One of the most significant areas of Data Ethics concern is bias in generative AI models. Concerns about algorithmic bias are not new. Associative model (i.e. neural network) bias is not new. Even the ceding of consequential decisions to these Read more…
In the holiday classic, It’s the Great Pumpkin, Charlie Brown, and earlier in the October 25, 1961 Peanuts comic strip, Linus Van Pelt famously says: There are three things I’ve learned never to discuss with people: religion, politics, and the Read more…
This is the second installment of a two-part series about the impact of AI on information management. The first covered Data Quality and Metadata Collection. Data Modeling Nobody at your company is more passionate about understanding the data than your Read more…
“The Golden Eagle award is presented to a senior who soars beyond the expectations of others. On first impression, people expect all sorts of different things about each of us; some we have to strive to meet and some we Read more…
We are at the threshold of the most significant changes in information management, data governance, and analytics since the inventions of the relational database and SQL. At their core, these areas have changed very little over the past thirty years. Read more…
The last class I needed to graduate from college was Statistics. I wasn’t avoiding it, but I wasn’t excited about it either. Statistics classes were taught out of a couple different departments, but “Math Stats” was the required option. There Read more…
Recent advances in large language models have reignited interest in Artificial General Intelligence (AGI). It’s coming soon! Just like it has every couple of decades since the 1950s. But the trajectory of recent successes make it seem more plausible this Read more…
In the Data Ethics episode of the Rock Bottom Data Feed podcast, our guest Daragh O’Brien made the observation that in our industry we often mix up word sequencing. For example, to him there is no such thing as “Data Read more…
I’ve covered Data Product implementation requirements at length in several past articles. You need Information, Infrastructure, and Process. Without any portion of any of those you don’t have a Data Product. No metadata? Not a Data Product. No lifecycle management? Read more…
This is the third part of a multi-part series discussing Data Quality and the ISO 25000 series standard. OK. You’re with the program. You recognize that having quality data is important for accurate AI models. You would even concede that Read more…