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

Summary

There you go! That was our introduction to the main features of the ADX UI. In this chapter, we ingested Microsoft's sample dataset using the one-click ingestion method and we learned how to query data from within the Azure portal.

The remainder of the chapter looked at the main panels and features of the ADX Web UI. We saw how the Azure portal uses the embedded UI and that the embedded UI can be embedded in any web page using iFrames. Next, we learned that the Web UI (https://dataexplorer.azure.com/) consists of three main views/windows.

The Data view allows us to ingest data using the one-click ingestion method.

The Query Editor view allows us to write and execute our queries and provides syntax highlighting and Microsoft's IntelliSense.

The Dashboards view allows us to create dashboards based on our queries that we can share with our stakeholders. We will cover dashboards in more detail in Chapter 8, Data Visualization with Azure Data Explorer and Power...