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Cloud Scale Analytics with Azure Data Services

You're reading from   Cloud Scale Analytics with Azure Data Services Build modern data warehouses on Microsoft Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781800562936
Length 520 pages
Edition 1st Edition
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Author (1):
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Patrik Borosch Patrik Borosch
Author Profile Icon Patrik Borosch
Patrik Borosch
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Data Warehousing and Considerations Regarding Cloud Computing
2. Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses FREE CHAPTER 3. Chapter 2: Connecting Requirements and Technology 4. Section 2: The Storage Layer
5. Chapter 3: Understanding the Data Lake Storage Layer 6. Chapter 4: Understanding Synapse SQL Pools and SQL Options 7. Section 3: Cloud-Scale Data Integration and Data Transformation
8. Chapter 5: Integrating Data into Your Modern Data Warehouse 9. Chapter 6: Using Synapse Spark Pools 10. Chapter 7: Using Databricks Spark Clusters 11. Chapter 8: Streaming Data into Your MDWH 12. Chapter 9: Integrating Azure Cognitive Services and Machine Learning 13. Chapter 10: Loading the Presentation Layer 14. Section 4: Data Presentation, Dashboarding, and Distribution
15. Chapter 11: Developing and Maintaining the Presentation Layer 16. Chapter 12: Distributing Data 17. Chapter 13: Introducing Industry Data Models 18. Chapter 14: Establishing Data Governance 19. Other Books You May Enjoy

Chapter 12: Distributing Data

After you have brought your data into your analytical environment and massaged it into the required shape, you may have even created machine learning models to acquire deeper insights into the circumstances that your data describes. Then, after loading it into the right storage for optimal access, you, of course, are now looking for ways to distribute the data in the right way to the right target groups.

This chapter will show you ways in which to create data marts to distribute insights in your modern data warehouse with Power BI. You will see how to use Power BI data models and the options to visualize and publish their content and even use the data with other tools.

Additionally, you will explore the options that you have to create a data model with Azure Analysis Services (AAS) aside from Power BI, that is, other options available to you to form insights from your data and make them available.

Finally, we will examine Azure Data Share as...

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