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Actionable Insights with Amazon QuickSight

Actionable Insights with Amazon QuickSight

By : Samatas
4.8 (5)
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Actionable Insights with Amazon QuickSight

Actionable Insights with Amazon QuickSight

4.8 (5)
By: 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)
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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

Chapter 1: Introducing the AWS Analytics Ecosystem

As data increases in both volume and variety, organizations from all verticals are adopting cloud analytics services for their data analytics. AWS offers a number of analytics services covering data lakes, data warehousing, big data processing, extract, transform, load (ETL), and data visualization. In this chapter, we will introduce the AWS analytics ecosystem. Some of the services we discuss here will be mentioned again later in the book.

First, we will map the AWS services into categories. Then, we will discuss how Amazon QuickSight fits into the wider AWS analytics ecosystem. We will look more closely at a modern Lake House architecture and we will discuss its benefits and its components. Finally, we will provide a step-by-step guide to set up a data Lake House architecture on AWS and load and query a demo data sample. Some of this information may already be familiar to you, but let's go back over the basics.

In this chapter, we will cover the following topics:

  • Discovering the AWS analytics ecosystem
  • Exploring the data Lake House architecture on AWS
  • Creating a basic Lake House architecture
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