When it comes to data quality, how good is good enough

The hallmark of data quality is how well data supports the context in which it’s consumed. Your legal department, for example, may use “Informatica Company” while your finance department uses “INFA,” and both records are of equal quality.

Quality is a relative and never-ending judgment, one that needs to be defined by the business (or business unit) that’s consuming the data. An essential element of holistic data governance, trustworthy data serves critical business needs across the enterprise—from legal to finance to marketing and beyond.

Driving data quality requires a repeatable process that includes:

Bad data cost U.S. business $600 billion a year, according to the research firm TDWI.

Why data quality matters

Why does quality data matter? An often-cited statistic puts the cost of “bad” data to U.S. businesses at $600 billion annually1. Whether bad data causes you to lose revenue, damages your brand, reduces your competitive edge, or simply results in bad decision-making, the costs are significant.

When looking for a data quality solution, we recommend you put the following at the top of your “must-haves” list: