Which process involves ensuring that data is devoid of errors and accurate?

The process that ensures data is devoid of errors and accurate is data validation. This integral step involves a set of checks and tests performed on the data to confirm its correctness, completeness, and quality before it is used for analysis or operational purposes. Data validation may include verifying the format, range, and integrity of data values, ensuring that they comply with certain rules or criteria. For instance, a system might check that dates are in the correct format, numeric values fall within expected ranges, or mandatory fields are not left blank.

This process is crucial in the context of database management and GIS applications, as inaccurate or erroneous data can lead to poor decision-making and unreliable analytical results. By validating data before it enters the system or is processed further, organizations can maintain high data quality standards, which is essential for effective mapping, geographic analysis, and overall information reliability.

In contrast, the other processes involve different aspects of data handling. Data transformation pertains to changing the format or structure of data to fit a particular model or system. Data integration is the process of combining data from different sources into a unified view. Data mapping refers to associating data elements from one data model or structure to another. Each of these processes has its importance, but none focus primarily on