Forget MVPs and sprint velocity — you’re not launching apps, you’re running a factory.
🚫 Agile playbooks don’t map 1:1 to data work.
Why? Because a broken dataset breaks everything downstream — no second chances, no “we’ll patch it later.”
💡 What still trips up teams:
• Shipping “half a pipeline” — it’s useless until complete
• One-column-per-sprint logic — busywork that delivers no value
• Tests that pass cleanly... until real production data hits
• Security so strict, engineers can’t inspect anomalies before access times out
🛠️ What actually works now:
• Up-front discovery instead of endless rework
• Assigning one owner per pipeline — not three hands guessing
• Accepting that data needs a touch of waterfall: plan well or pay in backfills
• Building for replayability — business wants time-travel analytics, not excuses
📦 Data pipelines aren’t shopfronts. They’re industrial systems.
They don’t delight — they deliver. Or they fail.
If your team builds data like product features, you’ll ship dashboards full of fiction.
Build like engineers — and your business will trust what comes out the other end.
👇 Full breakdown here (вставьте ссылку вручную)
👏 If this resonates — clap, follow, and stay tuned for more lessons from the pipeline room.
https://blog.det.life/building-data-pipelines-in-2025-different-rules-different-game-be48fa8b1d51
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