Data Governance Interview - Mark Horseman

Mark is an IT professional with nearly 20 years’ experience.  Mark moved into Data Quality, Master Data Management, and Data Governance early in his career and has been working extensively in BI since 2005.  Mark currently leads a team of IT professionals architecting a Data Warehouse at Vecima Networks.

How long have you been working in Data Governance?

I’ve been working in Data Governance off-and-on since 2007/08, but have been working with Data Quality since 2004/05.

How did you start working in Data Governance?

I started my IT Career in Sales in the 90’s, achieved a B.Sc in Computer Science and moved to programming.  During my internship, I worked on an Identity Management System for the University of Saskatchewan.  As part of that work, a lot of my programming was dealing with data associated with Students, Staff, and Faculty.

From that experience, I had moved on to Student Information Systems, and worked on integrating data from our Identity Management solution to our purchased Student system.  (“SCT Banner” at that time, now known as “Ellucian”)

After that integration, we worked on a Business Intelligence solution, and I became keenly aware of issues in Data Quality (2004/05 time frame) and how Data Quality impacted the understanding of the operations of the institution.

From there I moved on to Institutional Research, and began getting into data definitions and understanding data stewardship, ownership, and governance, although no one called it “Data Governance”.  I had begun reading as much content as I could, and kicked off my own blog as a method to reach out to the really talented people in the field.  This is where I ran into “The Data Governance Institute” (http://www.datagovernance.com/), books by Jill Dyché, and Jim Harris’s “OCDQ” blog.

What were your initial thoughts when you first fully understood what you had got into?

I had an epiphany that I landed on something that sounded a bit like IT, but wasn’t really an IT problem or process at all.  It was something that required outreach and awareness that data is an asset and that stakeholders needed processes to ensure that the data asset was a value to the institution.

Are there any particular resources that you found useful support when you were starting out?

Besides the excellent things mentioned above, the sheer brilliance and content available on Twitter.  There are a lot of really talented people out there providing thought provoking content absolutely free!

What is the biggest Data Governance challenge you have faced so far?

The word “Data Governance” is the biggest challenge to its implementation.  In the places I’ve gone to talk about Data Governance, that’s the comment I hear.  This could be a Saskatchewan / Canadian culture thing, but it’s as though the term “Governance” implies a level of bureaucracy that people find intimidating.  I find that processes around data management require a packaging that doesn’t include the term to achieve acceptance.

What have you implemented or solved so far that you are particularly proud of?

Back in my Higher Education days, I had implemented the “Data Quality Golf-Card”.  We had used the Kimball idea of Data Quality Screens (think panning for gold).  Using these Quality Tests, we had assigned a value to each time when data failed to pass through the screen.

Each screen was associated with a particular stakeholder and we met regularly to try and get their score down to “Par”.

What single piece of advice would you give someone just starting out in Data Governance?

Work hard at understanding the culture and what types of processes will be a good fit.  If there are vestiges of process in-place, work with it to implement Data Governance.

Finally, what do you wish you had known or done differently when you were just starting out in Data Governance?

I wish I had started sooner.  BI without Data Governance was more challenging than it needed to be.

Having read my interview with Mark you can also read my free report which reveals why companies struggle to successfully implement data governance.  

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