Current State of Data Quality: 2006 Open Research
|This open research into data quality was performed during the last week of September 2006 and there was 1,137 respondents. The survey was sent out to the Dr. Dobb’s Journal mailing list.
The results of this survey are summarized in the article Whence Data Quality? in the February 2007 of Dr. Dobb’s Journal.
You may use this data as you see fit, but may not sell it in whole or in part. You may publish summaries of the findings, but if you do so you must reference the survey accordingly (include the name and the URL to this page). Feel free to contact me with questions. Better yet, if you publish, please let me know so I can link to your work.
- There are significant data quality problems within many organizations, yet many organizations do not have a viable strategy for addressing them.
- The earlier, and more often, that you test your database in the development lifecycle, the greater the data quality.
- A collaborative approach to data standards/guidelines is more effective than a command-and-control approach, which in turn, is better than no approach at all.
- A large percentage of organizations struggle to evolve their database schema in a timely manner, thereby reducing their competitiveness.
- Evolutionary/agile approaches to data modeling are just as effective as traditional approaches, and both approaches correlated to improved data quality.
- Database service-level agreements (SLAs) are co-related to improved data quality.
- This survey suffers from the fundamental challenges faced by all surveys.
I’m sharing the results, and in particular the source data, of my surveys for several reasons:
- Other people can do a much better job of analysis than I can. If they publish online, I am more than happy to include links to their articles/papers.
- Once I’ve published my column summarizing the data in DDJ, I really don’t have any reason not to share the information.
- I think that it’s a good thing to do and I invite others to do the same.