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Scalable Data Analytics with Azure Data Explorer

Scalable Data Analytics with Azure Data Explorer


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.

  • Scalable Data Analytics with Azure Data Explorer
  • Foreword
  • Contributors
  • About the author
  • About the reviewers
  • Preface
    • Who this book is for
    • What this book covers
    • To get the most out of this book
    • Download the example code files
    • Code in Action
    • Download the color images
    • Conventions used
    • Get in touch
    • Share Your Thoughts
  • Section 1: Introduction to Azure Data Explorer
  • Chapter 1: Introducing Azure Data Explorer
    • Technical requirements
    • Introducing the data analytics pipeline
      • Overview of Azure data analytics services
    • What is Azure Data Explorer?
      • ADX features
      • Introducing Azure Data Explorer architecture
    • Azure Data Explorer use cases
      • IoT monitoring and telemetry
      • Log analysis
    • Running your first query
    • Summary
  • Chapter 2: Building Your Azure Data Explorer Environment
    • Technical requirements
    • Creating an Azure subscription
    • Introducing Azure Cloud Shell
    • Creating and configuring ADX instances in the Azure portal
    • Introducing Infrastructure as Code
    • Creating and configuring ADX instances with PowerShell
    • Creating ADX clusters with ARM templates
      • ARM template structure
      • Parameters
      • Variables
      • Resources
      • Deploying our templates
    • Summary
    • Questions
  • Chapter 3: Exploring the Azure Data Explorer UI
    • Technical requirements
    • Ingesting the StormEvents sample dataset
    • Querying data in the Azure portal
    • Exploring the ADX Web UI
    • Summary
  • Section 2: Querying and Visualizing Your Data
  • Chapter 4: Ingesting Data in Azure Data Explorer
    • Technical requirements
    • Understanding data ingestion
    • Introducing schema mapping
    • Ingesting data using one-click ingestion
    • Ingesting data using KQL management commands
    • Ingesting data from Blob storage using Azure Event Grid
      • Enabling streaming on ADX
      • Creating our table and JSON mapping schema
      • Creating our storage account
      • Creating our event hub
      • Creating our Event Grid
      • Ingesting data in ADX
    • Summary
    • Questions
  • Chapter 5: Introducing the Kusto Query Language
    • Technical requirements
    • What is KQL?
    • Introducing the basics of KQL
      • Introducing predicates
      • Searching and filtering data
      • Aggregating data and tables
      • Formatting output
      • Generating graphs in the ADX Web UI
      • Converting SQL to KQL
    • Introducing KQLs scalar operators
      • Arithmetic operators
      • Logical operators
      • Relational operators
      • String operators
      • Date and time operators
    • Joining tables in KQL
    • Introducing KQL's management commands
      • Cluster management
      • Database and table management
    • Summary
    • Questions
  • Chapter 6: Introducing Time Series Analysis
    • Technical requirements
    • What is time series analysis?
    • Creating a time series with KQL
      • Introducing the helper operators and functions
      • Generating time series data
    • Calculating statistics for time series data
    • Summary
    • Questions
  • Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data
    • Technical requirements
    • Calculating moving averages with KQL
    • Trend analysis with KQL
      • Applying linear regression with KQL
      • Applying segmented regression with KQL
    • Anomaly detection and forecasting with KQL
      • Anomaly detection
      • Forecasting for the future
    • Summary
    • Questions
  • Chapter 8: Data Visualization with Azure Data Explorer and Power BI
    • Technical requirements
    • Introducing data visualization
    • Creating dashboards with Azure Data Explorer
      • Navigating the dashboard window
      • Building our first Data Explorer dashboard
      • Sharing dashboards
      • Creating dashboard filters
    • Connecting Power BI to Azure Data Explorer
    • Summary
    • Questions
  • Section 3: Advanced Azure Data Explorer Topics
  • Chapter 9: Monitoring and Troubleshooting Azure Data Explorer
    • Technical requirements
    • Introducing monitoring and troubleshooting
    • Monitoring ADX
      • Azure Service Health
      • ADX metrics
      • ADX diagnostics
      • Alerting in Azure
    • Troubleshooting ADX
      • Creating a new data connection
      • Ingesting data to simulate an error
      • Observing and troubleshooting ADX
      • Configuring alerts for ingestion failures
    • Summary
    • Questions
  • Chapter 10: Azure Data Explorer Security
    • Technical requirements
    • Introducing identity management
      • Introducing RBAC and the management and data planes
      • Granting access to the management plane
      • Granting access to the data plane
    • Introducing virtual networking and subnet delegation
      • Creating a new resource group
      • Deploying the NSG
      • Deploying the route table
      • Deploying the virtual network
      • Deploying the public IP addresses
      • Deploying the ADX cluster
    • Filtering traffic with NSGs
      • Introducing NSGs
      • Creating inbound security rules
    • Summary
    • Questions
  • Chapter 11: Performance Tuning in Azure Data Explorer
    • Technical requirements
    • Introducing performance tuning
    • Introducing workload groups
      • How workload groups work
      • Creating custom workload groups
    • Introducing policy management
      • Managing the cache policy
      • Managing retention policies
    • Monitoring queries
    • KQL best practices
      • Version controlling your queries
      • Prioritizing time filtering
      • Best practices for string operators
    • Summary
    • Questions
  • Chapter 12: Cost Management in Azure Data Explorer
    • Technical requirements
    • Scaling and cost management
    • Selecting the correct ADX cluster SKU
      • Introducing dev/test clusters
      • Introducing production clusters
    • Introducing Azure Advisor
    • Introducing Cost Management + Billing
      • Accessing invoices
      • Configuring budget alerts
    • Summary
  • Chapter 13: Assessment
    • Chapter 1
    • Chapter 2
    • Chapter 4
    • Chapter 5
    • Chapter 6
    • Chapter 7
    • Chapter 8
    • Chapter 9
    • Chapter 10
    • Chapter 11
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