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

Introducing data visualization

Before diving into building dashboards, it is worth spending some time discussing what data visualization is and its goals. As we mentioned in Chapter 1, Introducing Azure Data Explorer, 90% of today's data is digital and we are generating quintillion bytes of data each day!

Once we have understood our data and identified traits such as trends, variations, seasonality, and anomalies and created forecasts with them, the next step is to present our findings to our audience. This is where data visualization can help. Data visualization is a method that helps facilitate your understanding of your data to your audience, who can have various backgrounds and expertise.

Designing and developing effective data visualizations is an art and requires practice. The types of charts and tiles you use can influence how your data is perceived and bad design decisions could lead to your audience interpreting the data incorrectly.

To illustrate the power...