Whenever people participate in a polling exercise they provide a valuable perspective to the poller. With that in mind, I’d like to thank all that voted in the second set of The Data Quality Chronicle Polling exercise. You can view the results of the first polling session here.
Basic Poll Design
A polling section of the blog was setup in order to solicit information from the readers on various topics. In an attempt to gain an insight of the larger data quality picture, the second edition of the polling contained questions that I have observed being discussed in the data quality blog-o-sphere. The questions were as follows:
- Do you view data quality as a business issue with technology requirements or a technology issue with business requirements?
- Does the return justify the cost of implementing a data quality program?
- Is data quality an essential part of Master Data Management?
Data Quality Ownership
The question of whether data quality is a business issue with technical requirements or a technical issue with business requirements has long been debated in the data quality community and recently has surfaced in a lot of blog postings I’ve read. For that reason I wanted to include it in this edition of the polls.
The results of the polling regarding data quality ownership are depicted in Figure 1 below.
Data Quality ROI
Like any other business initiative, one of the most important decision factors in deciding whether or not to implement is return on investment. So I felt it was a good question to include in the polls and was eager to see the results.
The results of the polling regarding data quality ownership are depicted in Figure 2 below.
Data Quality and Master Data Management
One question that has also surfaced lately is whether or not data quality belongs as a stand-alone solution or part of a broader defined master data management solution.
The results of the polling regarding data quality ownership are depicted in Figure 3 below.
Even though the sample size was relatively small, I feel like there are some strong conclusions that can be drawn when reviewing this simple polling exercise.
It is clear that those that responded feel as though data quality is part of a master data management solution and that data quality is a business issue with technical requirements. It’s also fairly clear that most feel that data quality initiatives are worth the capital investment, although this should be calculated before moving forward.
While there are no surprises in the results of this polling session, it does add credence to most of the material being generated by the data quality expert community.
If you are responsible for implementing data solutions, I hope this helps provide information on if and where to implement your data quality solution. If you are a data quality specialist, I hope this helps you provide information to your clients about where and why to implement a data quality solution.