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Data Modeling Strategies - Mandarin Chinese

本课程引导从业者全面了解 Databricks Data Intelligence Platform 上的各类数据建模方法——从经典数据仓库技术(Inmon、Kimball、Data Vault 2.0),到基于 特征存储 驱动的 ML 应用场景,再到通过 Unity Catalog 上的数据产品实现数据产品化。


每种建模方法均先通过讲座进行介绍,再结合共享数据集(TPC-H 样本)进行实操演示加以巩固。课程最后设有一个综合性端到端实验室,在单一集成工作流中涵盖 ERM、维度建模、Data Vault 2.0 及特征存储的综合练习。


注意:对于 SCORM 讲座文件,请确保在完成内容后关闭 SCORM 窗口。请勿点击‘Next Lesson’按钮,否则 SCORM 模块可能无法标记为已完成。


Languages Available: English | 日本語 | Português BR| 한국어 | 

Skill Level
Associate
Duration
2h
Prerequisites

本课程的内容是为具备以下技能、知识和能力的学员开发的:

• 具备 SQL 和关系数据库概念的基础知识

• 熟悉 Databricks 基础知识(Workspaces、Notebooks、Unity Catalog 基础)

• 对 OLTP 与 OLAP 以及金银铜架构有概念性了解

• 具备 Python 和 PySpark 的基本使用经验有所帮助,但非必需

• 了解维度建模概念有所帮助,但非必需

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