Listen to this article: Over the next several weeks we’re going to dive back into Data Products. If you’re not already familiar with the concept, a refresher on the foundations of Data Products may be useful. Take a minute and check out some of my blog articles on the subject Read more
Listen to this article: OK. You’ve convinced management to support a Data Products initiative. Maybe you want to do AI and not be one of the 95% that fail or underperform. Maybe you have an existing analytical environment that’s like the house at the end of the street that hasn’t Read more
Listen to this article: The vocabulary generator has been working overtime. Just last week I talked about Data Contracts. Here’s another: Data Trust. I predict that through 2028, 80% of S&P 1200 organizations will become curious about the meaning of Data Trust. Why? Because among The Gartner 100 Data, Analytics and Read more
Listen to this article: Here we go again. We seem to have an irresistible reflex to prepend “data” to every noun, verb, and adjective in the dictionary. Here’s another: Data Contract. My first thought, when I heard about Data Contracts, was that we’re creating a new term to describe something that 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? Not a Data Product. And so on. Data Product development Read more
Data Products are a bigger deal for you (and your company) than AI. You’ll see what I mean shortly. When I first started writing about Data Products, I mentioned my excitement at how information management had finally become the next big thing. Even better, the business was demanding the metadata. Read more
Part 1 of this Data Product Architecture series covered the “where” of Data Product data implementation: federated or consolidated or some combination of the two. Here in Part 2, we’ll get into the “how” of Data Product data implementation: virtual or materialized or some combination of the two. Which to Read more
Awesome! You’re moving forward with a modern analytics architecture built upon Data Products. Maybe you’re going to implement a Data Mesh and/or Data Fabric. Maybe you’re just looking to make your enterprise analytics more scalable and sustainable. Whatever the reason, you now have a couple of architectural decisions to make; Read more
I hate paying more than I have to for something. And I really hate paying interest, whether it’s on a credit card … or a loan … or Data Debt. Data Debt is the accumulation of unresolved data-related issues and unfinished information management activities. Think shortcuts taken in the interest Read more
Great question. After all, a Data Product Provider is responsible for: producing the content, ensuring its availability, and validating its correctness collecting the metadata and publishing it through the Data Product Catalog responding to questions and enhancement requests Or, more succinctly: content, curation, catalog, certification, and maintenance. Along the way Read more