KQL for Azure Admins Course Overview

KQL for Azure Admins Course Overview

The "KQL for Azure Admins" course is designed to equip learners with the skills to utilize Kusto Query Language (KQL) effectively within Azure services. As a vital tool for Azure administrators, KQL helps in analyzing and managing large datasets across various Azure resources.

Starting with an introduction to KQL commands, syntax, elements, and operators, learners will gain foundational knowledge necessary to run KQL queries. The course progresses to more advanced topics such as Analyzing query results, utilizing operators to summarize, filter, and Visualize data, and building Multi-table statements to extract comprehensive insights.

Learners will also explore constructing KQL statements specifically for Microsoft Sentinel, including the use of various operators like search, where, extend, and project. Hands-on lessons guide participants in writing their first queries, connecting to resources, and manipulating data returns.

Finally, the course covers Data exportation techniques to CSV files and Power BI, ensuring learners can share their insights effectively. Through this KQL training and Kusto training, Azure administrators will be empowered to perform complex data analysis, enhancing their operational capabilities within the Azure ecosystem.

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875

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Course Fee 875
Total Fees
875 (USD)
  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
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  • Live Training (Duration : 16 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Target Audience for KQL for Azure Admins

KQL for Azure Admins is a comprehensive IT training course designed for professionals seeking to master KQL for effective data management in Azure.


Target Audience for KQL for Azure Admins:


  • Azure Administrators
  • Data Engineers
  • Cloud Solution Architects
  • Security Analysts working with Microsoft Sentinel
  • IT Professionals interested in analytics and data visualization within Azure
  • Database Administrators looking to expand their querying skills
  • System Analysts and Developers responsible for monitoring and querying Azure resources
  • Business Intelligence Professionals seeking to integrate Azure data with Power BI
  • Technical Support Engineers involved in troubleshooting Azure environments
  • DevOps Engineers who need to analyze and visualize data as part of continuous integration/continuous deployment processes


Learning Objectives - What you will Learn in this KQL for Azure Admins?

Introduction to the Course's Learning Outcomes and Concepts Covered

Explore the power of KQL (Kusto Query Language) in Azure with our comprehensive course designed to equip you with the skills to analyze, manage, and visualize data effectively for Azure Admins.

Learning Objectives and Outcomes

  • Grasp the basics of KQL commands, syntax, elements, and operators for querying Azure data services.
  • Execute KQL queries efficiently and interpret the results to gain insightful data analysis.
  • Utilize the Summarize Operator to filter, sort, and prepare data for in-depth analysis.
  • Create compelling data visualizations using the Render operator to communicate findings clearly.
  • Construct complex, multi-table statements with the Union and Join operators to consolidate data from various sources.
  • Understand and apply KQL statement structures specifically for Microsoft Sentinel to enhance security analytics.
  • Develop proficiency in using essential KQL operators like Let, Search, Where, Extend, Order, and Project for refined data manipulation.
  • Write and run your first KQL query, connecting to resources and manipulating data with operators like Take, Project, Where, and Sort.
  • Learn to export data effectively from KQL queries to CSV files for reporting and to Power BI for advanced visualization and analytics.
  • Gain the ability to troubleshoot and optimize KQL queries, improving performance and accuracy in real-world Azure administration scenarios.
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