Data Cleanse

Data cleansing is the process of identifying and removing invalid contacts or amending records in a database to improve its overall performance. The most common reason for invalid contacts is the steady rate at which contacts leave jobs, move companies, and retire.

The ultimate goal of a data cleanse is to make sure your dataset is correctly formatted, deduplicated and is as accurate as possible. Clean data saves your organisation time and money, boosts employee trust in your systems, and improves your customers’ experience.

Data cleansing is important in order to have the most accurate, up-to-date, quality data. In the world of data science, there is the expression ‘garbage in, garbage out’; if the quality of the data you are using is sub-par, then the outcomes of its use will also be sub-par. Any data analysis will therefore be more difficult, less clear, and less accurate, as will any decisions based on that data analysis.   

By cleansing your data, you remove its deficiencies, replace inaccurate information, and add value. This improves your data’s overall quality and therefore the outcomes of its use. A data cleanse also makes your business better organised by tidying your database and improves productivity by saving time your team would otherwise take wading through old information to find what they’re looking for.