Introduction

  • 2 minutes

Kusto Query Language (KQL) lets you explore your data and discover patterns, identify anomalies and outliers, and create statistical models. A Kusto query is a read-only request to process data and return results. KQL offers a wide variety of functions that analyze your data in different ways. In a previous module, you learned how to use the most common tabular operators to begin exploring and filtering your data. In this module, you'll learn how to aggregation data using the Kusto Query Language (KQL), organize complex queries, and display results visually to gain meaningful insights from this dataset.

Example scenario

You're a data analyst with a passion for meteorological data. You want to use KQL to manipulate and consolidate a dataset that will allow you to answer questions about the kinds and locations of storms in the US. In particular, you want to compare the impacts of different types of storms in various locations.

What will we be doing?

You'll write queries in the Kusto Query Language (KQL) to explore and gain insights from a sample dataset. You'll learn how to:

  • Group data using aggregation functions.
  • Count events using the count(), dcount(), countif() functions.
  • Summarize data using sum(), avg(), min(), max(), and percentiles() functions.
  • Visualize data using the render operator.
  • Introduce variables using the let statement.

What is the main goal?

By the end of this session, you'll be able to write advanced queries in Kusto Query Language and visually render the results to gain insights from your data.