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Scalable Data Analytics with Azure Data Explorer

Scalable Data Analytics with Azure Data Explorer

By : Jason Myerscough
4.8 (8)
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Scalable Data Analytics with Azure Data Explorer

Scalable Data Analytics with Azure Data Explorer

4.8 (8)
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)
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1
Section 1: Introduction to Azure Data Explorer
5
Section 2: Querying and Visualizing Your Data
11
Section 3: Advanced Azure Data Explorer Topics

Technical requirements

If you do not already have an Azure account, head over to https://azure.microsoft.com/en-us/free/search/ and sign up. Microsoft provides 12 months of popular free services and $200 credit, which is enough to cover the cost of our Azure Data Explorer journey with this book. Microsoft also provides a free to use cluster (https://help.kusto.windows.net/) that is already populated with data. We will use this free cluster and create our own clusters throughout this book.

Please remember to clone or download the Git repository that accompanies the book from https://github.com/PacktPublishing/Scalable-Data-Analytics-with-Azure-Data-Explorer. All the code and query samples listed in the book are available in our repository. Download the latest version of Git from https://git-scm.com if you have not already installed the command-line tools.

Important Note

When developing and cloning repositories, I create a development folder in my home directory. On Windows, this is C:\Users\jason\development. On macOS, this is /Users/jason/development. When referencing specific code examples, I will refer to the repository's parent directory as ${HOME}, for example, ${HOME}/Scalable-Data-Analytics-with-Azure-Data-Explorer/Chapterxx/file.kql.

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