Book Image

Actionable Insights with Amazon QuickSight

By : Manos Samatas
Book Image

Actionable Insights with Amazon QuickSight

By: Manos Samatas

Overview of this book

Amazon Quicksight is an exciting new visualization that rivals PowerBI and Tableau, bringing several exciting features to the table – but sadly, there aren’t many resources out there that can help you learn the ropes. This book seeks to remedy that with the help of an AWS-certified expert who will help you leverage its full capabilities. After learning QuickSight’s fundamental concepts and how to configure data sources, you’ll be introduced to the main analysis-building functionality of QuickSight to develop visuals and dashboards, and explore how to develop and share interactive dashboards with parameters and on-screen controls. You’ll dive into advanced filtering options with URL actions before learning how to set up alerts and scheduled reports. Next, you’ll familiarize yourself with the types of insights before getting to grips with adding ML 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.
Table of Contents (15 chapters)
Section 1: Introduction to Amazon QuickSight and the AWS Analytics Ecosystem
Section 2: Advanced Dashboarding and Insights
Section 3: Advanced Topics and Management

Working with insights

QuickSight insights offer a set of features that allow you to express insights from data using natural language. QuickSight can automatically interpret a diagram and suggest narratives that you can quickly add to your analysis. In addition to that, you can build your own custom narrative. In this section, we will do the following:

  • Learn how to use suggested insights.
  • Create and edit a custom insight.

Adding suggested insights

To better understand the autonarrative features, we will use the example New York Taxi analysis. Let's start with the Sankey diagram to discover interesting insights from the data:

  1. First, open the analysis and select any visual by clicking on it.
  2. Next, click on the insights icon to reveal the Suggested insights list, as shown here:

Figure 6.4 – Selecting the suggested insights

Next, we will select an insight that looks interesting to display. For example, we can...