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Data Warehousing Concepts

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

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4 horas16 vídeos57 exercícios21.793 aprendizesTrophyDeclaração de Realização

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Descrição do Curso

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.
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  1. 1

    Data Warehouse Basics

    Gratuito

    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.

    Reproduzir Capítulo Agora
    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

    Now, 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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Nas seguintes faixas

Engenheiro de dados associado em SQL

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colaboradores

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Izzy Weber
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Arne Warnke
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Jess Ahmet

pré-requisitos

Introduction to SQL
Aaren Stubberfield HeadshotAaren Stubberfield

Senior Data Scientist @ Microsoft

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