Book Image

Scalable Data Analytics with Azure Data Explorer

By : Jason Myerscough
Book Image

Scalable Data Analytics with Azure Data Explorer

By: Jason Myerscough

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)
1
Section 1: Introduction to Azure Data Explorer
5
Section 2: Querying and Visualizing Your Data
11
Section 3: Advanced Azure Data Explorer Topics

Chapter 5: Introducing the Kusto Query Language

By this point, you have a solid understanding of what Azure Data Explorer (ADX) is, how to use it, and how to build ADX infrastructure via the Azure portal. You also know how to use Microsoft PowerShell and Azure Resource Manager (ARM) templates, and how to configure data ingestion. Now that we have ingested data, the next step is to understand how to query and explore our data. In this chapter, we are going to introduce the Kusto Query Language (KQL), and then in the next two chapters, Chapter 6, Introducing Time Series Analysis, and Chapter 7, Identifying Patterns, Anomalies, and Trends in Your Data, we will focus on the advanced features of KQL.

We will begin by explaining what KQL is, what its main features are, and where KQL can be used. Next, we will learn about the syntax and structure of KQL queries, as well as how to search using the search and where operators. Then, we will explore how to perform aggregation using the summarize...