May 1, 2024
Updated June 28, 2025
16 minute read
An Introduction to Kusto Query Language (KQL)
Kusto Query Language, widely known as KQL, is a powerful tool designed to explore vast amounts of data, identify patterns, spot anomalies, and create statistical models. It is a read-only language, meaning it is used to request and return data without modifying the source. This makes it a safe and robust choice for data analysis. KQL queries are stated in plain text, using a data-flow model where data passes through a sequence of steps, making the queries easy to read, write, and automate.
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Find a path to becoming a KQL. Learn more at:
OpenCourser.com/topic/612l6r/kq
Reading list
We've selected four books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
KQL.
This comprehensive guide provides a deep dive into Elasticsearch, covering its architecture, data ingestion, querying, and analytics capabilities. Its relevance to KQL stems from Elasticsearch being the underlying data store that KQL interacts with.
Collection of recipes for solving common KQL problems. It valuable resource for experienced users who want to learn how to use KQL to solve specific problems.
Provides a practical guide to Elasticsearch, including a chapter on KQL. It good choice for experienced users who want to learn more about how to use Elasticsearch and KQL to solve real-world problems.
Provides a comprehensive overview of Elasticsearch, including chapters dedicated to KQL. It's a great resource for beginners who want to understand the fundamentals of KQL and its role in data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/612l6r/kq