Data Scrubbing

What is Data Scrubbing?

If in the course of doing household chores, someone told you to clean the floor, you most likely grabbed a broom, swept the floor, then maybe ran a damp mop over it. But if that same person tells you to scrub the floor, then you will be down on your hands and knees with a scrub brush and bucket of hot soapy water and putting a major effort in cleaning. The word “scrub” implies a more intense level of cleaning, and it fits perfectly in the world of data maintenance.

Techopedia?defines data scrubbing as “…the procedure of modifying or removing incomplete, incorrect, inaccurately formatted, or repeated data in a database.” The procedure improves the data’s consistency, accuracy, and reliability.

What is Data Cleaning, and is it the Same Thing?

Although many sources use the phrases “data scrubbing” and “data cleaning” interchangeably, that’s not accurate.

Data cleaning, also called data cleansing, is a less involved process of tidying up your data, mostly involving correcting or deleting obsolete, redundant, corrupt, poorly formatted, or inconsistent data. Data professionals do the actual cleaning, checking the database and making corrections and edits as needed, and practicing good data entry habits.

Consider data scrubbing as a subset of data cleaning. Data scrubbing employs actual tools to do a much “deeper clean” than just having a user pore over database spreadsheets and making corrections. Here’s a glance at how you should clean your data, and how scrubbing fits into the timeline.

Scrub Duplicates from Your Database

• Use data scrubbing tools to search and remove redundant information, a condition that usually occurs when users must merge two different databases

Have the Data Analyzed

• Once your data has been cleaned and scrubbed, make sure it is following all regulations and standards. If possible, use a third-party for data tool for verification