There are data quality issues where the cause and remedy are obvious. For instance, users are fat-fingering data entry tasks so you need to implement a drop-down selection list. Or ETL loads are misfiring so you need to industrialize ETL monitoring. Or key metrics yield conflicting results so you need a standardized definition and calculation.

Then, there are other data quality issues that are just.... nasty. The cause is not obvious - it might be a combination of outdated systems, poor internal processes, or synchronization issues with external providers. It might take an army of people to track down root causes and build new processes and validations to improve data quality and consistency.

In this webinar, our consultants will explore how to deal with the nastiest, gnarliest, and most pernicious data quality issues. And we'll tackle your use cases and do some real-time problem-solving! So bring your worst data nightmares and let's have some fun!