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)
1
Section 1: Introduction to Amazon QuickSight and the AWS Analytics Ecosystem
6
Section 2: Advanced Dashboarding and Insights
10
Section 3: Advanced Topics and Management

Working with ML insights

QuickSight has a special type of insight where the results are driven from ML-based computations. QuickSight supports two types of ML insights:

  • Forecasting
  • Anomaly detection

In the next section, we will learn how to configure each of these types of insights.

Working with forecasting insights

We learned how to add forecasting in a line graph visual. QuickSight also allows you to add forecasting as a narrative to display forecasted values. For example, how many miles is expected to be traveled between Manhattan and Queens on a specific date?

To better understand how to configure this type of visual, we will use our example New York Taxi analysis to answer this question:

  1. First, let's create a new insight and select Forecast ML-Powered Insight from the drop-down list.
  2. For this example, let's assume that we want the user to choose the pick-up borough and the destination borough (drop-off borough). To achieve...