Data analysis in Azure Data Explorer with Kusto Query Language
In this learning path, students will learn how to analyze data in Azure Data Explorer using the Kusto Query Language.
Prerequisites
The following pre-requisite should be completed:
- A Microsoft account, a Microsoft Entra user identity to create a free cluster, or an Azure account
- Familiarity with database structures like tables, columns, and rows
Achievement Code
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Modules in this learning path
Learn to describe the ingestion, query, visualization, and data management features that Azure Data Explorer provides to help you make sense of the data flowing into your business. Determine the types of data analysis for which Azure Data Explorer is a good data management platform.
Learn about the basics of Kusto Query Language (KQL), and the various Microsoft products that use it.
Get started by writing simple queries in Kusto Query Language (KQL) to explore and gain insights from your data. Learn how to use the operators take, project, where, count, sort, and others.
Write advanced queries in Kusto Query Language to help you gain insights from your data. Use the aggregation functions count, dcount, countif, sum, min, max, avg, percentiles, and others. Communicate these results visually in charts.
Write advanced queries in Kusto Query Language to gain deeper insights by combining data from several tables. Learn how to use the table-level operators lookup, join, union, and materialize, and the new aggregation functions arg_min and arg_max. Also, learn how to communicate these results visually in charts.
Characterize the schema, range, and completeness of a dataset using Azure Data Explorer. Use queries to visualize data trends, and then share these queries and results with others.
Create a dashboard from a query in Azure Data Explorer web UI. Add new tiles. Create dashboard parameters, and cross-filters for the parameters.