The Data Warehouse Is a Monolithic Data Product

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Eric: 20 years ago data warehouses were very similar data warehouses they threw traditional developers at it and they wanted to use kind of a waterfall development methodology get all of the requirements spend six months developing it roll it out people are like this is great used at once by the way the business is moved on. Eric: I just very clearly remember this kind of epiphany of like oh no a data warehouse which is definitely like a monolithic data product that needs to be living and iterating not just growing in complexity so I agree 100% shit yeah he says. He argued about whichWhich internal product affects more people's decisions on a daily basis? "The org chart" The most commonly trafficked page

Have you ever built a data-related "thing" — a dashboard, a data catalog, an experimentation platform, even — only to find that, rather than having the masses race to adopt it and use it on a daily basis, it gets an initial surge in usage… and then quietly dies? That's sorta' the topic of this episode. Except that's a pretty clunky and overly narrow summary. Partly, because it's a hard topic to summarize. But, data as a product and data products are the topic, and Eric Weber, the data scientist behind the From Data to Product newsletter, joined us for a discussion that we've been trying to make happen for months. It was worth the wait! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.