Like many BI practitioners, I have been spending a lot of time lately thinking about what analytics tools should look like in the age of AI. Most people fall into one of two camps. The first camp believes that AI should essentially do analytics for you. Ask a question, get
Tableau 2026.2 recently released, and it was loaded with important features. In my opinion, none was bigger than Composable Data Sources (now available in 2026.2.2). But there were plenty of other really solid additions: drive time on maps, SVG downloads, the ability to edit Bridge data sources
Back in 2025, Tim Ngwena and I did a Tableau data modelling masterclass on Tim's channel using the bookshop data set. This is still a great foundation for data modelling. However, we covered modelling but not the implications for it in an enterprise Tableau Cloud/Server environment. Composable
For years, Tableau developers have lived in an awkward middle ground. Tableau developers have done great work only to hear, “That calculation should really be in the data source” or maybe, “Why is this dashboard so slow?” To which the answer, in frustration, is often, "I would… if I
When working with people who are new to Tableau and using it in enterprise environments, I'm usually asked the following within a few weeks of them starting: “Wait… are you saying I can't build relationships on top of published data sources?” The natural tendency, especially for
Part 2 of 2 - Multiple base tables Part 1 of this series explained how Tableau data models with a single base table create joins. This post will explain the differences with multi-fact relationship models, that is, models with more than one base table. To follow along with this post,
Part 1 of 2 - Single base table Tableau released the relationships feature (aka object model; aka the noodle) six (6) years ago in the 2020.2. In my experience, it is still an underused feature because people don't understand how the model leads to the creation of joins