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</span><a href="/2021/05/24/Kafka%E5%B8%B8%E7%94%A8%E5%91%BD%E4%BB%A4/" class="post-title-link" itemprop="url">Kafka 常用命令</a>
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<p>Kafka 的常用命令整理</p>
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<a href="/2022/05/15/%E6%95%B0%E6%8D%AE%E4%B8%AD%E5%8F%B0_%E7%BB%93%E6%9D%9F%E8%AF%AD-%E6%95%B0%E6%8D%AE%E4%B8%AD%E5%8F%B0%E4%BB%8E%E5%93%AA%E9%87%8C%E6%9D%A5%EF%BC%8C%E8%A6%81%E5%88%B0%E5%93%AA%E9%87%8C%E5%8E%BB/" class="post-title-link" itemprop="url">数据中台_结束语-数据中台从哪里来，要到哪里去</a>
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还记得在 03 讲数据中台建设的三板斧中，关于组织关系，我曾经说过，数据中台的团队必须独立于业务部门，同时又不能脱离业务。
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从 OneData 到 OneService、从方法论到支撑技术、从宏观架构到微观实现，我已经带你系统地了解了建设数据中台的所有核心知识点。你可以看到，虽然人人都在讨论数据中台，但是真的实战起来，还是不简单吧？
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上一篇，我们了解了数据研发的四个阶段，你可以发现，标准化的研发流程对交付高效、高质量的数据来说非常关键。那么数据被加工好以后，怎么使用数据和管理数据就是重点了。
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到现在，已经介绍了 10 几个数据中台的工具产品，除此之外，我还提到了数据产品、数据架构师、数据开发、应用开发、分析师……多个角色。既然数据中台要用到这么多工具，又涉及这么多角色，如果没有配套的协同流程和规范，那也没办法达到数据中台高效、高质量、低成本的建设目标。来看几件有意思的事儿。
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