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Author: Ann All

Who should be responsible for data governance? Data duties have traditionally fallen to IT, but the business is held accountable for problems arising from poor data quality, says Ian Rowlands, senior director of product management at ASG Software Solutions. Ann recently interviewed Rowlands:
All : Why is data governance so important?

Rowlands : There are three main drivers: one highly tactical, one highly strategic and one kind of in between. The tactical one is data quality. I am starting to chant a little mantra: "Data dictates decisions." If you have bad data, you make bad decisions. That can be hugely significant, of course. That's a pointer to the fact that data governance is a framework that can encompass a wide variety of different projects.

The second big driver is compliance. We're seeing things like Basel II, which was a driver for the project we did with HSBC. (Editor's note: ASG and its client HSBC were named co-winners of The Data Warehousing Institute's Best Practice Award in the category of Data Governance. HSBC uses ASG-Rochade, a metadata repository that is implemented in 10 of the world's 20 largest banks and at other companies worldwide as an enabling technology that manages information about data and systems across the enterprise.) But compliance is now almost everywhere you turn. Every industry has its own multi-initial nightmare, HIPA in the health care space, etc. If you sign for data knowing it hasn't been adequately derived, you can wind up in a nice, orange suit. That to me fits between the tactical and strategic.

The very strategic driver is all about business agility. Very often data governance encompasses data integration and business transformation initiatives. Clearly if you have multiple instances of effectively the same information or you have people creating their own variants of the same information, it becomes very difficult to make business changes as rapidly as you'd like. A telecommunications company we worked with had difficulty changing rate plans because they had to rush around and change so much information before they could actually change the plan.

All : Is data governance getting a higher profile now that organizations are interested in using their data to do things like analyze customer behavior patterns? Rowlands : That's where you get to a really interesting phenomenon. There are a whole bunch of disciplinary and technical trends which play into the notion of data governance. At the disciplinary end, there are things like master data management, there are functional capabilities like CRM, which is kind of a subset of master data management. All of those drive toward a governance notion.

Then there is the shift of power from the IT organization to the business organization, particularly the interest in business glossaries and other semantic-related concerns. That gets to be interesting. We work with a health care organization, for instance, which is having great debates about what "length of stay" means for their organization. Is it the amount of time a patient spends in a bed or the amount of time the insurance company is prepared to pay? In the end, it's a governance question.

At the technical end is the whole SOA phenomenon. We have organizations that are moving rapidly from the idea of SOA as a functional repartitioning approach to using SOA as a way of encapsulating and exposing data objects for reuse in a wide variety of contexts. That obviously isn't going to happen unless there's an effective data governance approach in place.

All : You touched on the problem of different data definitions. What are some other data governance challenges? Rowland : There is data quality, of course. That's a technical issue, as are data definitions. But there are some straightforward, big picture challenges as well. The biggest one is all about who should own the processes. It's a cultural thing more than anything else. Traditionally IT has owned the data, but the accountability is increasingly with the business. It's generally the CFO who will get arrested if the data that is signed off on proves to have been constructed using a process that has caused the data to be inaccurate or unreliable.

Related to that is the whole question of who has to do the work and who gets value out of doing the work. A data governance activity can impose a significant burden on the people who are responsible for defining the business entities, defining the relationship between the business entities and the technical entities, managing the business rules that control how information may be accessed and transformed. The benefit very often does not fall on the people who have had to do the work.

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