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Microsoft Fabric Data Flows and Data Storage

Microsoft Fabric Data Flows and Data Storage

1h 45mIntermediate2024-01-19

Authors

Ginger Grant

Ginger Grant

Course details

Microsoft Fabric is an integrated cloud data environment that includes data lakehouses, data warehousing, data transformation, and machine learning. Explore the different components of data in Microsoft Fabric as well as how to get started organizing data lakes, developing and managing data factory pipelines, and implementing data engineering solutions with third-party notebooks, Python, and Spark. Instructor Ginger Grant also shows you how to secure data stored in one lake and in data lakes within Microsoft Fabric.

This course is designed for analytics professionals with data and dimensional modeling experience who are interested in learning how Microsoft Fabric can be applied to enterprise data environments.

Skills covered

Microsoft FabricCloud StorageEnterprise Content ManagementBusiness AnalysisProject ManagementNetwork and System AdministrationCloud ComputingBusiness Analysis and StrategyMicrosoftOne-Off

Concepts

0. Introduction

  • 01 - Implementing Microsoft Fabric
  • 02 - What you should know
  • 03 - Course data configuration

1. Introducing Microsoft Fabric

  • 04 - Microsoft Fabric overview
  • 05 - Microsoft Fabric environment
  • 06 - Microsoft Fabric data component review
  • 07 - Compute engines in Microsoft Fabric
  • 08 - Challenge - Examining the lakehouse
  • 09 - Solution - Examining the lakehouse

2. Data Organization in Microsoft Fabric

  • 10 - OneLake architecture
  • 11 - Data organization
  • 12 - Adding data to OneLake
  • 13 - Using data wrangling to examine your data
  • 14 - Challenge - Creating and using pipelines
  • 15 - Solution - Creating and using pipelines

3. Security in Fabric

  • 16 - Fabric security overview
  • 17 - Workspace permissions and access
  • 18 - Fabric compute
  • 19 - Challenge - Implementing database roles
  • 20 - Solution - Implementing database roles

4. Integrating OneLake with Power BI

  • 21 - OneLake and Power BI data modeling
  • 22 - Data transformation with dataflows
  • 23 - Using SQL endpoints
  • 24 - Using AI with Power BI

Conclusion

  • 25 - Further your knowledge with Fabric

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