Dan[at]DQMatters.com
Dan Myers is Principal Information Quality Educator of DQMatters.com, his own company, focused on providing consulting, on-site training and Web-based eLearning materials. Dan is based in the Silicon Valley; primarily serving clients on the West Coast of the USA. Previously, Dan has worked as an applications developer, data modeler, and manager of data governance/data quality. Dan is a frequent speaker at various data management and business conferences both in the US and abroad.
After attending a number of data management conferences, where Dan heard a number of professionals use terms such as Integrity, Accuracy and Currency/Timeliness to mean different things, he began to look for a detailed and agreed-upon standard set of definitions for the dimensions of data quality. What he found was a few great academic studies on the topic that have proposed a list of dimensions1, a series of author’s lists2, and a few sets of dimensions documented by professional organizations3. What he discovered was that no two sets of dimensions were in agreement on what should be included within a set of dimensions and most lacked complete and verbose descriptions. So, in 2013, he wrote a series of six articles reviewing four authors and two organization’s list of the dimensions of data quality. This effort did reveal similarity in some areas, (e.g. Completeness and Validity) and the need for a conformed version that brings together the best of each. In 2016, Dan enhanced the conclusions made during the prior work in 2013 and published a proposed set of Conformed Dimensions of Data Quality (CDDQ) on this website for others to use, leverage during future research/study, and most importantly use on a day-to-day basis to communicate data quality issues. Since the release in 2016, Dan has presented on this topic at conferences in the USA and Japan and at companies in the USA. Dan also conducts an annual survey on the topic of the dimensions of data quality in order to foster further development and understanding.
Notes:
1. Wang and Strong (1996), Batini et.al. (2009), For a more complete list see http://dimensionsofdataquality.com/research
2. English (1999 and 2001), Redman (1996 and 2001), McGrilvray (2008), Loshin (2009), Lee/Papino/Funk/Wang (2006)
3. Data Administration and Management Association (DAMA) DMBOK (2009), TDWI- Data Quality Fundamentals (2011)
"For the data industry, standardized definitions of data quality dimensions are needed, just as other professions, such as accounting have agreed-upon concepts and terms like “chart of accounts”." --Danette McGilvray, Granite Falls Consulting
