Data Engineering on Microsoft Azure: Designing the Serving Layer

Azure    |    Intermediate
  • 11 videos | 1h 11m 1s
  • Includes Assessment
  • Earns a Badge
Rating 4.6 of 41 users Rating 4.6 of 41 users (41)
The serving layer is where data is stored for consumption by processing services. In this course, you'll explore dimensional data modeling and hierarchies. You'll learn how to define slowly changing dimensions and temporal design within databases. Then, you'll learn about the differences between the star and snowflake schemas as well as how to design a star schema. Next, you'll examine incremental data loading for stream processing and the options for analytical data stores. Finally, you'll learn about options for creating metastores for use by Azure Databricks and Azure Synapse Analytics. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Recognize the concepts of dimensional data modeling
    Describe multidimensional data modeling dimensional hierarchies
    Describe slowly changing dimensions used to capture changing data over time, as well as the various types and their applications
    Describe temporal databases and steps for designing a database for temporalness
    Describe the differences between the star and snowflake schemes for data modeling
  • Recognize the rules and best practices to follow when designing a star schema
    Implement incremental data loading using azure data factory
    Select the appropriate technology for analytical data storage
    Describe the options for storing metadata external to azure synapse analytics and azure databricks
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 31s
  • 10m
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    3.  Dimensional Hierarchies
    5m 57s
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    4.  Slowly Changing Dimensions
    6m 59s
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    5.  Temporal Design
    5m 54s
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    6.  Star and Snowflake Schemas
    11m 9s
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    7.  Designing a Star Schema
    5m 16s
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    8.  Implementing Incremental Data Loading
    10m 11s
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    9.  Choosing an Analytical Data Store
    8m 7s
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    10.  Metastore Design
    5m 4s
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    11.  Course Summary
    53s
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