Part 3/9:
One of the key takeaways was the importance of raising our voices about data quality issues. Often, organizations overlook problems like bad data, but if left unaddressed, they diminish the reliability of insights and decision-making.
The speaker highlighted real-world examples—such as inaccuracies in customer details, outdated records, or inconsistent data across platforms—that create confusion and inefficiency. For instance, discrepancies in customer names or addresses expand back to broader operational problems, affecting customer experience and strategic planning.
The point was made clear: data quality is everyone’s responsibility — from data generators to analysts and leadership.