Identify and Categorize Anomalies
From there, analyze the data and identify anomalies. This is where a data profiling tool can be indispensable. By profiling data, it's easy to reveal its content, quality and structure with minimal effort. Data profiling will also help you identify actual problems with the data as it relates to business needs. Categorize data quality into six data groups to make the results easily digestible for IT and business completeness, conformity, consistency, accuracy, duplication and integrity.
Find the Business Impact of Aberrations
After profiling the data and identifying anomalies, it becomes critical to work with decision-makers to understand the effect the anomalies will have on the business. Consider the following example. A profile of customer sales data shows that 8 percent of the records have inoperable or missing phone numbers. How does that impact the ability to up-sell or cross-sell your other line-of-business products to existing customers. Chances are, if business leaders knew at the start of the month that their sales force's operational ceiling would at best be 92 percent efficiency, there would be quite a bit of explaining to do to senior leadership.
State the Case for Data Quality
When stating the case for data quality, it pays to draw a link between how a lack of quality data can adversely affect the operational efficiency of an organization as well as the accuracy of business decisions. Now that the data has been compiled, analyzed, categorized and flagged for known anomalies, the case can effectively be made to increase data quality practices.