We could talk all day about the giant puzzle created by dirty data. But to master the data quality domino game, it’s more important to focus on stopping the data dominoes from falling and blocking future issues so you don’t get buried under a pile of bad data.

Based on more than a decade of experience in working together with hundreds of top firms on CRM and data quality projects, here are some top tips to help you identify data quality issues and prevent future problems.

1. Assess: Start by stepping back from the never-ending data deluge and take a minute to assess the mess and come up with answers to a few important questions that can help you to scope the situation:

How much bad data do we have?
Where is it located?
How did it get there?
Who is in charge of it?
What is it costing us?
What is the best way to clean it up?
Who will assist with cleanup?
How long will the cleanup take?
How much will the cleanup cost?