---
title: "Best practices that break data platforms"
url: https://daily.dev/posts/best-practices-that-break-data-platforms-nnk2zbvpe
source_url: https://www.datasciencecentral.com/best-practices-that-break-data-platforms/
type: article
source: "Data Science Central"
published: 2025-10-22T16:02:56.964Z
updated: 2025-10-22T16:03:19.434Z
tags: ["big-data", "data-engineering", "data-architecture"]
reading_time: 12
upvotes: 0
comments: 0
language: en
---

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# Best practices that break data platforms

**[Data Science Central](https://daily.dev/sources/ds_central)** · 12 min read · 0 upvotes · 0 comments

## Summary

Traditional data engineering best practices like centralizing all data, granting full pipeline autonomy, and relying on role-based access control are becoming counterproductive in modern cloud-native environments. Industry leaders argue for intent-driven pipelines that start with business outcomes, centralized ingestion layers with decentralized transformation, and dynamic governance models that scale beyond manual role management. The shift requires moving from rigid dogma to first-principles thinking, prioritizing purposeful data collection over hoarding, and choosing scalable open-source solutions over expensive enterprise tools that create vendor lock-in.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.datasciencecentral.com/best-practices-that-break-data-platforms/>

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---

Tags: [#big-data](https://daily.dev/tags/big-data), [#data-engineering](https://daily.dev/tags/data-engineering), [#data-architecture](https://daily.dev/tags/data-architecture)

[View this post on daily.dev](https://daily.dev/posts/best-practices-that-break-data-platforms-nnk2zbvpe)