BACKGROUND IMAGE: iSTOCK/GETTY IMAGES
data scrubbing (data cleansing)
Data scrubbing, also called data cleansing, is the process of amending or removing data in a database that is incorrect, incomplete, improperly formatted, or duplicated. An organization in a data-intensive field like banking, insurance, retailing, telecommunications, or transportation might use a data scrubbing tool to systematically examine data for flaws by using rules, algorithms, and look-up tables. Typically, a database scrubbing tool includes programs that are capable of correcting a number of specific type of mistakes, such as adding missing zip codes or finding duplicate records. Using a data scrubbing tool can save a database administrator a significant amount of time and can be less costly than fixing errors manually.
Machine Learning Meets Data Quality
Read an exclusive interview with Andrew Burt, chief privacy offer and legal engineer at Immuta Inc., on data governance and machine learning integration. Plus, uncover steps IT managers are taking to improve data quality in their big data environments in order to ensure analytics accuracy.
IBM, HP, Symantec, Dataladder etc.