Microsoft Fabric: Working with Data Lakehouses

Microsoft Fabric 2024    |    Expert
  • 17 videos | 2h 12m 42s
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Microsoft Fabric's OneLake includes a data lakehouse that combines some of the most attractive features of data warehouses and data lakes. Heavily leveraging Delta tables as well as Apache Spark, it also adds the power of Power BI and Power Query. In this course, you'll explore data warehouses, comparing them with Azure Data Lake and Amazon S3. You'll build your first data lakehouse in Microsoft Fabric, running T-SQL queries, exploring parquet files and the delta log. You'll write SQL queries, construct visual queries and work with Spark notebooks, using PySpark and SparkSQL. After that, you'll study the Delta Lake architecture and its implementation as Delta tables. You'll explore data ingestion, including data pipelines, dataflows, and Spark notebooks. Finally, you'll create visual queries from the SQL analytics endpoint, learn about query folding, work with M-language expressions, and create and customize Power BI reports. This course is part of a series that prepares learners for Exam DP-600: Implementing Analytics Solutions Using Microsoft Fabric.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Define and enumerate attributes of structured, semi-structured and unstructured data
    Analyze features, benefits, drawbacks and important examples of data warehouses
    Enumerate important examples of data lakes and contrast them with data warehouses
    Analyze data lakehouses in relation to data warehouses and data lakes and determine microsoft fabric's place amid important data lakehouses
    Create a new workspace and a lakehouse within it
    Create a delta table from an uploaded file and examine the parquet files and delta log
    Run t-sql queries and visual queries on data in a delta table
    Create a spark notebook and use pyspark and sparksql to work with delta tables and files
  • Analyze features, benefits and drawbacks of data lakes
    Outline the architecture of a typical data lakehouse and analyze onelake and its constituent offerings, including data lakehouses, data warehouses, and kql databases
    Define and analyze the delta lake open-source storage layer and its implementation in the form of delta tables
    Specify methods of ingesting data into fabric lakehouses, including data pipelines, dataflows, spark notebooks, and the lakehouse explorer
    Create a visual query, view the equivalent t-sql, and open the visual query in the power query editor
    Examine query folding, how it is sometimes impossible to convert a visual query to t-sql, and how to add m-language steps to a visual query
    Create, customize and save power bi reports in a data lakehouse
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 9s
    In this video, you will discover the key concepts covered in this course. FREE ACCESS
  • 9m 6s
    Learn how to define and enumerate attributes of structured, semi-structured and unstructured data. FREE ACCESS
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    3.  Data Warehouses for Structured Data
    7m 49s
    In this video, discover how to analyze features, benefits, drawbacks and important examples of data warehouses. FREE ACCESS
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    4.  Data Lakes vs. Data Warehouses
    5m 1s
    During this video, you will learn how to enumerate important examples of data lakes and contrast them with data warehouses. FREE ACCESS
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    5.  Data Lakehouses
    9m 27s
    Find out how to analyze data lakehouses in relation to data warehouses and data lakes and determine Microsoft Fabric's place amid important data lakehouses. FREE ACCESS
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    6.  Creating a Data Lakehouse
    9m 12s
    Upon completion of this video, you will be able to create a new workspace and a lakehouse within it. FREE ACCESS
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    7.  Loading Data Into a Delta Table
    11m 2s
    During this video, you will learn how to create a delta table from an uploaded file and examine the parquet files and delta log. FREE ACCESS
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    8.  Running SQL Queries and Visual Queries
    6m 1s
    After completing this video, you will be able to run T-SQL queries and visual queries on data in a delta table. FREE ACCESS
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    9.  Creating Spark Notebooks and Data Lakehouses
    7m 45s
    In this video, you will learn how to create a spark notebook and use PySpark and SparkSQL to work with delta tables and files. FREE ACCESS
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    10.  Features, Benefits, and Drawbacks of Data Lakes
    8m 52s
    Discover how to analyze features, benefits and drawbacks of data lakes. FREE ACCESS
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    11.  OneLake in Microsoft Fabric
    7m 17s
    Learn how to outline the architecture of a typical data lakehouse and analyze OneLake and its constituent offerings, including data lakehouses, data warehouses, and KQL databases. FREE ACCESS
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    12.  Delta Lakes and Delta Tables
    8m 17s
    In this video, learn how to define and analyze the Delta Lake open-source storage layer and its implementation in the form of delta tables. FREE ACCESS
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    13.  Data Lakehouses in Microsoft Fabric
    6m 45s
    Discover how to specify methods of ingesting data into Fabric Lakehouses, including data pipelines, dataflows, Spark notebooks, and the Lakehouse explorer. FREE ACCESS
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    14.  Creating Visual Queries and Using Power Query Editor
    7m 31s
    Find out how to create a visual query, view the equivalent T-SQL, and open the visual query in the Power Query editor. FREE ACCESS
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    15.  Analyzing Query Folding and M-language Expressions
    12m 29s
    Learn how to examine query folding, how it is sometimes impossible to convert a visual query to T-SQL, and how to add M-language steps to a visual query. FREE ACCESS
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    16.  Creating Power BI Reports in a Lakehouse
    12m 1s
    After completing this video, you will be able to create, customize and save Power BI reports in a data lakehouse. FREE ACCESS
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    17.  Course Summary
    1m 59s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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