InetSoft Webinar: What Data Governance Success Looks Like

This is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of "Prerequisites For Good Reporting: Data Governance." The speaker is Abhishek Gupta, product manager at InetSoft.

When we talk about what data governance success looks like, what it looks like is making sure that the policies that come down from this data governance process are actually executed in a regular and sustainable way. And that can look like anything from making data quality more robust, to making sure that metadata is formalized, to enacting data privacy and security logging within the data itself.

So data stewardship is really the act of aligning the policies from data governance with the execution of data management, and tracking all of that data across its supply chain with the company. What does success look like. Success looks like a closed loop between the policy making and the constant evolution of the data quality and deployment over time.

What is the role of data stewardship in data governance?

Data stewards for better or for worse have really become roving line backers in a lot of companies, where, you know, anything having to do with data, the data steward shows up, but we find there are two qualifiers for a successful data steward. And one of them is that he or she is somebody who understands data at either the subject area level, or even the element level enough to track it across its supply chain or its lineage in a company. A data steward really understands the systems of origin, where the data’s created, where it comes from, how it’s touched across the organization by different systems and different users, and what its life cycle looks like in a company.

The data steward is really the de facto expert on a piece of data or a domain of data, for example, customer data or financial data, or charge of accounts data. Depending on the scope and the scale of the organization, across that data’s life cycle in the company, so that’s number 1, it’s sort of that, that data owner, that data expert if you will. But we also see the data steward as very much of a visionary and a change agent. We find that a lot of people who raise the hands and say, look, we need our processes around data to be more robust, become de facto data stewards in an organization. So what we’re finding is this role of a change agent really means, I see this data, I see how it’s being used, I see how it’s confusing people, I see how we can make it better.

And that has not only tactical implications in terms of data management, that actually has strategic implications in terms of customer loyalty, smarter target marketing, better compliance and ultimately higher lifetime revenue for a company as well. So the data steward is a big role, and we see the data steward in a data governance context actually participating in not only the data governance policy making, but also as a liaison down to data management where that policy execution is taking place. So in a lot of ways the data steward becomes the mouth piece on behalf of the data governance process to data management. It’s a really important role.

I’ve talked to a lot of people at different companies, it seems like data steward can be a role or a title that describes people that have very different job responsibilities. How many data stewards are actually at a company? What do they do? Is this something that’s real or something that I’ve heard, that’s sort of inconsistency in the roles and responsibilities?

Yes, there is really no one job description for data steward, and what we find, sort of counter intuitively, is that the role of the data steward depends on the size and the scope of the organization. So there may actually be a data steward within each business unit. What we’re finding more and more is that most companies will have subject area specific data stewards. So there will be a customer data steward, a financial data steward, a product data steward, and those data stewards will be responsible for the quality and deployment of the master data for that data domain.

However, that really depends on the size of the company. A lot of companies can’t afford to have a data steward for each domain, and in that particular case what we’re finding is the difference between a data steward on the business side who understands the business context and usage for the data versus what we call a source system data steward, somebody on the IT side who understands the systems that generate and process that data. So again, it really does depend on the size and the number of organizations in a company, how the role of data steward is divided up.

What are some final recommendations for data governance initiatives?

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One is, again, don’t rush to convening a committee. That usually backfires. Don’t prematurely enlist executives in data governance. We are finding that there’s a lot of unnecessary missionary work that’s going on in trying to, you know, proselytize the value of data to executives, who actually just want to see results. And we’re also saying that you should let data governance piggyback on an existing initiative or project that really needs data to be managed as an asset and really needs data in order to inform its success.

We’ve seen with a lot of business intelligence projects hit the wall because of data. So data governance really matters in some of these very customer focused initiatives. So when we’re getting ready for data governance I think the three pieces of advice are, don’t rush to committee, make sure to piggyback on a specific initiative that is already perceived to promise some value, and make sure that the ability to execute on the resulting policies is there at the beginning.