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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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What Is a Data Product? A Star Schema with 15 Tables as a Test Case
I hear this one from clients every now and then: even the smallest table is a data product here, you can click on it, subscribe, and use it. I know the other end too, a whole schema of physical tables provided as a data product without any further description. Both go by the same name, which shows how differently the term gets used.
Data Products: What Has to Be in Place Before an Agent Can Build Them?
In June, at TDWI in Munich, I watched an AI agent build a data product in about 18 minutes. That was pretty impressive, for me and for everyone in the room. During the talk it quickly became clear to me what has to be in place before something like that works.
3NF, Data Vault, Star Schema: Which Method Belongs in Which Layer
The conceptual model is finished, and from here on it gets built. The shortest implementation route from source to finished report is the one that skips a whole layer of the architecture, and it works, too — for as long as the assumptions behind it hold.
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.