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

Ingesting the StormEvents sample dataset

In the spirit of keeping the chapter both theoretical and practical, we are going to jump ahead a little and ingest an example dataset that Microsoft provides. Don't worry if you do not understand all the details, as data ingestion will be discussed in Chapter 4, Ingesting Data in Azure Data Explorer.

In the previous chapter, we created our ADX cluster and databases, but we did not ingest any data or create any tables. We are going to use a method called one-click ingestion, which is amazingly simple to use and is a great example of ADX allowing you to focus on exploring your data rather than worrying about the low-level details of ingestion.

As you will recall from Chapter 2, Building Your Azure Data Explorer Environment, the third step in the creation process is to ingest data, as shown in the following screenshot:

Figure 3.1 – Data ingestion

The following sequence of steps will import Microsoft...