How to Improve Your Data Quality
The article outlines 12 actions companies can take to improve their data quality, with some commentary for each action and nuggets like “a 10% improvement in customer DQ can be linked to a 5% improvement in customer responsiveness quoted”.
No. 1: Establish how improved data quality impacts business decisions
No. 2: Define what is a “good enough” standard of data
No. 3: Establish a DQ standard across the organization
No. 4: Use data profiling early and often
No. 5: Design and implement DQ dashboards for monitoring critical data assets, such as master data
No. 6: Move from a truth-based semantic model to a trust-based semantic model.
No. 7: Include DQ as an agenda item at D&A governance board meetings
No. 8: Establish DQ responsibilities and operating procedures as part of the data steward role
No. 9: Establish a special interest group for DQ across BUs and IT, led by the chief data officer team or equivalent body
No. 10: Establish a DQ review as a release management “stage gate”
No. 11: Communicate the benefits of better DQ regularly to business departments
No. 12: Leverage external/industry peer groups, such as user groups from vendors, service providers and other established forums
Why it’s relevant to Nextspace
Apart from the 12 actions, the article is of interest to Nextspace Partners as Gartner makes the case that poor data quality costs organizations an average $12.9 million. Apart from the immediate impact on revenue - over the long term poor quality data increases the complexity of data ecosystems and leads to poor decision making. The emphasis on data quality in enterprise systems has increased as organizations increasingly use data analytics to help drive business decisions.
Gartner predicts that by 2022,70% of organizations will rigorously track data quality levels via metrics improving it by 60% to significantly reduce operational risks and costs. “Data quality is directly linked to the quality of decision making,” says Melody Chien, Senior Director Analyst, Gartner.
