Introduction to Azure Data Explorer and KQL Queries

Azure Data Explorer is a fast, fully managed data analytics service purpose-built for real-time analysis of large volumes of streaming data. It powers scenarios ranging from IoT telemetry analysis to security log investigation, using the Kusto Query Language (KQL) - a read-only, expressive language designed for exploring structured, semi-structured, and unstructured data. Organizations use Azure Data Explorer to detect anomalies in manufacturing systems, analyze application performance metrics, and correlate security events across millions of log entries in seconds.

KQL is not limited to Azure Data Explorer - it is the query language behind Azure Monitor, Microsoft Sentinel, and Microsoft Defender, making it one of the most valuable analytical skills for cloud engineers and security professionals. In this lab, you will create a free Azure Data Explorer cluster, ingest sample weather event data, and progressively build KQL queries using operators like where, project, summarize, and render to filter, aggregate, and visualize time-series patterns.

Objectives

Upon completion of this intermediate level lab, you will be able to:

• Create a free Azure Data Explorer cluster and database using the web UI
• Ingest the StormEvents sample dataset into a database table
• Write KQL queries using where and project operators to filter and shape results
• Use the summarize operator with aggregation functions to analyze event distributions
• Create time-series visualizations using the render operator
• Explore time-series analysis patterns to identify trends and anomalies

Who is this lab for?

This lab is designed for:

• Cloud engineers building real-time analytics solutions
• Data analysts working with large-scale telemetry data
• Security professionals learning KQL for Sentinel and Defender
• Anyone preparing for Azure certification exams involving data analytics