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:
And because rules and needs change and new systems can be added to the mix, truly successful data quality initiatives need to be scalable to address those new requirements.
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:
We’ve pioneered the categories of data integration and data quality since 1993 and offer a full suite of data quality and data enrichment—or Data as a Service (DaaS)—products that ensures consistent quality throughout data’s lifecycle—as it enters your systems, is analyzed mid-stream, and when it’s stored or archived—on premise, in the cloud, or on Hadoop.