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A lot of times report developers are working against a running clock to deliver the reports they are asked to produce as quickly as possible. As such, many times we end up with a multitude of reports with different looks and feels as this is usually a lower priority. Best practices ask for a consistency in …read more
Participating as a speaker at different international conferences and being engaged in different data governance communities, provides me with a lot of interactions with data professionals from different industries, countries, and organizational cultures. I’m always interested to know how each organization develops and evolves its data governance program, how it structures its operating model, and …read more
Similarly to how an organization’s human resources, equipment, and intellectual property are assets, so is data. Managing its quality is essential in order for the organization to be able to rely on it and benefit from it, yet many data quality initiatives tend to fail when these common mistakes are ignored. These are the 7 …read more
I’ve received a lot of positive feedback on the data governance maturity models series as it provides the high level overview of each model to guide you into adopting one for your program. In this article I’ll go over the Gartner data governance maturity model. If you’d like to go over the ones covered so …read more
In order to have a successful and fully functioning data governance council/ committee, you need to establish a Terms of Reference (TOR). What is this TOR? It’s a document which outlines the purpose, structure, and roles and sets certain expectations for the members. The details listed in the TOR are are important as the selection of …read more
This article is covering DataFlux data governance maturity model and continuing the series of data governance maturity models as a data governance evaluation tool. Check out these other ones: Stanford Data Governance Maturity Model IBM Data Governance Maturity Model DataFlux Maturity Model Overview: Developed by DataFlux in 2007, it was based on their ten years …read more
In all data visualizations you want to have the user quickly identify the most important information. You might need to draw their attention to an outlier, to a metric that is under-performing or over-performing. This can be done through color, though not only, by applying these principles: 1. Use commonly understood colors We get bombarded …read more
When reference data comes up in discussions with other data management or data governance practitioners, we sometimes realize we mean different things or we only overlap in our definitions 80% of the time. Within a data governance conversation, this seems a bit ironic. So what is reference data, in the context of data management (let’s …read more
As an educator, speaker, and data governance professional I sometimes get asked, “How can you measure the effectiveness of your data governance program?” From my experience, there are two main ways to do so: Through a data governance scorecard By evaluating it against a data governance maturity model This series of articles is focusing on …read more
I love metadata because of the benefits it offers. In fact, I never “metadata” \met a data\ I did not find useful (geeky joke, I know). If you don’t have a metadata management program or initiative in place, there are a lot of reasons why you should consider investing into it. In fact, the following …read more
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