After 834 days away, Andy Clark, Tom Gough and Shailan Chudasama are back. They open with a quick stats quiz:
- It’s been 2,181 days since the podcast first launched.
- The show has had 3,421 downloads during the break alone.
- Their book, Financial Modelling and Reporting with Microsoft Power BI, came out 151 days ago and is holding a 4.8/5 rating on Amazon.
They then look at what’s changed. Fabric has gone from a hard sell (“why not just buy the Azure pieces?”) to a mature platform where the financial case is easy to make, even for smaller teams. Tom’s work has shifted toward Python notebooks for metadata-driven loading and handling schema drift. Shailan notes that clients now arrive asking for a medallion Lakehouse by name, rather than needing to be talked out of a classic data warehouse. They put this down to Microsoft’s push and to people discovering Lakehouses when they spin up Fabric trials.
On Copilot, perceptions are improving, and its availability across all F SKUs makes it an easy box to tick in procurement. The move to consumption-based billing for AI raises real cost concerns, though. Tom suspects that once AI costs show up as a clear line on the P&L, some of the expected savings will evaporate. Andy questions how much prompt-based querying of semantic models is actually happening, and Tom argues a well-designed model shouldn’t need it. All three warn that AI-generated reporting could worsen report sprawl and conflicting numbers. As Tom puts it, a man with two watches is never quite sure what time it is.
The episode closes with reflections on writing the book: a year of enjoyable writing followed by an exhausting editing and proofing process, the difficulty of writing for an unseen global audience, and a new appreciation for why tech books cost what they do.
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