Who is responsible for data quality? – Survey Results

After my recent post about “Who is responsible for data quality?” I received several comments from people. I posted this question to Business Intelligence Professionals in LinkedIn to get an understanding of what is the experience of BI professionals when it comes to responsibility for enterprise data quality… following are some of the findings based on responses to this survey/discussion.

In this survey I asked several questions

1. As to whom do you think is responsible for data quality?
2. How did you handle situations where data quality was an issue in your BI project or deployment?
3. How do you monitor data quality on a ongoing basis? How do you measure it?
4. How often do you assess data/information quality?

Following is summary of what I learned from the responses I received…

1. Unanimously, it was expressed and felt that the data quality responsibility lies with all parties who deal with data across organization (creation, maintenance, usage, management etc…).
2. It was suggested that IT should play advisory and enabler role where IT is not only providing tools and technologies to find out quality problems but also making recommendations and providing capabilities to correct the data quality issues business faces. Extreme collaboration between business stake holders and IT was suggested and expected in fixing data/Information quality issues.
3. There was consensus around validating data quality periodically. Response as to how often it should be validated varied from person to person and was based on their specific experience from the past and current engagements. (It varied from daily to monthly to quarterly to every once in two years)
4. While data warehouse or BI solutions can correct data quality within the warehouse domain, there was preference to fixing data quality at the source where ever possible (off course with the help from business stakeholders or business stakeholders taking responsibility to do this with enablement from IT)
5. Other measures/factors which could be used to make data quality a continuous process was…
   1. Building business rules/processes in the System of records applications
   2. Training users who are responsible for generating data as well as people responsible for using/consuming data for decision making
   3. Use and aid of various technologies including but not limited to data profiling, business rules repository, metadata repository to capture metadata/rules etc… was suggested.

In summary, I was really happy to see the unanimous response about IT-Business stakeholder collaboration to fixing data quality. This really puts IT in much more strategic and valu additive role in the organization when it comes to valuing the data assets of the organization.

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