This is the code repository for Actionable Insights with Amazon QuickSight, published by Packt.
Develop stunning data visualizations and machine learning-driven insights with Amazon QuickSight
The adoption of cloud-native BI tools, like Amazon QuickSight, enables organizations to gather insights from data at scale. This book is a practical guide to performing simple-to-advanced tasks with Amazon QuickSight.
You’ll begin by learning QuickSight’s fundamental concepts and how to configure data sources. Next, you’ll be introduced to the main analysis-building functionality of QuickSight to develop visuals and dashboards. The book will also demonstrate how to develop and share interactive dashboards with parameters and on-screen controls. Advanced filtering options with URL actions will then be covered, before learning how to set up alerts and scheduled reports. Later, you’ll explore the Insights visual type in QuickSight using both existing insights and by building custom insights. Further chapters will show you how to add machine learning insights such as forecasting capabilities, analyzing time series data, adding narratives, and outlier detection to your dashboards. You’ll also explore patterns to automate operations and look closer into the API actions that allow us to control settings. Finally, you’ll learn advanced topics such as embedded dashboards and multitenancy.
By the end of this book, you’ll be well-versed with QuickSight’s BI and analytics functionalities that will help you create BI apps with ML capabilities.
This book covers the following exciting features:
- Understand the wider AWS analytics ecosystem and how QuickSight fits within it
- Set up and configure data sources with Amazon QuickSight
- Include custom controls and add interactivity to your BI application using parameters
- Add ML insights such as forecasting, anomaly detection, and narratives
- Explore patterns to automate operations using QuickSight APIs
- Create interactive dashboards and storytelling with Amazon QuickSight
- Design an embedded multi-tenant analytics architecture
- Focus on data permissions and how to manage Amazon QuickSight operations
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
$aws quicksight update-user --user-name author-iam --role
AUTHOR --custom-permissions-name custom-author --email <youremail>
--aws-account-id <account-id> --namespace default
--region us-east-1
Following is what you need for this book: This book is for business intelligence (BI) developers and data analysts who are looking to create interactive dashboards using data from Lake House on AWS with Amazon QuickSight. This book will also be useful for anyone who wants to learn Amazon QuickSight in depth using practical examples. You will need to be familiar with general data visualization concepts, however, no prior experience with Amazon QuickSight is required.
With the following software and hardware list you can run all code files present in the book (Chapter 1-10).
| Chapter | Software required | OS required |
|---|---|---|
| 1-10 | AWS Web Services(AWS) with a recent version of a modern web browser(Chrome, Edge, etc.) | Any OS |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Manos Samatas is a Solutions Architect specializing in Big Data and Analytics. He has several years of experience developing and designing big data applications for various industries, including telecommunications, cybersecurity, healthcare, and public sector. He is an accredited AWS Subject Matter Expert (SME) in Analytics and he is certified with the AWS Data Analytics Specialty and the AWS Solutions Architect Professional certifications. Manos lives in London with his fiancé Gabriela. In his free time, he enjoys traveling, socializing with friends, and taking care of his plants.
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.
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