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A new data model for the data warehouse is necessary, but how do you model data? Understanding temporal data and learning methods and techniques to do so? Or a certification in data modeling?
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When Data Arrives Out of Order: Late Arrivals and Corrections
There's a question that comes up in every workshop sooner or later: “Do we really need this complexity?” What people mean is bitemporal historization – two timelines instead of one, a few more columns, more logic when loading. It's a fair question.
![„[antifragile data] — podcast logo, launching September 2026"](/images/blogposts/2026/podcast-ankuendigung/AntifragileData_Podcast_Article.webp#joomlaImage://local-images/blogposts/2026/podcast-ankuendigung/AntifragileData_Podcast_Article.webp?width=1500&height=844)
Why I'm starting a podcast
The best conversations at conferences rarely happen on stage. They happen during coffee breaks, at dinner, on the walk to the taxi. That's where people talk openly about what actually worked and what didn't — no slides, no marketing filter. And those conversations are almost never recorded.
The Data Modeler in 2026: A Role in Transition
"Do we actually still need data modelers if AI can take over?" The question came up after a coaching session. I paused. Not because the question was fundamentally wrong — but because it was the wrong question.
Read more …As a long-standing partner of TEDAMOH, we would like to express our enthusiasm and appreciation for the cooperation in our Smart Factory project. One of our outstanding achievements was the successful implementation of a fully automated production line at our plant in Bamberg.
Read more …First of all, I would like to emphasize that preparing for the DMC was a challenging but absolutely rewarding experience. In order to pass the exam successfully, I focused on different methods:
Read more …The training is highly recommended because the complexity and added value of modelling becomes clear. It is also comprehensive and covers all aspects of modelling. Everyone benefits from modelling!
Read more …As a result, the team's knowledge, identification with, and trust in the data model are at a high level. This is very good, because we are facing great challenges on our way to becoming a data-driven company.