For many marketing teams, a little bit of data is not enough, according to ClickZ. The big data revolution led many analytics adopters to harp on tactics focusing on speed and size, but this strategy may not generate the results they are hoping to see. Taking too large of a scope can sometimes cause data scientists to lose sight of the details close up, and ultimately sacrifice data quality.
As stewards of customer data, marketing firms must always ensure they are adhering to governance plans and keeping data clean, the source adds.
In an recent podcast for the Obsessive-Compulsive Data Quality blog, Jim Harris explains the importance of housing trustworthy data for smarter business intelligence. He states that the purpose of data warehousing is to deliver reliable information in a timely fashion, but the information plucked from these systems must be checked for data quality or it could relay misleading insights.
Big data adopters are warned not to cherry pick information blindly from these locations, assuming the content is valuable insight, Harris adds. Companies must build databases that are transparent like glass houses, which reveal quality issues that exist so they can be addressed before larger issues occur.