Book Image

Scalable Data Analytics with Azure Data Explorer

By : Jason Myerscough
Book Image

Scalable Data Analytics with Azure Data Explorer

By: Jason Myerscough

Overview of this book

Azure Data Explorer (ADX) enables developers and data scientists to make data-driven business decisions. This book will help you rapidly explore and query your data at scale and secure your ADX clusters. The book begins by introducing you to ADX, its architecture, core features, and benefits. You'll learn how to securely deploy ADX instances and navigate through the ADX Web UI, cover data ingestion, and discover how to query and visualize your data using the powerful Kusto Query Language (KQL). Next, you'll get to grips with KQL operators and functions to efficiently query and explore your data, as well as perform time series analysis and search for anomalies and trends in your data. As you progress through the chapters, you'll explore advanced ADX topics, including deploying your ADX instances using Infrastructure as Code (IaC). The book also shows you how to manage your cluster performance and monthly ADX costs by handling cluster scaling and data retention periods. Finally, you'll understand how to secure your ADX environment by restricting access with best practices for improving your KQL query performance. By the end of this Azure book, you'll be able to securely deploy your own ADX instance, ingest data from multiple sources, rapidly query your data, and produce reports with KQL and Power BI.
Table of Contents (18 chapters)
1
Section 1: Introduction to Azure Data Explorer
5
Section 2: Querying and Visualizing Your Data
11
Section 3: Advanced Azure Data Explorer Topics

Ingesting data from Blob storage using Azure Event Grid

In our final example of data ingestion, we will enable streaming on our cluster and use Azure Event Grid and Event Hubs so we can ingest data whenever new files are placed in our storage account's blob container. A blob container is a location on the storage account used to store our data.

For this section, we need to create the following Azure resources:

  • A storage account for storing files
  • An event grid to emit blob creation events
  • An event hub deliver the notification to Azure Data Explorer

Using JSON data, we will demonstrate how to create JSON-based mapping schemas.

When a file is uploaded to the storage account, a blob created event is generated and received by the event grid. The event grid then updates Azure Data Explorer to pull information from the storage account. In our example, the information is a JSON file.

This path of data ingestion is shown in the following figure:

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