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

Creating a time series with KQL

KQL makes it remarkably simple to perform time series analysis and does not require you to have a background in time series analysis, although it does help. Before we dive into creating a time series, I would like to discuss some new KQL operators and functions that we will be using as helper functions.

Introducing the helper operators and functions

The first KQL feature is variables. We briefly mentioned variables in the previous chapter, Chapter 5, Introducing the Kusto Query Language, but it is worth spending some time learning about variables. As you will see, variables can help with the readability of your queries, which is important once you progress from the simple examples we used in the previous chapter. A few decades ago, when I first started to learn about programming, one of the first things I learned was maintainability and readability and why magic numbers are bad practice. As you will see, as we write more complex queries, values...