Run data quality checks by manually inspecting each user engagement and identifying fake engagements.

Use AWS Glue to run data quality checks by writing custom scripts that identify fake engagements based on specific patterns or anomalies.

Define data quality rules using AWS Glue DataBrew by creating a new project, selecting the user engagement dataset, and specifying rules to identify and filter out fake engagements.

Ignore data quality checks and assume all user engagements are genuine.