Data gives you insights, helps you predict trends and discover anomalies, and gives you a competitive advantage.
In this course, How to Start with Microsoft Azure Data Explorer, you'll learn the foundational knowledge needed to ingest, query, analyze, and visualize large amounts of data with Azure Data Explorer.
First, you'll understand the architecture of Data Explorer.
Next, you'll learn how create and scale infrastructure, ingest data, and query using the Kusto Query Language, also known as KQL.
Finally, you'll learn how to visualize data from within ADX or integrating with a third-party product like Power BI, Grafana, Redash, Tableau, Sisense, and any other platform that uses ODBC and JDBC.
When you're finished with this course, you'll have the skills and knowledge required to analyze all kinds of data, including log and telemetry data, using Azure Data Explorer - Microsoft's interactive Big Data platform.
Xavier is very passionate about teaching, helping others understand search and Big Data. He is also an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP.
Course Overview Hi everyone. My name is Xavier Morera, and welcome to my course, How to Start with Microsoft Azure Data Explorer. I am very passionate about working with data in the cloud, something that I've been doing for quite a few years now. Did you know that Azure Data Explorer, code named Kusto, is what Microsoft themselves have been using for years as their own interactive big data analytics platform for Windows, Skype, Xbox, LinkedIn, Office, Azure Log Analytics, Application Insights, and many more products that generate large amounts of data. And now it is available for you to work with your data. In this course, we're going to learn end to end what we need to know on how to get started with Microsoft Azure Data Explorer. Some of the major topics that we will cover include a high‑level overview and understanding of Data Explorer, how to create and scale Data Explorer infrastructure, how to ingest data into Data Explorer using several different ingestion methods from varied sources. Then, I will give you a crash course on querying using the Kusto query language, or KQL, followed by how to visualize data using different methods, including the render operator, the ADX dashboard, Power BI, Kibana, Grafana, Redash, Tableau, and Sisense, to name a few. By the end of this course, you'll know how to use Azure Data Explorer, Microsoft's interactive big data platform. Before beginning the course, you should be familiar with the basics of Microsoft Azure. I hope you'll join me on this journey to learn how to ingest, query, analyze, and visualize data with the How to Start with Microsoft Azure Data Explorer course, at Pluralsight.