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Introduction to Data Warehousing

4.5+
12 reviews
Intermediate

This introductory and conceptual course will help you understand the fundamentals of data warehousing.

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4 Hours16 Videos57 Exercises
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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. Some have forecasted that the global data warehousing market is expected to reach over $50 billion in 2028. This industry has continued to evolve over the years and has been a critical component of the data revolution for many organizations. There has never been a better time to learn about data warehousing.
  1. 1

    Data Warehouse Basics

    Free

    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.

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    What is a data warehouse?
    50 xp
    Knowing the what and why
    50 xp
    Possible use cases for a data warehouse for Zynga
    50 xp
    What's the difference between data warehouses and data lakes?
    50 xp
    Data warehouses vs. data lakes
    100 xp
    Data warehouses vs. data marts
    50 xp
    Deciding between a data lake, warehouse, and mart
    50 xp
    Data warehouses support organizational analysis
    50 xp
    Data warehouse life cycle
    100 xp
    Support where needed
    50 xp
    Who does what?
    100 xp
  2. 2

    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.

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  3. 3

    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.

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Collaborators

Collaborator's avatar
Izzy Weber
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Arne Warnke
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Jess Ahmet

Prerequisites

Introduction to SQL
Aaren Stubberfield HeadshotAaren Stubberfield

Senior Data Scientist @ Microsoft

I am a Senior Data Scientist with expertise in Machine Learning, AI, and data governance. Currently, I work for Microsoft's Digital Advertising, which has revenues of more than $10 billion in the fiscal year 2023. However, my experience is not limited to just the advertising industry. I have worked in the Supply Chain and Data Governance industries. With my vast experience, I have led numerous teams of data scientists and have been instrumental in the successful completion of many projects. My technical skills include the use of AI, like LLMs, Python, and other various tools necessary for the execution of data science projects. My passion lies in using data to gain insights and making data-driven decisions. I constantly strive to improve my skills and knowledge and am always open to learning new techniques and tools.
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  • Benjamin M.
    8 months

    I am responsible for a data warehouse and needed a refresher on my basics for applying for a Data Engineer position. Good structure and presentation of the essential aspects. Integration of the most important roles. Focus on bottom-up very good. Helped me understand my current job even better Strong recommendation

  • Danielle F.
    6 days

    Excellent much better than mh college lectures

  • Alex M.
    about 2 months

    Excellent

  • Rob T.
    3 months

    Nice introduction to warehousing concepts.

  • K58 N.
    4 months

    Great course

"I am responsible for a data warehouse and needed a refresher on my basics for applying for a Data Engineer position. Good structure and presentation of the essential aspects. Integration of the most important roles. Focus on bottom-up very good. Helped me understand my current job even better Strong recommendation"

Benjamin M.

"Excellent much better than mh college lectures"

Danielle F.

"Excellent"

Alex M.

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