{"id":118764,"date":"2023-04-18T11:53:30","date_gmt":"2023-04-18T11:53:30","guid":{"rendered":"https:\/\/businessyield.com\/?p=118764"},"modified":"2023-04-18T12:28:10","modified_gmt":"2023-04-18T12:28:10","slug":"data-cleansing","status":"publish","type":"post","link":"https:\/\/businessyield.com\/terms\/data-cleansing\/","title":{"rendered":"DATA CLEANSING: Best Practices For The Cleaning Process","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

The amount of data available to us has grown, as has the potential for error. As a result, we rely on data cleansing to improve the efficiency of our data management procedures. Data cleansing improves data quality and relevance by decreasing inconsistencies, eliminating errors, and allowing businesses to make accurate, educated decisions. In this post, you’ll learn the fundamentals of data cleansing, why it’s important for your business, and how to get started with a data cleansing process.<\/p>

What is Data Cleansing?<\/h2>

Data cleansing, also known as data scrubbing or cleaning, is the act of locating and removing errors, inconsistencies, duplications, and missing entries from data in order to improve data consistency and quality.<\/p>

While businesses can take proactive measures to ensure data quality throughout the collection stage, it can still be loud or unclean. This could be due to a variety of issues, including:<\/p>