In part one of “Metadata Governance: An Outline for Success,” I discussed the steps required to implement a successful data governance environment, what data to gather to populate the environment, and ...

In the last few months, we have seen the wave of Artificial Intelligence break on the shores of wide-scale business adoption and mainstream media coverage of Large Language Models, most famously ...

No, this is not a mistyping of data literacy. Yes, like everyone, I am aware of and fully on-board with the growing movement to improve data literacy in the enterprise. What I want to talk about is ...

In this column, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter ...

There’s no denying it. The digital revolution we’re living through has fundamentally changed how business is done. So much so that digital platforms and applications now drive enterprises of all kinds ...

We are culturally conditioned to want more. More money, more fun, more pleasure, more accomplishment, more intelligence, and yes, more data. There is an idea that if we get more, we will be happier ...

Let’s assume this scenario — Your organization has conducted an EDM Assessment. You now have detailed knowledge of your data management strengths, accomplishments, and capability gaps. Armed with that ...

As autumn settles here in the northern hemisphere, with October baseball underway, the first frost arriving, and the holiday season on the horizon, it’s a time I look forward to. The exhilarating ...

In the first part of this blog, I wrote about challenges Chief Data Analytics Officers face in their role. Our understanding of the challenges as background on CDAOs brings us to the four key tenets ...

It’s my great pleasure and honor to begin as a columnist for TDAN.com. TDAN.com has a long and distinguished record of giving voice to ideas in the data space and I will do my best to continue that ...

What happens when people who should be accountable for producing quality data as part of their job make it clear that they want nothing to do with producing data? What happens when these people say, ...

There are always two aspects to data quality improvement. Data cleansing is the one-off process of tackling errors within the database- ensuring retrospective anomalies are automatically located and ...