Scalable Data Analytics with Azure Data Explorer



Scalable Data Analytics with Azure Data Explorer: Modern ways to query, analyze, and perform real-time data analysis on large volumes of data

by Arunee SinghchawlaJason Myerscough

  • Length: 364 pages
  • Edition: 1
  • Language: English
  • Publisher: Packt Publishing
  • Publication Date: 2022-03-17

Write efficient and powerful KQL queries to query and visualize your data and implement best practices to improve KQL execution performance

Key Features

  • Apply Azure Data Explorer best practices to manage your data at scale and reduce KQL execution time
  • Discover how to query and visualize your data using the powerful KQL
  • Manage cluster performance and monthly costs by understanding how to size your ADX cluster correctly

Book Description

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.

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