Summarize and Aggregate Data with Kusto Query Language (KQL)

Master the essential KQL aggregation functions to transform raw data into meaningful business insights. This course will teach you to summarize, group, and analyze large datasets effectively using Azure Data Explorer.

Data professionals working with large-scale datasets in Azure environments often struggle to extract meaningful insights from raw data. Without proper aggregation techniques, analyzing thousands or millions of records becomes overwhelming and inefficient, leading to missed opportunities for data-driven decision making. In this course, Summarize and Aggregate Data with Kusto Query Language (KQL), you'll gain the ability to transform raw data into actionable business insights using powerful aggregation functions. First, you'll explore fundamental aggregation operations including count, sum, average, minimum, and maximum functions, along with the essential 'summarize' operator. Next, you’ll learn how to use ‘project’, ‘extend’, and ‘let’ to calculate and format derived metrics, how to rename fields for clarity, and how to apply rounding or percentage calculations for clear, presentation-ready results. Finally, you’ll learn how to build top-N and time-based summaries, apply conditional aggregations, and compare metrics across groups to answer practical business questions. When you're finished with this course, you'll have the skills and knowledge of KQL aggregation and summarization needed to efficiently analyze large datasets and deliver meaningful insights in Azure Data Explorer environments.