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Learn Microsoft Fabric

You're reading from   Learn Microsoft Fabric A practical guide to performing data analytics in the era of artificial intelligence

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781835082287
Length 338 pages
Edition 1st Edition
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Authors (2):
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Bradley Schacht Bradley Schacht
Author Profile Icon Bradley Schacht
Bradley Schacht
Arshad Ali Arshad Ali
Author Profile Icon Arshad Ali
Arshad Ali
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Table of Contents (19) Chapters Close

Preface 1. Part 1: An Introduction to Microsoft Fabric FREE CHAPTER
2. Chapter 1: Overview of Microsoft Fabric and Understanding Its Different Concepts 3. Chapter 2: Understanding Different Workloads and Getting Started with Microsoft Fabric 4. Part 2: Building End-to-End Analytics Systems
5. Chapter 3: Building an End-to-End Analytics System – Lakehouse 6. Chapter 4: Building an End-to-End Analytics System – Data Warehouse 7. Chapter 5: Building an End-to-End Analytics System – Real-Time Analytics 8. Chapter 6: Building an End-to-End Analytics System – Data Science 9. Part 3: Administration and Monitoring
10. Chapter 7: Monitoring Overview and Monitoring Different Workloads 11. Chapter 8: Administering Fabric 12. Part 4: Security and Developer Experience
13. Chapter 9: Security and Governance Overview 14. Chapter 10: Continuous Integration and Continuous Deployment (CI/CD) 15. Part 5: AI Assistance with Copilot Integration
16. Chapter 11: Overview of AI Assistance and Copilot Integration 17. Index 18. Other Books You May Enjoy

Orchestrating ETL operations with Data Factory pipelines

Data Factory pipelines are an extremely useful tool in analytics projects. Earlier in this chapter, you created a data pipeline that runs a Copy data activity to load the stage.DimCity table. This data was later used in a stored procedure to load a dimensional model table called dbo.DimCity. It is now time to extend the pipeline to orchestrate the entire ETL process, which will include the following:

  1. Dropping and recreating all stage schema tables so that data is not duplicated from prior runs
  2. Loading the stage.DimCity table using the Copy data activity
  3. Loading the stage.DimDate and stage.FactSale tables using the T-SQL COPY command by executing a stored procedure
  4. Incrementally loading the dimensional model using a stored procedure

Let’s extend the pipeline created earlier in the chapter:

  1. Return to the pipeline created in the Loading data section earlier in the chapter by navigating to...
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