Data Cleansing

Data Cleansing is the process of identifying, correcting or removing corrupt, inaccurate, duplicated, irrelevant parts of data within a dataset. Coursera's data cleansing catalogue teaches you to enhance data quality, reliability, and longevity while minimizing the risk of errors and improper decision-making. You'll learn about various data cleansing techniques such as data auditing, workflow specification, data transformation, data reconciliation, and much more. You'll gain proficiency in leveraging tools and software to detect and rectify data inconsistencies, thus enabling you to take your first step towards becoming a data analyst, data scientist, or data manager.