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Apply SCD2 to Build Dynamic Data Models

本课程是 Pipeline Architects: Data Engineering to Lakehouse 专项课程的一部分

位教师：Hurix Digital

包含在中

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2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Historical data preservation is essential for accurate business analytics and regulatory compliance - once overwritten, critical context is lost.
SCD2 patterns create sustainable data architecture by maintaining complete audit trails through automated versioning than destructive updates.
Effective dimensional modeling requires systematic change detection logic that identifies modifications and creates new historical records.
Modern data tools like dbt democratize complex SCD2 implementation, making enterprise-grade historical tracking accessible through declarative SQL.

您将获得的技能

要了解的详细信息

可分享的证书

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了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Pipeline Architects: Data Engineering to Lakehouse 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有2个模块

Did you know that without historical data tracking, over 40% of business insights can become inaccurate or misleading? Implementing Slowly Changing Dimension (SCD) Type 2 ensures every change in your data tells the full story over time.

This Short Course was created to help professionals in this field implement robust historical data tracking systems that maintain complete audit trails and support accurate trend analysis in enterprise data warehouses. By completing this course, you will be able to apply SCD Type 2 logic to build dynamic data models that capture historical changes, enabling reliable reporting, timebased analysis, and improved business intelligence accuracy. By the end of this 3hour long course, you will be able to: Apply slowlychanging dimension (SCD) Type 2 logic to build data models that track historical changes. This course is unique because it connects data modeling theory with practical warehouse implementation, giving you the skills to design scalable, auditready models that preserve data integrity across time. To be successful in this project, you should have: Basic SQL knowledge Understanding of data modeling concepts Familiarity with dbt fundamentals Data warehouse basics

单元详情

Learners will understand the fundamental concepts of SCD2 logic and begin applying these principles to create data models that preserve historical context in enterprise data warehouses.

涵盖的内容

3个视频1篇阅读材料1个作业1个非评分实验室

3个视频总计14分钟

Why SCD2 Matters in Enterprise Data Warehouses4分钟
Understanding SCD2 Core Components and Business Logic 7分钟
Building Your First SCD2 Table Structure in SQL4分钟

1篇阅读材料总计8分钟

SCD2 Implementation Patterns and Data Model Design8分钟

1个作业总计3分钟

SCD2 Fundamentals Knowledge Check3分钟

1个非评分实验室总计20分钟

Build Historical Data Models with SCD2 Logic20分钟

Learners will implement productionready SCD2 models using dbt, creating automated historical tracking systems with proper change detection, validity periods, and current status management.