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Azure Data Explorer(ADX) and Kusto Query Language (KQL)
Rating: 4.1 out of 5(57 ratings)
1,239 students

Azure Data Explorer(ADX) and Kusto Query Language (KQL)

Learn Azure Data Explorer (ADX) and Kusto Query Language (KQL) in easiest possible way.
Created byAtchyut Kumar, Edufulness EFN
Last updated 4/2024
English

What you'll learn

  • Understand Azure Data Explorer (ADX)
  • Write queries in Kusto Query Language (KQL)
  • Learn Joins, Subqueries, Aggregate functions in KQL.
  • Create clusters and databases in ADX
  • Create geospatial visualization.
  • Learn Tabular operators, Scaler operators, Scalar functions, special functions and Time series analysis.

Course content

1 section • 8 lectures • 51m total length

  • Azure Data Explorer (ADX) account creation6:45
  • Azure Data Explorer (ADX) Free account creation4:29

    Create a free Azure Data Explorer account via the Kusto portal, sign in with your Azure ID, and set up a free cluster and database to ingest data and query.

  • Ingest Data from Local file and Microsoft Blob8:02
  • Basic commands5:44

    Demonstrate writing basic Kusto queries to display table data, count rows, and list distinct values using table name, pipe, and distinct, with practical examples from EMP, orders, and events tables.

  • Project Operator5:03
  • Where operator3:28
  • Summarize Operator12:49
  • Summarize Operator - bin()4:54

Requirements

  • Basic Data base concepts

Description

Welcome!

Hi, I am happy to helping you with learning one of the in-demand data engineering tools in the cloud, Azure Data Explorer (ADX) and Kusto Query Language (KQL).

Azure Data Explorer aka ADX, is a fast, highly scalable and fully managed data analytics service for log, telemetry and streaming data. This data exploration service enables you to pull together, store and analyze diverse data. You can query terabytes of data in a few seconds and it allows fast ad-hoc queries over the varied data.

Kusto Query Language is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more. The query uses schema entities that are organized in a hierarchy similar to SQLs: databases, tables, and columns.


This course is designed to help for develop the skills necessary to understand Azure Data Explorer (ADX) and Kusto Query Language (KQL).


Who this course is for:

  • University students looking for a career in Data Engineering

  • IT developers working on other disciplines trying to move to Data Engineering

  • Data Architects looking to gain an understanding about Azure Data Engineering stack

  • Data Scientists who want extend their knowledge into data engineering

  • Data Analyst or similar profiles

  • Other on-premises Database related profiles who want to learn how to implement these technologies in Azure Cloud.

  • Database Developer

  • Database Administrators (DBA)

Who this course is for:

  • For all levels

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