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Each of these three territories is well understood and well defined. The borders between them are clear and uncontested. It feels good. The top layer—how we cooked with our data, once the other tools put it all in its place—is the only problem left to solve (View Highlight)

Specifically, the data warehouse—the anchor, the main beam, the hub around which even ETL and transformation tools spin—has already started to break apart. And an idea like replacing the whole thing with dbt and some CSVs in Azure isn’t actually a deranged dive into some unhinged chaos; it may well be exactly where we’re headed. (View Highlight)

Certainly there were a ton of us in the data warehousing space at the time that were saying that it made no sense to use Hadoop for that purpose. (View Highlight)

no amount of Apache Impala and other band aids on top of Hadoop were ever going to match (View Highlight)