Amazon (AWS) QuickSight – Getting Started

Course Curriculum

Chapter 1: Welcome & First Steps

Lecture 1: Welcome to This Course

Lecture 2: What is QuickSight?

Lecture 3: What is AWS?

Lecture 4: Join our Online Learning Community

Lecture 5: AWS – A Closer Look (Optional)

Lecture 6: Let's Start: Creating our AWS and QuickSight Accounts

Lecture 7: Starting Our First Project

Lecture 8: Creating our First Visual

Lecture 9: Course Outline

Chapter 2: QuickSight – Starting with the Basics

Lecture 1: The Development of QuickSight

Lecture 2: Understanding the Workflow

Lecture 3: Looking at the Interface

Lecture 4: SPICE – What it that actually?

Lecture 5: Pricing and Editions of QuickSight

Chapter 3: Preparing our Data

Lecture 1: Module Introduction

Lecture 2: Before we Start: Understanding Data Preparation in QuickSight

Lecture 3: Loading Data: SPICE vs. Direct Query

Lecture 4: Introducing AWS S3

Lecture 5: Uploading Data and Importing Data to QuickSight

Lecture 6: A Closer Look at the Interface

Lecture 7: Working with Columns and Fields

Lecture 8: Taking a First Look at Calculated Fields

Lecture 9: Understanding Functions and Operators

Lecture 10: Adding Calculated Fields using Strings to our Project

Lecture 11: Extracting Information out of Strings

Lecture 12: Working with Conditional Functions

Lecture 13: Another Look at the IF-Function

Lecture 14: Creating Calculated Fields with Numeric Values

Lecture 15: Adding Different Filters to our Project

Lecture 16: A Little Helper: Dealing with Skipped Rows

Lecture 17: Module Summary

Chapter 4: Analyzing and Visualizing our Data

Lecture 1: Module Introduction

Lecture 2: Preparing Data vs. Analyzing Data – Understanding the Differences

Lecture 3: Creating the Analysis

Lecture 4: Understanding the Interface and Creating our First Visual

Lecture 5: Understanding Dimensions and Measures

Lecture 6: Adding Additional Data Sets to our Analysis

Lecture 7: Understanding Field Formatting, Aggregation and Granularity

Lecture 8: Formatting our Visuals

Lecture 9: Adding Drill-Down

Lecture 10: Creating our First Story

Lecture 11: Creating a Treemap

Lecture 12: Applying Filters

Lecture 13: Understanding Pivot Tables

Lecture 14: Continuing our Story

Lecture 15: Understanding Heat Maps

Lecture 16: Adding a KPI visual

Lecture 17: Adding the Final Scene to our Story

Lecture 18: Module Summary

Chapter 5: Refreshing, Exporting and Sharing our Project Data

Lecture 1: Module Introduction

Lecture 2: Our Ways to Continue

Lecture 3: Understanding Refresh and Schedule Refresh

Lecture 4: Exporting our Project Data as .csv Files

Lecture 5: Adding Users to our Account – Some Theory

Lecture 6: AWS – More about IAM (Optional)

Lecture 7: Adding a User to our Account – Continuing with the Project

Lecture 8: Sharing our Data Set

Lecture 9: Sharing our Analysis

Lecture 10: Creating and Sharing Dashboards

Lecture 11: Managing Capacity and Understanding Subscriptions

Lecture 12: Taking a Quick Look at the Mobile App

Lecture 13: Module Summary

Chapter 6: Databases as Data Sources

Lecture 1: Module Introduction

Lecture 2: Setting up a Database (Optional)

Lecture 3: More Information about AWS RDS

Lecture 4: Preparing Dummy Data (Optional)

Lecture 5: Connecting Quicksight to a Database

Lecture 6: More Resources about Connecting Quicksight to Databases

Lecture 7: Importing Data into SPICE

Lecture 8: Importing Data as a Query

Lecture 9: Calculated Fields & Query Imports

Lecture 10: What about NoSQL Databases?

Lecture 11: Wrap Up

Chapter 7: Course Roundup

Lecture 1: Course Roundup