Scalable Data Analytics with Azure Data Explorer: Modern ways to query, analyze, and perform real-time data analysis on large volumes of data
- Length: 364 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2022-03-17
- ISBN-10: 1801078548
- ISBN-13: 9781801078542
- Sales Rank: #277556 (See Top 100 Books)
Write efficient and powerful KQL queries to query and visualize your data and implement best practices to improve KQL execution performance
Key Features
- Apply Azure Data Explorer best practices to manage your data at scale and reduce KQL execution time
- Discover how to query and visualize your data using the powerful KQL
- Manage cluster performance and monthly costs by understanding how to size your ADX cluster correctly
Book Description
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.
What you will learn
- Become well-versed with the core features of the Azure Data Explorer architecture
- Discover how ADX can help manage your data at scale on Azure
- Get to grips with deploying your ADX environment and ingesting and analyzing your data
- Explore KQL and learn how to query your data
- Query and visualize your data using the ADX UI and Power BI
- Ingest structured and unstructured data types from an array of sources
- Understand how to deploy, scale, secure, and manage ADX
Who this book is for
This book is for data analysts, data engineers, and data scientists who are responsible for analyzing and querying their team’s large volumes of data on Azure. SRE and DevOps engineers who deploy, maintain, and secure infrastructure will also find this book useful. Prior knowledge of Azure and basic data querying will help you to get the most out of this book.
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 KQL's 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 Why subscribe? 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