8 posts about KQL by 5 contributors.
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Master .NET application monitoring with Application Insights! Gain real-time insights, track performance, dependencies, and errors for optimized reliability.
This article is about Understanding the Supported File Types for Data Ingestion into the KQL Database in Fabric Real-time Analytics. Supported file types include JSON, CSV, XML, & Text. Note: XLSX is not supported. See how to ingest & transform data using Data Factory.
This video shows how to calculate Total and Average Sales by Account Manager by writing Kusto Query Language code in Microsoft Fabric.
Delve into the advanced features of Microsoft Defender for Endpoint (MDE) with this detailed guide. Learn the art of threat hunting using the Advanced Hunting method and explore controls available in MDE. From setting up your time zone to creating detection rules using Kusto Query Language (KQL), this post covers essential aspects, including data retention, email notifications, and querying for specific events like PDF files in emails or Smart Screen warnings. Understand how to save and reuse queries, render query results into charts, and create detection rules for proactive threat detection.
Kusto Query Language (KQL) is a potent tool developed by Microsoft for diverse data analytics needs. Uncover its applications across industries, from log analytics to IoT, and explore essential queries, distinguishing KQL from other database query languages with its specialized focus on log analytics, time-series analysis, and data exploration efficiency. Enhance your understanding of KQL's rich functionalities and its seamless integration with Azure Data Explorer, making it a standout choice for efficient and specialized data querying.
This video shows how to Create Database and Ingest Data into KQL Table in Microsoft Fabric.
In this video, I demo how to fetch data from azure data explorer of the kusto Microsoft Fabric database in Excel.
Kusto Query Language (KQL) empowers Azure IoT projects with real-time data analysis, flexible exploration, aggregation, and seamless Azure service integration. It's pivotal in extracting insights from IoT data streams.
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