What are the best practices for media data quality and governance?

2 Establish data quality criteria

Data quality is not a one-size-fits-all concept. It depends on the context and purpose of the data. Therefore, you need to establish data quality criteria that suit your specific media data needs. Some common data quality dimensions include accuracy, completeness, consistency, timeliness, validity, and relevance. For each dimension, you need to define the expected level of quality, the methods of measurement, and the actions to take if the quality is compromised.

4 Assign data roles and responsibilities

Data governance is not only about policies and standards, but also about people and culture. You need to assign data roles and responsibilities to the stakeholders who are involved in the media data lifecycle, such as data owners, data stewards, data analysts, data consumers, and data providers. Each role should have a clear definition of its scope, authority, and accountability for the data. By assigning data roles and responsibilities, you can ensure that the data is properly managed and used according to the data governance framework.

5 Communicate and document data policies and standards

Data policies and standards are the rules and guidelines that govern how the media data is collected, stored, accessed, shared, and used across the organization. They should align with the media objectives, data needs, and data quality criteria. Data policies and standards should be communicated and documented clearly and consistently, so that everyone understands and follows them. They should also be reviewed and updated regularly, to reflect the changes in the media environment, data sources, and data requirements.

6 Monitor and evaluate data quality and governance

Data quality and governance are not static or one-time activities. They require ongoing monitoring and evaluation, to ensure that they are effective and efficient. You need to measure and report on the key indicators of data quality and governance, such as data completeness, accuracy, consistency, timeliness, validity, relevance, compliance, and satisfaction. You also need to identify and address any gaps, issues, or risks that may affect your media data quality and governance. By monitoring and evaluating data quality and governance, you can continuously improve your media data capabilities and outcomes.