True or False: Data cleaning improves the quality and accuracy of data by removing errors.

Data cleaning is indeed a crucial process that enhances the quality and accuracy of data by identifying and removing errors, inconsistencies, and inaccuracies within datasets. This process often involves correcting spelling mistakes, eliminating duplicate entries, filling in missing values, and ensuring that the data is in a consistent format. By addressing these issues, data cleaning improves the reliability and validity of the information, which is essential for effective analysis and decision-making.

In many organizations, clean data facilitates better insights, enhances customer relationships, and optimizes operations. Considering the significance of accurate data, the assertion that data cleaning improves quality and accuracy by removing errors is entirely accurate. This foundational step in data management is vital across various applications and industries, making it a universally effective strategy rather than being limited to specific datasets or just data preparation.