Posts tagged: data governance

How to Govern Data – A Simple Method to Implement Governance

Some time ago, while working with a large data warehouse, I formulated a simple method to govern data. The method was introduced as part of our Basel II work and was required by our Basel II Risk Management Policy. Subsequently as we were validating our plans for a data governance program, it was reviewed and [...]

Where to Govern Data – Control Points in Information Flows

My last entry suggested that data governance is not a new problem. While exploring data governance, we are revisiting the issues encountered as society built out roads, and developed modern manufacturing processes. The only difference is what we are governing this time is data content instead of a physical thing. With that in mind, it [...]

5 Simple Criteria to Determine What to Govern

With increasing frequency, people are asking, “what is a simple solution to data governance?” They, and likely you, are looking a silver bullet to bring order out of chaos. The ironic part of the problem is that it is not a new problem; rather it is an old recurring problem with a new name. What [...]

Data Steward v. Data Custodian – What’s in a name?

Some time ago, on a project far, far, away, we spent a good deal of time trying to define roles around data governance. We recognized that both the business and the technology teams were key contributors in our fledgling data governance program. What was proposed was that Data Stewards were on the business side of [...]

Data Governance and The Laws of Physics

As much as developers would like to believe that they have total creative license, they really are bound to some degree by the underpinnings of their development software. No matter the language, platform, or technology, somewhere along the line there are limiters on what a developer can do that govern their efforts. Solution developers will [...]

A Simple Choice

Right now many enterprise data producers behave like monopolies. They set the standards for what they produce and the downstream applications have no choice but to take what they get. This is a fundamental problem with most enterprise data architectures. This behavior encourages chaotic environments and cost business billions of dollars in wasted effort.

Data Governance and Industrial / Organizational Psychology

Much has been written about the technical side of data governance, but we continue to give minimal treatment to the human side of the equation. I think that is in part due to the fact that as IT professionals, we tend to look for technical solutions to problems. But what do you do when the [...]

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