You can also look at it differently. Late last year I was at a meeting of DAMA NL, the association of data professionals. "Poor quality data are not worthless," 70% of the attendees responded to a poll. In fact, you can clean up a data collection very well. So consider yourself lucky if your organization has a lot of data, even if some of it is "moldy" or out of sync.
Raising and maintaining the quality of data collections does, however, require time, attention and investment, for example in setting up a good data quality management system. Data professionals must convince their company management that those investments are worthwhile. And data management is not a sexy topic in the boardroom.
Sexy data
One way to solve that is to make the topic sexier. With greater insight and understanding of the entire process of data quality management, it is also easier for company executives to envision the importance of good data management. In an effort to create that understanding, DAMA's Data Quality Working Group developed a flow chart inspired by subway line maps. They aptly named it "Metro Model . By following the lines, you visit the 30 stations and become familiar with all the aspects involved in data quality management, at both strategic and operational levels. You visit 'Stakeholder Analysis and Compliance' and pass 'Roles and Responsibilities'. 'Risk analysis' is covered and of course 'Data cleansing & Data issues', but also 'Data suppliers & Data lineage', just to name a few stations on the metro map.
The working group even created an interactive online diagram to go with it. By playing with it, you get an even better understanding of the relationships between the various elements.
More playful subject
Whether the subject really becomes "sexy" with a subway ticket remains to be seen, but which topics in the boardroom really deserve that designation? That said, discussing the topic with the boardroom is very important, now that everyone is talking about data-driven work. DAMA's Metro model at least makes it more playful and ensures that all components of data quality management are on the agenda.
