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  • Book Overview & Buying Scalable Data Analytics with Azure Data Explorer
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Scalable Data Analytics with Azure Data Explorer

Scalable Data Analytics with Azure Data Explorer

By : Jason Myerscough
4.8 (8)
Buy this Book
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Scalable Data Analytics with Azure Data Explorer

Scalable Data Analytics with Azure Data Explorer

4.8 (8)
By: Jason Myerscough
Buy this Book

Overview of this book

Azure Data Explorer (ADX) enables developers and data scientists to make data-driven business decisions. This book will help you rapidly explore and query your data at scale and secure your ADX clusters. The book begins by introducing you to ADX, its architecture, core features, and benefits. You'll learn how to securely deploy ADX instances and navigate through the ADX Web UI, cover data ingestion, and discover how to query and visualize your data using the powerful Kusto Query Language (KQL). Next, you'll get to grips with KQL operators and functions to efficiently query and explore your data, as well as perform time series analysis and search for anomalies and trends in your data. As you progress through the chapters, you'll explore advanced ADX topics, including deploying your ADX instances using Infrastructure as Code (IaC). The book also shows you how to manage your cluster performance and monthly ADX costs by handling cluster scaling and data retention periods. Finally, you'll understand how to secure your ADX environment by restricting access with best practices for improving your KQL query performance. By the end of this Azure book, you'll be able to securely deploy your own ADX instance, ingest data from multiple sources, rapidly query your data, and produce reports with KQL and Power BI.
Table of Contents (18 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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Code in Action
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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
1
Section 1: Introduction to Azure Data Explorer
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Section 1: Introduction to Azure Data Explorer
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Chapter 1: Introducing Azure Data Explorer
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Chapter 1: Introducing Azure Data Explorer
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Technical requirements
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Introducing the data analytics pipeline
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What is Azure Data Explorer?
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Azure Data Explorer use cases
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Running your first query
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Summary
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Chapter 2: Building Your Azure Data Explorer Environment
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Chapter 2: Building Your Azure Data Explorer Environment
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Technical requirements
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Creating an Azure subscription
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Introducing Azure Cloud Shell
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Creating and configuring ADX instances in the Azure portal
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Introducing Infrastructure as Code
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Creating and configuring ADX instances with PowerShell
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Creating ADX clusters with ARM templates
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Summary
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Questions
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Chapter 3: Exploring the Azure Data Explorer UI
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Chapter 3: Exploring the Azure Data Explorer UI
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Technical requirements
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Ingesting the StormEvents sample dataset
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Querying data in the Azure portal
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Exploring the ADX Web UI
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Summary
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Section 2: Querying and Visualizing Your Data
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Section 2: Querying and Visualizing Your Data
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Chapter 4: Ingesting Data in Azure Data Explorer
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Chapter 4: Ingesting Data in Azure Data Explorer
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Technical requirements
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Understanding data ingestion
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Introducing schema mapping
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Ingesting data using one-click ingestion
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Ingesting data using KQL management commands
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Ingesting data from Blob storage using Azure Event Grid
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Summary
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Questions
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Chapter 5: Introducing the Kusto Query Language
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Chapter 5: Introducing the Kusto Query Language
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Technical requirements
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What is KQL?
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Introducing the basics of KQL
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Introducing KQL's scalar operators
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Joining tables in KQL
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Introducing KQL's management commands
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Summary
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Questions
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Chapter 6: Introducing Time Series Analysis
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Chapter 6: Introducing Time Series Analysis
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Technical requirements
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What is time series analysis?
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Creating a time series with KQL
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Calculating statistics for time series data
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Summary
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Questions
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Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data
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Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data
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Technical requirements
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Calculating moving averages with KQL
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Trend analysis with KQL
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Anomaly detection and forecasting with KQL
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Summary
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Questions
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Chapter 8: Data Visualization with Azure Data Explorer and Power BI
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Chapter 8: Data Visualization with Azure Data Explorer and Power BI
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Technical requirements
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Introducing data visualization
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Creating dashboards with Azure Data Explorer
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Connecting Power BI to Azure Data Explorer
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Summary
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Questions
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Section 3: Advanced Azure Data Explorer Topics
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Section 3: Advanced Azure Data Explorer Topics
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Chapter 9: Monitoring and Troubleshooting Azure Data Explorer
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Chapter 9: Monitoring and Troubleshooting Azure Data Explorer
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Technical requirements
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Introducing monitoring and troubleshooting
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Monitoring ADX
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Troubleshooting ADX
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Summary
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Questions
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Chapter 10: Azure Data Explorer Security
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Chapter 10: Azure Data Explorer Security
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Technical requirements
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Introducing identity management
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Introducing virtual networking and subnet delegation
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Filtering traffic with NSGs
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Summary
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Questions
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Chapter 11: Performance Tuning in Azure Data Explorer
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Chapter 11: Performance Tuning in Azure Data Explorer
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Technical requirements
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Introducing performance tuning
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Introducing workload groups
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Introducing policy management
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Monitoring queries
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KQL best practices
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Summary
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Questions
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Chapter 12: Cost Management in Azure Data Explorer
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Chapter 12: Cost Management in Azure Data Explorer
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Technical requirements
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Scaling and cost management
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Selecting the correct ADX cluster SKU
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Introducing Azure Advisor
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Introducing Cost Management + Billing
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Summary
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Chapter 13: Assessment
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Chapter 1
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Chapter 2
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Chapter 4
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Chapter 5
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Chapter 6
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Chapter 7
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Chapter 8
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Chapter 9
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Chapter 10
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Chapter 11
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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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Chapter 1: Introducing Azure Data Explorer

Welcome to Scalable Data Analytics with Azure Data Explorer! More than 90% of today's data is digital and most of that data is considered unstructured, such as text messages and other forms of free text. So how can we analyze all our data? The answer is data analytics and Azure Data Explorer (ADX). Data analytics is a complex topic and Microsoft Azure provides a comprehensive selection of data analytics services, which can seem overwhelming when you are first starting your journey into data analytics.

In this chapter, we begin by introducing the data analytics pipeline and learning about each of the steps in the pipeline. These steps are required for taking raw data and producing reports and visuals as a result of your analysis, which will help you understand the workflow used by ADX.

Next, we will introduce some of the popular Azure data services and understand where they fit in the data analytics pipeline. Some of these services, such as Azure Event Hubs, will be used in later chapters when we learn about data ingestion.

We will also learn what ADX is, the features that make it a powerful data exploration platform, the architecture, and key components of ADX, such as the engine cluster, and understand some of the use cases for ADX, for example, in IoT monitoring, telemetry, and log analysis. Finally, we will get our feet wet and dive right into running your first Kusto Query Language (KQL) query using the Data Explorer UI.

In this chapter, we are going to cover the following main topics:

  • Introducing the data analytics pipeline
  • What is Azure Data Explorer?
  • Azure Data Explorer use cases
  • Running your first query
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