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Scalable Data Analytics with Azure Data Explorer

You're reading from  Scalable Data Analytics with Azure Data Explorer

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801078542
Pages 364 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Jason Myerscough Jason Myerscough
Profile icon Jason Myerscough

Table of Contents (18) Chapters

Preface Section 1: Introduction to Azure Data Explorer
Chapter 1: Introducing Azure Data Explorer Chapter 2: Building Your Azure Data Explorer Environment Chapter 3: Exploring the Azure Data Explorer UI Section 2: Querying and Visualizing Your Data
Chapter 4: Ingesting Data in Azure Data Explorer Chapter 5: Introducing the Kusto Query Language Chapter 6: Introducing Time Series Analysis Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data Chapter 8: Data Visualization with Azure Data Explorer and Power BI Section 3: Advanced Azure Data Explorer Topics
Chapter 9: Monitoring and Troubleshooting Azure Data Explorer Chapter 10: Azure Data Explorer Security Chapter 11: Performance Tuning in Azure Data Explorer Chapter 12: Cost Management in Azure Data Explorer Chapter 13: Assessment Other Books You May Enjoy

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...

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