From SQL to KQL via Azure Data Explorer

We all know (and love) our SQL, the Structured Query Language. Some of us have been writing SQL queries for decades. But there's a relatively new kid on the block: KQL, the Kusto Query Language. A powerful tool to explore data, discover patterns and anomalies, even analyze streaming data and time series. It's also the language used to query the Azure log databases and your IoT sensor data.

In this session you'll get to know the most important elements of KQL: tables, queries and the pipe, visualizations and dashboards. We'll see what it has in common with SQL and what the differences are. We'll learn our ways to get from SQL to KQL.

One possible tool of choice to get going with KQL is ADX, the Azure Data Explorer (others are the KQL extension for Azure Data Studio or the Kusto.Explorer). For the practical parts of this session we'll use ADX with the free cluster option as our environment to ingest, analyze and visualize our data.

Thomas Hütter

Explorer of Things

Brüggen, Germany

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