![]() Interestingly KQL is a read-only query language, which processes the data and returns results. KQL (Kusto Query Language) was developed with certain key principals in mind, like – easy to read and understand syntax, provide high-performance through scaling, and the one that can transition smoothly from simple to complex query. You can share the insights using Excel, or Power BI, or directly from the ADX. ![]() There are multiple different ways to share the visualized data. This can be done by exporting the data in the CSV format directly from ADX.įinally, after the data has been validated, the visualized data needs to be presented. This is where you would wish to share the data. We can use such queries to discover patterns, identify anomalies and outliers, create statistical modeling and more.Īt the end you should get your data validated by SMEs or stakeholders. This is technically called data ingestion.Īfter creating tables and ingesting data to them we can move forward and use Kusto Query Language (aka KQL) to explore the data. ![]() We already created the environment in the previous section, and now, we will extend our knowledge by first creating the tables using the Kusto explorer, and then import the data in the table from an external source.
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