In my previous post I explained that even if your organization does not have anyone with data steward as their official job title, data stewardship plays a crucial role in data governance and data quality. Let’s assume that this has inspired you to formally make data steward an official job title. How
Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines
Data stewardship is one of the most important, and commonly misunderstood, aspects of data quality and data governance. Not only are the characteristics of a good data steward a rare combination of skills to find in an individual employee, the culture of most organizations does not nurture the development of data stewardship. It would not
Truth is a funny thing. And I don’t just mean how some true things are funny. A few examples include that strawberries are not berries, peanuts are not nuts, Chock Full o’Nuts coffee does not contain nuts, and the singer-songwriter Barry Manilow did not write his hit song “I Write
Every day of the year, there's a holiday celebrating one thing or another. In fact, you probably didn't know that Oct. 22 WAS CAPS LOCK DAY. Whoops. Or, if you're like me, you completely spaced on Oct. 26. It was Mother-in-Law Day. Boy, we'll be hearing about that for the
The first step is establishing governance for reference data is assessing the existing reference data landscape: understanding what reference data sets are used, who is using them, and how they are being employed to support business processes. That suggests a three-pronged approach to identifying organizational business process and application dependencies
Sometimes you have to get small to win big. SAS Data Management breaks solution capabilities into smaller chunks – and deploys services as needed – to help customers reduce their total cost of ownership. SAS Master Data Management (MDM) is also a pioneer in "phased MDM." It's built on top of a data
In a previous blog, I wrote about the top ten fallacies of why data governance is perceived to be too burdensome and costly. Hopefully I dispelled the preconception that data governance is slower and less nimble than today's informal data management practices. In this post, we'll examine the concept of governance
One of the biggest impediments to (and failures of) a new data governance program is the perceived level of “extras” required. Let’s enumerate some of the concerns that I hear consistently from our clients: Extra people will be required to staff the implementation. Extra budget money will be needed to fund the
"One size doesn’t fit all" is a well-known refrain in the data governance community. Typically, this well-worn but evergreen adage is applied when discussing organizational structures. Two companies in the same industry, of like size and means, with similar objectives can take drastically different approaches for instantiating data governance within
