Data is always important to your business, but correct data in invaluable to your enterprise. Data quality metrics are instrumental in gauging the overall health of an enterprise. Poor data quality impacts your resources, morale, productivity, compliance, customer retention, and your bottom line. Evaluating data quality and moving to a proactive capability requires thoughtful data quality metrics. Improving data fitness requires using short and repeatable processes, along with a thoughtful set of metrics, to measure progress.
Ultimately, an enterprise strives to implement an integrated platform with consistent, timely, and accurate data. Determining if you have quality data is important in that process. This is how you measure data fitness.
You and your data experts will need to analyze the data elements used in your enterprise to determine different levels of data fitness. The final results should include rough order of magnitude cost estimates to help prioritize next steps and additional work required to correct any identified issues.
Once the various data elements have been identified, verified, and remediated your business can rely on the data and stop questioning if the data is correct and instead focus on addressing business issues with confidence.