Introduction to Data Warehousing
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This introductory and conceptual course will help you understand the fundamentals of data warehousing.
Course Description
This introductory and conceptual course will help you understand the fundamentals of data warehousing. You’ll gain a strong understanding of data warehousing basics through industry examples and real-world datasets.
What You’ll Learn
Data Warehouse Basics
Prepare for your data warehouse learning journey by grounding yourself in some foundational concepts. To begin this course, you’ll learn what a data warehouse is and how it compares and contrasts to similar-sounding technologies, data marts and data lakes. You’ll also learn how different personas help support the various stages of a data warehouse project.
Data Warehouse Data Modeling
Here, you’ll learn how to organize the data in your data warehouse with an excellent data model. First, you’ll cover the basics of data modeling by learning what a fact and a dimension table are and how you use them in the star and snowflake schemes. Then, you’ll review how to create a data model using Kimball’s four-step process and how to deal with slowly changing dimensions.
Warehouse Architectures and Properties
In chapter two, you’ll gain a better understanding of data warehouse architecture by learning the typical layers of a data warehouse and how the presentation layer supports analysts. Additionally, you’ll learn about Bill Inmon and his top-down approach and how it compares to Ralph Kimball and his bottom-up approach. Finally, you’ll understand the difference between OLAP and OLTP systems.
Implementation and Data Prep
You’ll wrap up the course by learning the pros and cons of ETL and ELT processes and on-premise versus an in-cloud implementation. You’ll conclude by walking through an example, making key decisions on warehouse design and implementation.
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