Learn about how to use Kusto Query Language (KQL) to explore data, discover patterns, identify anomalies, and create statistical models.
Learn about how to use Kusto Query Language (KQL) to explore data, discover patterns, identify anomalies, and create statistical models.
if you are working with KQL / Kusto / Azure Data Explorer and looking for KQL cheat sheet, this post is for you
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Kusto Query Language (KQL) is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more. KQL is a simple yet powerful language to query structured, semi-structured, and unstructured data. The language is expressive, easy to...
KQL provides an operator called "explain" to translate SQL queries into KQL While this approach is fine on simple queries and learning KQL, it is recommended to use KQL for Azure Synapse Data Explorer for more complex analytics.SQL to KQL Cheat Sheetis available to help in the jou...
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Enterprise security has become a big data problem, so using big data tooling to help generate insights makes sense, especially when you’re regularly exploring specific log files or combinations of logs. As KQL is designed for this sort of task and used by some of the analytical tools that ...
對嵌入 KQL 的 Python 進行除錯 KQL 查詢的最佳實踐 實體或單位 資料類型 功能 查詢陳述式 表格運算子 特殊函數 標量運算子 純量函式 彙總函數 圖表 地理空間 時間序列分析 外掛程式 視窗函數 限制和錯誤 參考 Regex 語法 JSONPath 語法 SQL 到 Kusto 速記表 Splunk 對 Kusto 的功能提要 使用T-SQL 查詢資料 時...