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  • Book Overview & Buying Learn Azure Synapse Data Explorer
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Learn Azure Synapse Data Explorer

Learn Azure Synapse Data Explorer

By : Pericles Rocha
5 (12)
Buy this Book
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Learn Azure Synapse Data Explorer

Learn Azure Synapse Data Explorer

5 (12)
By: Pericles Rocha
Buy this Book

Overview of this book

Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data. This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you’ll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you’ll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users. By the end of this book, you’ll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.
Table of Contents (19 chapters)
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Preface
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Preface
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Who this book is for
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What this book covers
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To get the most out of this book
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Download the example code files
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Download the color images
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Conventions used
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Get in touch
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Share Your Thoughts
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1
Part 1 Introduction to Azure Synapse Data Explorer
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Part 1 Introduction to Azure Synapse Data Explorer
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2
Chapter 1: Introducing Azure Synapse Data Explorer
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Chapter 1: Introducing Azure Synapse Data Explorer
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Technical requirements
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Understanding the lifecycle of data
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The need for a fast and highly scalable data exploration service
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What is Azure Synapse?
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What is Azure Synapse Data Explorer?
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Integrating Data Explorer pools with other Azure Synapse services
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Exploring the Data Explorer pool infrastructure and scalability
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What makes Azure Synapse Data Explorer unique?
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When to use Azure Synapse Data Explorer
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Summary
3
Chapter 2: Creating Your First Data Explorer Pool
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Chapter 2: Creating Your First Data Explorer Pool
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Technical requirements
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Creating a free Azure account
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Creating an Azure Synapse workspace
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Creating a Data Explorer pool using Azure Synapse Studio
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Creating a Data Explorer pool using the Azure portal
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Creating a Data Explorer pool using the Azure CLI
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Summary
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Chapter 3: Exploring Azure Synapse Studio
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Chapter 3: Exploring Azure Synapse Studio
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Technical requirements
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Exploring the user interface of Azure Synapse Studio
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Running your first query
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Managing and monitoring Data Explorer pools
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Monitoring Data Explorer pools
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Summary
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Chapter 4: Real-World Usage Scenarios
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Chapter 4: Real-World Usage Scenarios
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Technical requirements
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Building a multi-purpose end-to-end analytics environment
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Managing IoT data
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Processing and analyzing geospatial data
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Enabling real-time analytics with big data
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Performing time series analytics
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Summary
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Part 2 Working with Data
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Part 2 Working with Data
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Chapter 5: Ingesting Data into Data Explorer Pools
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Chapter 5: Ingesting Data into Data Explorer Pools
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Technical requirements
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Understanding the data loading process
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Defining a retention policy
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Choosing a data load strategy
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Performing data ingestion
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Summary
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Chapter 6: Data Analysis and Exploration with KQL and Python
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Chapter 6: Data Analysis and Exploration with KQL and Python
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Technical requirements
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Analyzing data with KQL
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Exploring Data Explorer pool data with Python
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Summary
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Chapter 7: Data Visualization with Power BI
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Chapter 7: Data Visualization with Power BI
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Technical requirements
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Introduction to the Power BI integration
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Creating a Power BI report
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Adding data sources to your Power BI report
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Connecting Power BI with your Azure Synapse workspace
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Authoring Power BI reports from Azure Synapse Studio
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Summary
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Chapter 8: Building Machine Learning Experiments
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Chapter 8: Building Machine Learning Experiments
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Technical requirements
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Understanding the application of ML
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Introducing ML into your projects with AutoML
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Exploring additional ML capabilities in Azure Synapse
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Summary
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Chapter 9: Exporting Data from Data Explorer Pools
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Chapter 9: Exporting Data from Data Explorer Pools
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Technical requirements
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Understanding data export scenarios
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Exporting data with client tools
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Using server-side export to pull data
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Performing robust exports with server-side data push
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Configuring continuous data export
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Summary
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Part 3 Managing Azure Synapse Data Explorer
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Part 3 Managing Azure Synapse Data Explorer
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Chapter 10: System Monitoring and Diagnostics
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Chapter 10: System Monitoring and Diagnostics
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Technical requirements
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Monitoring your environment
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Setting up alerts
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Summary
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Chapter 11: Tuning and Resource Management
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Chapter 11: Tuning and Resource Management
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Technical requirements
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Implementing resource governance with workload groups
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Speeding up queries using cache policies
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Summary
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Chapter 12: Securing Your Environment
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Chapter 12: Securing Your Environment
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Technical requirements
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Security overview
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Managing data encryption
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Authenticating users
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Configuring access to resources
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Implementing network security
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Protecting against external threats
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Summary
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Chapter 13: Advanced Data Management
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Chapter 13: Advanced Data Management
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Technical requirements
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Managing extents
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Purging personal data
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Summary
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Index
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Index
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Why subscribe?
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Other Books You May Enjoy
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Other Books You May Enjoy
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Packt is searching for authors like you
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Summary

Azure Synapse Data Explorer brings all the innovation that was built into the standalone service Azure Data Explorer into Azure Synapse. By using Data Explorer pools in Azure Synapse, you can correlate data from several different sources, residing on different analytical engines, to get a 360-degree view of all your data and unlock insights.

In this chapter, you learned about the lifecycle of data, the TDSP, and how Data Explorer fits into the analytics landscape. We explored the key components of Azure Synapse and Azure Synapse Data Explorer, and how Data Explorer pools benefit from integration with other Azure Synapse services such as Apache Spark.

Next, you learned about the infrastructure of Data Explorer pools and how they deliver massive scalability. We looked at the service architecture and how Data Explorer pools manage data in a distributed cluster. We also explored the mission-critical features of Azure Synapse Data Explorer that give the trust enterprises need to adopt the solution.

Finally, we discussed what makes Azure Synapse Data Explorer unique when compared to the standalone service Azure Data Explorer, and how to determine whether Azure Synapse Data Explorer is the right solution for you.

In the next chapter, we will explore how to create an Azure Synapse workspace and a Data Explorer pool.

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