Book Image

Effective Business Intelligence with QuickSight

By : Rajesh Nadipalli
Book Image

Effective Business Intelligence with QuickSight

By: Rajesh Nadipalli

Overview of this book

Amazon QuickSight is the next-generation Business Intelligence (BI) cloud service that can help you build interactive visualizations on top of various data sources hosted on Amazon Cloud Infrastructure. QuickSight delivers responsive insights into big data and enables organizations to quickly democratize data visualizations and scale to hundreds of users at a fraction of the cost when compared to traditional BI tools. This book begins with an introduction to Amazon QuickSight, feature differentiators from traditional BI tools, and how it fits in the overall AWS big data ecosystem. With practical examples, you will find tips and techniques to load your data to AWS, prepare it, and finally visualize it using QuickSight. You will learn how to build interactive charts, reports, dashboards, and stories using QuickSight and share with others using just your browser and mobile app. The book also provides a blueprint to build a real-life big data project on top of AWS Data Lake Solution and demonstrates how to build a modern data lake on the cloud with governance, data catalog, and analysis. It reviews the current product shortcomings, features in the roadmap, and how to provide feedback to AWS. Grow your profits, improve your products, and beat your competitors.
Table of Contents (15 chapters)
Effective Business Intelligence with QuickSight
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

From data to visualization using QuickSight


Let's review the steps involved in getting to the visualization stage from source data.

  1. First, to work with data, we need to create QuickSight datasets, which typically include one or more tables, or files, from the source.

  2. Optionally, if the dataset needs some cleanup or format changes, you can prepare data using the QuickSight SPICE engine.

  3. From each dataset, we can create one or more analyses, which are containers for visualizations.

  4. Within each analysis, we can create one or more visualizations. A visualization is a graphical representation on a dataset enabling consumers to get insights from the data.

  5. Optionally, you can add scenes to the default story to provide a narrative about the insights.

  6. Optionally, you can create read-only snapshots of the visualizations as dashboards and share the insights with others.

Note

For further information on dataset creation, refer to Chapter 3, Spice up Your Data.

The preceding steps to get to visualizations are...