When performing data cleansing, what is the primary goal?

The primary goal of data cleansing is to correct errors and inaccuracies in data. This is crucial in ensuring that the data used for analysis, reporting, and decision-making is reliable and valid. Accurate data enhances the quality of insights derived from analysis, thereby supporting better business decisions. Data cleansing processes typically involve identifying and rectifying inconsistencies, duplication, missing values, and other irregularities, leading to a more accurate and meaningful data set.

This goal is essential in various domains, as clean data can significantly affect outcomes in fields such as finance, marketing, healthcare, and more. By focusing on correction, organizations can improve their operational efficiency and maintain higher standards of data integrity, which ultimately leads to more accurate analytics and reporting.

The other choices focus on different aspects of data management, such as organization (eliminating unnecessary files), security (enhancing data privacy), and user experience (improving interface design), but they do not address the core objective of data cleansing, which is about ensuring data accuracy and reliability.