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

Questions

Before moving on to the next chapter, test your knowledge by trying out these exercises. The answers can be found at the back of this book:

  1. What is the purpose of workload groups?
  2. Assuming that we have our request classification policy configured and enabled, what will happen when we execute the following query as a database admin?
    .alter cluster policy request_classification '{"IsEnabled":false}' <|
        iff(current_principal_is_member_of('aadgroup=TrialUsers;27447925-1f0e-41b6-b01f-973eaab478b0'), "Packt Demo","default")
  3. Why should you filter your data based on a date field as early as possible in your query?
  4. Create a dashboard in the Data Explorer Web UI and display the query execution metrics, such as the longest top 5 running queries, and aggregate the workload groups. Hint: use .show queries and review Chapter 8, Data Visualization with Azure Data Explorer and Power BI.
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