Wrap-up

Data Warehousing Concepts

Aaren Stubberfield

Data Scientist

What we covered - Chapter 1

Data Warehouse Basics

  • What is a data warehouse?
  • Data warehouse life-cycle
  • Comparing to data lakes and marts

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Data Warehousing Concepts

What we covered - Chapter 2

Warehouse architectures and properties

  • Warehouse layers
  • Inmon vs Kimball designs
  • OLAP and OLTP systems

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Data Warehousing Concepts

What we covered - Chapter 3

Data warehouse data modeling

  • Fact and dimension tables
  • Slowly changing dimensions
  • Row / column store
  • Kimball's four-step process

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Data Warehousing Concepts

What we covered - Chapter 4

Data cleaning and other considerations

  • ETL / ELT processes
  • Data cleaning
  • On-premises / in the cloud implementations

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Data Warehousing Concepts

Things we didn't cover

  • SQL fundamentals
  • Building data pipelines
  • Analyzing warehouse data
Data Warehousing Concepts

Learning more

Books:

  • The Data Warehouse Toolkit, Third Edition: The Definitive Guide to Dimensional Modeling (by Kimball)
  • Building the Data Warehouse (by Inmon)
  • DAMA - Data Management Body of Knowledge (by DAMA International)

DataCamp courses:

  • Understanding Data Engineering
  • Introduction to Power BI
  • Intermediate SQL Server
Data Warehousing Concepts

Good bye and thank you!

Data Warehousing Concepts

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