Buy, Build, or Bleed: Why the Data Stack Decision Is a False Binary

Every company serious about data runs the same play. Leadership asks whether the company can use its own data for marketing, AI, or basic health metrics. The answer is to hire data people. The data people need tooling, and at that moment the organization walks into a fork it treats as binary: buy the stack from a set of SaaS vendors, or build it in-house on the company's own cloud.
This talk walks that fork honestly, including the parts vendors and platform teams both tend to skip. The buy path is faster to start and fails on two axes: costs multiply as every capability that matters turns out to live behind an enterprise tier, and security teams eventually notice that company data is transiting four different vendors' clouds for reasons nobody can defend. The build path keeps the data at home and fails differently: three to six months to something barely usable, configuration that only one person understands, and brittleness that surfaces every time a version upgrade lands. Both paths share the same failure mode when they hit the wall, which is the most interesting part of the talk. Organizations double down. Buyers pay more for the enterprise tier. Builders hire more engineers to build and maintain. The pain gets medicated rather than diagnosed, and the loop repeats.
The closing argument is that the binary was never real. There is a third shape, where infrastructure is deployed and managed for you but runs inside your own cloud account, so the data never leaves and the operational burden never lands on your team. Chris will lay out what that model actually requires, what it costs, and where it does not fit, since it is not the right answer for everyone.

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Schedule:
6:30-6:45 pm: arrive, eat
6:45pm announcements
7:00pm - 7:45 speakers
7:45-8:30 pm networking