The Best Data Quality Blog Posts of 2010

This year-end review provides summaries of and links to The Best Data Quality Blog Posts of 2010.  Please note the following:

  • For simplicity, “Data Quality” also includes Data Governance, Master Data Management, and Business Intelligence
  • Intentionally excluded from consideration were my best blog posts of the year — not counting that shameless plug :-)
  • The Data Roundtable was also excluded since I already published a series about its best 2010 blog posts (see links below)
  • Selection was based on a pseudo-scientific, quasi-statistical, and proprietary algorithm (i.e., I just picked the ones I liked)
  • Ordering is based on a pseudo-scientific, quasi-statistical, and proprietary algorithm (i.e., no particular order whatsoever)


The Best Data Quality Blog Posts of 2010

  • Data Quality is a DATA issue by Graham Rhind – Expounds on the common discussion about whether data quality is a business issue or a technical issue by explaining that although it can sometimes be either or both, it’s always a data issue.
  • Bad word?: Data Owner by Henrik Liliendahl Sørensen – Examines how the common data quality terms “data owner” and “data ownership” are used, whether they are truly useful, and generated an excellent comment discussion about ownership.
  • Predictably Poor MetaData Quality by Beth Breidenbach – Examines whether data quality and metadata quality issues stem from the same root source—human behavior, which is also the solution to these issues since technology doesn’t cause or solve these challenges, but rather, it’s a tool that exacerbates or aids human behavior in either direction.
  • WANTED: Data Quality Change Agents by Dylan Jones – Explains the key traits required of all data quality change agents, including a positive attitude, a willingness to ask questions, innovation advocating, and persuasive evangelism.
  • Profound Profiling by Daragh O Brien – Discusses the profound business benefits of data profiling for organizations seeking to manage risk and ensure compliance, including the sage data and information quality advice: “Profile early, profile often.”
  • The Importance of Scope in Data Quality Efforts by Jill Dyché – Illustrates five levels of delivery that can help you quickly establish the boundaries of your initial data quality project, which will enable you to implement an incremental approach for your sustained data quality program that will build momentum to larger success over time.
  • The Myth about a Myth by Henrik Liliendahl Sørensen – Debunks the myth that data quality (and a lot of other things) is all about technology — and it’s certainly no myth that this blog post generated a lengthy discussion in the comments section.
  • Definition drift by Graham Rhind – Examines the persistent problems facing attempts to define a consistent terminology within the data quality industry for concepts such as validity versus accuracy, and currency versus timeliness.
  • Data Quality: A Philosophical Approach to Truth by Beth Breidenbach – Examines how the background, history, and perceptions we bring to a situation, any situation, will impact what we perceive as “truth” in that moment, and we don’t have to agree with another’s point of view, but we should at least make an attempt to understand the logic behind it.
  • What Are Master Data? by Marty Moseley of IBM Initiate – Defines the differences between reference data and master data, providing examples of each, and, not surprisingly, this blog post also sparked an excellent discussion within its comments.
  • Data Governance Remains Immature by Rob Karel – Examines the results of several data governance surveys and explains how there is a growing recognition that data governance is not — and should never have been — about the data.
  • The Future – Agile Data-Driven Enterprises by John Schmidt on Informatica Perspectives – Concludes a seven-part series about data as an asset, which examines how successful organizations manage their data as a strategic asset, ensuring that relevant, trusted data can be delivered quickly when, where and how needed to support the changing needs of the business.
  • Data as an Asset by David Pratt – The one where a new guy in the data blogosphere (his blog launched in November 2010) explains treating data as an asset is all about actively doing things to improve both the quality and usefulness of the data.


PLEASE NOTE: No offense is intended to any of the great 2010 data quality blog posts not listed above.  However, if you feel that I have made a glaring omission, then please feel free to post a comment below and add it to the list.  Thanks!

I hope that everyone had a great 2010 and I look forward to seeing all of you around the data quality blogosphere in 2011.


Related Posts

The 2010 Data Quality Blogging All-Stars

Recently Read: May 15, 2010

Recently Read: March 22, 2010

Recently Read: March 6, 2010

Recently Read: January 23, 2010


Additional Resources

From the IAIDQ, read the 2010 issues of the Blog Carnival for Information/Data Quality:

From the Data Roundtable, read the 2010 quarterly review blog series: