The Pendulums of Data

Data EngineeringModern Data StackIndustry CommentaryAI & LLMs

Joe Reis argues that the data industry doesn't progress linearly but oscillates between recurring tensions—centralized vs. decentralized, batch vs. real-time, governance vs. self-service—like pendulums in a feedback system. Each winning idea solves a real problem but gets overextended until its downsides become obvious, causing the pendulum to swing back. The key insight is that the pendulum never returns to the same place; each cycle leaves behind new infrastructure and capabilities, making it more like a pendulum attached to a ratchet.

Data industry trends are feedback systems—every winning paradigm eventually creates the conditions for its own backlash, so the smarter move is to ask what tension a new idea temporarily resolves and where the next swing will begin when it succeeds too well.
  • 6

    The data industry doesn't move in a straight line. It moves through a collection of pendulums.

  • 6

    The feedback loop looks something like this: centralize until you create bottlenecks, decentralize until you create fragmentation, standardize to deal with the fragmentation, and then recentralize the things that are difficult to coordinate independently.

  • 8

    Sometimes technology just gets us to the same old problem much faster. If we're enlightened, we treat this fast feedback loop as a way to get ourselves out of a hole. More likely, we use the fast feedback loop to dig an even deeper hole.

  • 7

    Every architecture eventually becomes its own counterforce. An idea's success creates the conditions for backlash.

  • 6

    Maybe the better mental model is a pendulum attached to a ratchet. We oscillate between recurring tensions while the underlying capability frontier continues moving forward.

reflective, analytical