What term describes the procedures put in place to ensure data accuracy and validity within a company?

The term that best describes the procedures established to ensure data accuracy and validity within a company is "data quality assurance." This concept encompasses the processes, policies, and methodologies that are employed to maintain the integrity of data across its lifecycle.

Data quality assurance is focused specifically on verifying that the data used in operational and analytical processes meets defined standards of quality. This includes measures such as data validation, data cleansing, and regular audits, all aimed at minimizing errors and ensuring that the data is both reliable and valid.

While data governance relates to the overall management of data within an organization, including policies for compliance and responsibilities, it does not solely focus on the accuracy and validity of the data itself. Data management is a broader term that involves the practices for collecting, storing, and utilizing data, but it encompasses more than just the measures for ensuring quality. Data analysis, on the other hand, refers to the techniques used to interpret and derive insights from data, which does not directly involve the mechanisms to ensure data quality.

Thus, in the context of ensuring data accuracy and validity, data quality assurance is the most accurate descriptor for the procedures involved.