ADX Azure Data Explorer Workshop

Welcome to the ADX Azure Data Explorer Workshop! In this workshop, you will learn how to work with Azure Data Explorer, a fast and highly scalable data exploration service.

Submodules

This workshop is divided into the following submodules:

Submodule 1: Introduction to Azure Data Explorer

In this submodule, you will get an overview of Azure Data Explorer and its key features. You will also learn how to provision an Azure Data Explorer cluster and connect to it.

Submodule 2: Data Ingestion

In this submodule, you will learn how to ingest data into Azure Data Explorer. You will explore different data ingestion methods and understand how to optimize data ingestion for performance.

Submodule 3: Data Querying and Analysis

In this submodule, you will learn how to query and analyze data in Azure Data Explorer. You will explore the Kusto Query Language (KQL) and learn various techniques for data analysis and visualization.

Submodule 4: Advanced Topics

In this submodule, you will dive deeper into advanced topics related to Azure Data Explorer. You will learn about:

  • Time Series Analysis: Explore techniques for analyzing and visualizing time series data using Azure Data Explorer.

  • Root Cause Analysis: Learn how to identify the root causes of issues or anomalies in your data using advanced querying techniques.

  • Machine Learning with Azure Data Explorer: Discover how to leverage machine learning algorithms and models in Azure Data Explorer for predictive analytics and anomaly detection.

Getting Started

To get started with the workshop, follow the instructions in each submodule. Make sure to complete the exercises and hands-on labs to gain practical experience with Azure Data Explorer.

  • Basic knowledge of SQL and data analysis concepts
  • Familiarity with Azure portal and Azure Resource Manager (ARM)

Conclusion

By the end of this workshop, you will have a solid understanding of Azure Data Explorer and its capabilities. You will be able to ingest, query, and analyze data at scale using Azure Data Explorer.

Let's get started!