. This variation of names is most likely a mistake and refers to a person. However, normally a computer would treat the information as if it were two different people. Specialized data cleansing software can distinguish the discrepancy and fix it.
While these small errors may seem like a trivial problem, when you merge corrupt or incorrect data across multiple databases, the problem can be multiplied by millions. This so-called “dirty data” has been a problem since there have been computers, but it is becoming more critical as businesses become more complex and data warehouses are merging data from multiple sources. It makes no sense to have a complete database if that database is full of errors and controversial information.
Companies using specialized software can either develop it in-house or purchase it from a variety of vendors. The software is not cheap and can range in price from $20,000 to $300,000 US Dollars (USD). It also often requires some customization so that the software works according to the specific needs of the company. Goes through a process of using algorithms to standardize, correct, match and consolidate data and is able to work with one or more datasets.
Data scrubbing is sometimes skipped as part of a data warehouse implementation, but it is one of the most critical steps in having a good and accurate end product. Since errors will always be made when entering data, this process will always be necessary.
