This is post number 666 on this blog. 666 is the number of the beast. Something diabolic.
The first post on my blog came out in June 2009 and was called Qualities in Data Architecture. This post was about how we should talk a bit less about bad data quality and instead focus a bit more on success stories around data quality. I haven’t been able to stick to that all the time. There are so many good data quality train wrecks out there, as the one told in the post called Sticky Data Quality Flaws.
Some of my favorite subjects around data quality were lined up in Post No. 100. They are:
- The role of technology in data quality improvement. This subject was discussed not long ago in the post Reading the right Reading.
- Fit for purpose versus real world alignment, a subject revisited recently in the post called The “Fit for Purpose” Trap.
- Diversity in data quality was touched latest in the post American Exceptionalism in Data Management.
The biggest thing that has happened in the data quality realm during the five years this blog has been live is probably the rise of big data. Or rather the rise of the term big data. This proves to me that changes usually starts with technology. Then we after sometime starts thinking about processes and finally peoples roles and responsibilities.