I watched the above video today and was shocked with what you showed. I have been investigating Power BI for about 3 years and everywhere I go, it is suggested that a STAR SCHEMA be used. This obviously requires upfront study to determine the fact table and dimensions to be populated. The video today showed a schema straight from the transaction system—not a best practice.
I do not even know where to start with my questons — but I have lost a lot of confidence today in Enterprise DNA.
A friend showed me her companies PBI model and it was exactly as shown in your video - not a STAR. This makes everything in the model more confusing.
I watched the video today too, and would be very interested to hear ways in which you think @sam.mckay 's model violated a star schema approach? Star schema is not limited to a single fact table, but characterized by fact tables filtered by a single level of dimension tables (as opposed to a snowflake schema with multilevel dimension tables) and connected to the fact table(s) (and NOT to each other) via key fields in a unidirectional one-to-many relationship at the appropriate level of granularity. I saw no violations of any of that in Sam’s model, so I’m not sure where your “loss of confidence” comes from.
I would suggest perhaps reviewing the definition and characteristics of a star schema:
I watched the replay of the video this morning, and I’ll echo @BrianJ’s comments; @sam.mckay did use a data modelling approach consistent with the eDNA teachings - a standard waterfall layout, albeit looking more complicated this time as there were multiple fact tables instead of just one.
I’ve consumed hundreds (more likely thousands, actually) of eDNA videos and always found a clear, consistent approach to data modelling. I as well would be interested in hearing from you what you think the violations were.
I echo what @Greg and @BrianJ has commented. I turned into the actual live webinar and followed along what Sam was instructing us on a data set that he never has used before.
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