Kusto Query Language (KQL) Part 1

Kusto Query Language (KQL) – Part 1, available at $84.99, has an average rating of 4.34, with 51 lectures, based on 759 reviews, and has 4942 subscribers.

You will learn about An overview of Azure Data Explorer (ADX) Azure Data Explorer Web UI and Log Analytics Demo Site A deep dive into the essentials of KQL The most commonly used KQL operators and functions Aggregating data with KQL Exporting data to Excel and Power BI Ingesting Data into Azure Data Explorer This course is ideal for individuals who are Anyone needing to analyze data from Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources or Anyone wanting to learn the amazing Kusto Query Language It is particularly useful for Anyone needing to analyze data from Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources or Anyone wanting to learn the amazing Kusto Query Language.

Enroll now: Kusto Query Language (KQL) – Part 1

Summary

Title: Kusto Query Language (KQL) – Part 1

Price: $84.99

Average Rating: 4.34

Number of Lectures: 51

Number of Published Lectures: 50

Number of Curriculum Items: 51

Number of Published Curriculum Objects: 50

Original Price: $27.99

Quality Status: approved

Status: Live

What You Will Learn

An overview of Azure Data Explorer (ADX)

Azure Data Explorer Web UI and Log Analytics Demo Site

A deep dive into the essentials of KQL

The most commonly used KQL operators and functions

Aggregating data with KQL

Exporting data to Excel and Power BI

Ingesting Data into Azure Data Explorer

Who Should Attend

Anyone needing to analyze data from Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources

Anyone wanting to learn the amazing Kusto Query Language

Target Audiences

Anyone needing to analyze data from Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources

Anyone wanting to learn the amazing Kusto Query Language

There is a good chance you have already used Azure Data Explorer (ADX) to some degree without knowing it. If you have used Azure Security Center, Azure Sentinel, Application Insights, Resource Graph Explorer, or enabled diagnostics on your Azure resources, then you have used ADX. All these services rely on Log Analytics, which is built on top of ADX and is queried using KQL.

Like many other tools and products, ADX was started by a small group of engineers in Israel around 2015. They needed to solve a problem. A group of developers from Microsoft’s Power BI team needed a high-performing big data solution to ingest and analyze their logging and telemetry data. So, of course, they built their own because they could not find a service that met all their needs. This resulted in the Azure Data Explorer, also known as Kusto.

So, what is ADX? It is a fully managed, append-only columnar store big data service capable of elastic scaling and ingesting literally hundreds of billions of rows daily. ADX offers:

Low-latency ingestion and elastic scaling

Security

Cost-efficient (pay as you consume)

High availability

Time Series Analysis

Super fast query performance via KQL

Custom built solutions

As great as ADX is, this course is mostly centered around KQL (Kusto Query Language). KQL is the query language for managing all logging and telemetry data stored in ADX. Even if you do not use ADX directly, you will still use KQL for monitoring, analyzing logs, managing assets, exploring security data, and exploring Application Insights data. KQL is ADX’s read-only query language that has many similarities with SQL, such as working with tables, columns, and providing functionality for filtering. KQL supports a subset of SQL, and SQL statements can be executed and converted to KQL using the EXPLAIN keyword, reducing the learning curve for engineers with an SQL background.

This is part 1 of a two part series covering ADX (lightly) and the KQL language (mostly). The goal of this course is to cover the basics. At the end of this five hour course you will have a solid understanding of what KQL can do. And it can do a lot! In some respects I like it better than T-SQL which I have used for over 20 years.

Part 2 of this course goes well beyond the basics and will cover many advanced KQL topics and scenarios (and some more ADX).

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Before You Purchase This Course!

Chapter 2: Azure Data Explorer / ADX / Kusto

Lecture 1: Overview

Lecture 2: Creating an Azure Data Explorer Cluster

Lecture 3: Azure Data Explorer Web UI

Chapter 3: Kusto Query Language

Lecture 1: Contoso Dataset

Lecture 2: What is Kusto Query Language (KQL)?

Lecture 3: Would You Rather Use T-SQL?

Chapter 4: The Most Common Operators and Functions You Will Use

Lecture 1: Getting Started

Lecture 2: Project / Extend / Take

Lecture 3: Where / Ago

Lecture 4: Search

Lecture 5: Distinct

Lecture 6: Summarize / Bin

Lecture 7: Parse

Lecture 8: Order By

Lecture 9: Datetime / Timespans

Lecture 10: Datetime_Part / Datetime_Diff / Datetime_Add

Lecture 11: Format_Datetime / Format_Timespan

Lecture 12: StartOf / EndOf / Between

Lecture 13: IIF / Case / Split

Lecture 14: String Operators

Lecture 15: Strcat

Lecture 16: ToDynamic / Parse_Json

Lecture 17: Getschema

Chapter 5: Aggregating Data – Most Common Functions

Lecture 1: Count and DCount

Lecture 2: Arg_max and Arg_min

Lecture 3: Make_set / Make_list / Mv-expand

Lecture 4: Percentiles

Lecture 5: Pivot

Lecture 6: Top-Nested

Lecture 7: Any / Take_any

Lecture 8: Wrap Up

Chapter 6: Miscellaneous Statements, Operators and Functions

Lecture 1: Let

Lecture 2: Join

Lecture 3: Union

Lecture 4: Datatable

Lecture 5: Prev and Next

Lecture 6: Top-hitters

Lecture 7: Sample

Lecture 8: Render

Lecture 9: Geo Location

Chapter 7: Exporting Data

Lecture 1: Exporting to Excel / CSV and Power BI

Chapter 8: Microsoft Fabric and KQL

Lecture 1: Introduction

Lecture 2: Microsoft Fabric – What is it?

Lecture 3: KQL Integrated Into Microsoft Fabric

Lecture 4: Microsoft Fabric Real-Time Intelligence (Real-Time Analytics)

Chapter 9: Updates and New Features

Lecture 1: Build 2023

Chapter 10: Test Your Knowledge

Lecture 1: Test Your Knowledge

Chapter 11: Bonus Section

Lecture 1: Bonus

Instructors

Randy Minder
Lead BI Developer / Power BI / Microsoft Fabric

Rating Distribution

1 stars: 4 votes

2 stars: 15 votes

3 stars: 68 votes

4 stars: 278 votes

5 stars: 394 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!