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

Editing datasets

In this section, we will look more closely at the typical tasks an author user needs to do to edit a dataset. In real-world applications, it is common that datasets might need some degree of processing so that they can be used optimally by QuickSight.

These tasks include the following:

  • Importing into SPICE
  • Renaming fields
  • Changing the field types
  • Adding calculated fields
  • Combining datasets together
  • Applying security filters

In the next section, we will learn how to complete these tasks using the example dataset we configured earlier.

Importing into SPICE

It's time for us to learn how to import a dataset into SPICE. We will change the query mode using the dataset editor and then we will observe the status of the import job. Finally, we will learn how to schedule automatic refresh jobs for our SPICE datasets.

Setting the dataset query mode

Earlier in this chapter, we configured a Redshift dataset as a Direct Query...