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Cloud Scale Analytics with Azure Data Services

You're reading from Cloud Scale Analytics with Azure Data Services

Product type Book

Published in Jul 2021

Publisher Packt

ISBN-13 9781800562936

Pages 520 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Patrik Borosch

Table of Contents (20) Chapters

Preface

Section 1: Data Warehousing and Considerations Regarding Cloud Computing

Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses

Chapter 2: Connecting Requirements and Technology

Section 2: The Storage Layer

Chapter 3: Understanding the Data Lake Storage Layer

Chapter 4: Understanding Synapse SQL Pools and SQL Options

Section 3: Cloud-Scale Data Integration and Data Transformation

Chapter 5: Integrating Data into Your Modern Data Warehouse

Chapter 6: Using Synapse Spark Pools

Chapter 7: Using Databricks Spark Clusters

Chapter 8: Streaming Data into Your MDWH

Chapter 9: Integrating Azure Cognitive Services and Machine Learning

Chapter 10: Loading the Presentation Layer

Section 4: Data Presentation, Dashboarding, and Distribution

Chapter 11: Developing and Maintaining the Presentation Layer

Chapter 12: Distributing Data

Chapter 13: Introducing Industry Data Models

Chapter 14: Establishing Data Governance

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Further reading

Discovering Power BI:
Power BI data sources:
The calculate() DAX function:

DAX formula to filter ad_noofflights for the first of the month:

FirstofMonthSum = calculate(sum(Query1[ad_noofflights]), Query1[ad_dayofmonth]=1)

DAX deep dive readings:
a) Alberto Ferrari, Marco Russo, and Daniele Perilli:
b) Chris Webb's BI blog:
c) Adam Saxton, aka Guy in a Cube:
d) DAX reference documentation:
Data model optimization:
Differences between Power BI and Azure Analysis Services:
Data Share source-to-target mapping:
Azure Data Share: https://docs.microsoft.com/en-us/azure/data-share/overview

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Authors (1)

Patrik Borosch

Patrik Borosch is a cloud solution architect for data and AI at Microsoft Switzerland GmbH. He has more than 25 years of BI and analytics development, engineering, and architecture experience and is a Microsoft Certified Data Engineer and a Microsoft Certified AI Engineer. Patrik has worked on numerous significant international data warehouse, data integration, and big data projects. Through this, he has built and extended his experience in all facets, from requirements engineering to data modeling and ETL, all the way to reporting and dashboarding. At Microsoft Switzerland, he supports customers in their journey into the analytical world of the Azure Cloud.

Read more

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