Data scrubbing, also known as data cleansing, is the process of changing or removing data in a database that is incorrect, incomplete, improperly formatted, or duplicated. Data scrubbing focuses on cleaning up data by making it more consistent and accurate.
All organizations deal with data, so scrubbing can be useful for a variety of industries. However, certain data-intensive fields may find it particularly beneficial such as banking, insurance, retailing, and telecommunications.
Database errors are prevalent for a variety of reasons. They typically result from human error in entering the data, merging of databases, a lack of company-wide or industry-wide data standards, or old systems that contain outdated data. Before technology had the capability and sophistication to sort and cleanse data, data scrubbing was done by hand. Not only was this time consuming and expensive, but it oftentimes led to even more human error.
This created the need and subsequent emergence of data scrubbing tools, which systematically examine data for flaws by using rules, algorithms, and lookup tables. However, a better alternative is today’s cloud-based solutions that work in real-time. As opposed to on-premise data scrubbing tools, cloud solutions can capture and cleanse data on the front-end. This saves a database administrator a significant amount of time and resources. It is less costly to correct from the get-go than fixing errors manually on the back-end.
While small errors may seem like a trivial problem, merging corrupt or erroneous data causes the problem to be magnified and exponentially troublesome. It is so burdensome that it is affectionately called the “dirty data” problem, which has existed for as long as there have been computers. Experts argue that the dirty data problem costs companies from millions to trillions of dollars each year. The problem is becoming increasingly critical as businesses are becoming more complex with more data and systems. There is no point in having a comprehensive database if that database is filled with errors and inaccuracies.
Look for a vendor like StrikeIron that offers cloud-based data quality solutions, not software, that go through a process of using algorithms to standardize, correct, match, and consolidate data.
Data scrubbing is sometimes skipped as part of a data warehouse or MDM project, but it is one of the most critical steps to having a good, accurate end-product. Since mistakes will always be made in data entry, the need for data scrubbing will always be present. Therefore, implement a cloud solution that can easily adapt as your company evolves and grows with time.