December 1, 2023
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Data Governance Columns

Eyes on Data: The Right Foundation for Trusted Data and Analytics

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Trust. Trust is defined as the assured reliance or belief on the character, ability, strength, or truth of someone or something (Webster’s Dictionary). It’s a term we use often to describe how we feel about the people, the institutions, and the things around us. But I would argue that the term “trust” was used differently…

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Crossing the Data Divide: Framework for Selling Data Initiatives

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Deja Vu All Over Again Something interesting has been happening to me over the last few months that I’ve not experienced in a while. Smart and experienced CIOs and their data leaders have been asking me for input regarding how to sell the value of a data program. The question is a clear sign of…

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Data Professional Introspective: Accelerating Enterprise Data Quality

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My recent columns have focused on actionable initiatives that can both deliver business value, providing a tangible achievement, and raise the profile of the data management organization data management organization (DMO).(For more on the DMO, a plug-and-play initial organization was proposed in an earlier TDAN column, “Coming in from the Cold.”) In that light, let’s…

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Through the Looking Glass: Data Provenance in the Age of Generative AI

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Am I right that you can’t open LinkedIn, read a tech or business blog, or attend a conference for more than 30 seconds without encountering the generative AI hype? It’s been this way ever since last fall when OpenAI unleashed ChatGPT upon a (mostly) unsuspecting world. Depending on who you read or listen to, generative…

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Data is Risky Business: A Wicked Problem This Way Comes

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A recent data security incident in the Police Service of Northern Ireland (PSNI) got me thinking about the idea of wicked problems and data. The data security incident was the disclosure of the names, ranks, and job assignments of every officer and civilian support staff member in the PSNI. This happened due to ‘human error’…

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