Self-service analytics solutions often quickly expose data quality issues that you may not even realize exist.
Unfortunately, inaccurate data undermines the value of analytics. If people don't trust your reports, they won’t use them.
Since self-service analytics credibility, adoption and success hinges on accurate data, data quality should be given more attention as you implement these solutions. Please join me in this informative session to learn how to address common data quality issues. We will cover practical recommendations, review top data quality solutions, and share additional lessons learned.
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