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

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781800562936

Length 520 pages

Edition 1st Edition

Tools

Azure

Concepts

Data Streaming

Author (1):

Patrik Borosch

View More author details

Table of Contents (20) Chapters

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

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Understanding the supporting services

Regardless of the size you are planning for, some services might catch your attention anyway. This section will give you an overview of the supporting services that you might need in your modern data warehouse approach.

Requiring data governance

When you start building your modern data warehouse, there is one thing that you need to get right: data governance! There are too many data lakes out there that have mutated into data swamps, and you'll find so many Data Warehouses that have lost any credibility because their users can't find the right data or are only able to find outdated information. The relationship between these data sources might not be clear to self-service BI users if they produce the wrong figures. Plus, dimension data, which describes the measures that you want to report on, might not be up to date or might rely on the wrong sources. Alternatively, your users might not be able to recognize the date and time of...