Amazon (AWS) QuickSight - Getting Started

Get started with Amazon QuickSight - AWS' Business Intelligence (BI) answer to Tableau and Power BI

  1. Courses
  2. Amazon (AWS) QuickSight - Getting Started

Working with modern Business Intelligence tools is exciting. Although the market offers a broad variety of tools, you may not have found the tool that meets all your requirements yet. This course might change that!

In this course, you will learn how to use one of the latest Business Intelligence tools released to the market: Amazon QuickSight, a tool which allows you to easily analyze and visualize data. But what makes QuickSight special? QuickSight is a cloud solution and completely integrated into Amazon Web Services (AWS). With that, it can be easily connected to a broad variety of services and sources which make QuickSight a highly scalable, easy-to-use and very flexible data analysis tool.

This course will give you a first overview of QuickSight including the following topics:

  • How to use QuickSight and its different functions
  • Understand the workflow of QuickSight
  • How to connect QuickSight to different data sources within and outside of AWS
  • How to prepare your data in QuickSight, for example by adding filters and calculated fields
  • How to easily create your analysis by building multiple visuals
  • How to create dashboards and stories
  • Share your project results with people within and outside your organization
  • How to use the iOS mobile app
  • Understand the user management of QuickSight
  • And more!

These topics will be covered throughout this course, but is this your course?

If you...

  • ... never worked with QuickSight and want to get started with it
  • ... are looking for a cloud based Business Intelligence tool to quickly analyze your data
  • ...have worked with other Business Intelligence tools but want to take a look at new tools
  • ... already worked with AWS and now want to understand how to analyze and visualize your data using a service within the AWS universe
  • ...are generally interested into data analysis

...then this course is made for you!

Section: Getting Started

1. Welcome to This Course (2:14)
2. What is QuickSight? (3:50)
3. Join our Online Learning Community (1:00)
4. What is AWS? (2:36)
5. [OPTIONAL] AWS – A Closer Look (1:00)
6. Let's Start: Creating our AWS and QuickSight Accounts (8:15)
7. Starting Our First Project (8:05)
8. Creating our First Visual (8:03)
9. Course Outline (1:40)

Section: QuickSight - Starting with the Basics

10. The Development of QuickSight (2:18)
11. Understanding the Workflow (2:39)
12. Looking at the Interface (6:22)
13. SPICE - What it that actually? (3:44)
14. Pricing and Editions of QuickSight (2:40)

Section: Preparing our Data

15. Module Introduction (1:49)
16. Before we Start: Understanding Data Preparation in QuickSight (3:55)
17. Loading Data: SPICE vs. Direct Query (3:53)
18. Introducing AWS S3 (6:13)
19. Uploading Data and Importing Data to QuickSight (12:47)
20. A Closer Look at the Interface (6:49)
21. Working with Columns and Fields (6:38)
22. Taking a First Look at Calculated Fields (5:04)
23. Understanding Functions and Operators (4:03)
24. Adding Calculated Fields using Strings to our Project (11:11)
25. Extracting Information out of Strings (2:43)
26. Working with Conditional Functions (8:24)
27. Another Look at the IF-Function (4:04)
28. Creating Calculated Fields with Numeric Values (3:11)
29. Adding Different Filters to our Project (6:08)
30. A Little Helper: Dealing with Skipped Rows (2:49)
31. Module Summary (1:32)
32. Assignment: Basics (Problem) (10:59)
33. Assignment: Basics (Solution) (1:33)

Section: Analyzing and Visualizing our Data

34. Module Introduction (1:07)
35. Preparing Data vs. Analyzing Data - Understanding the Differences (2:36)
36. Creating the Analysis (2:50)
37. Understanding the Interface and Creating our First Visual (9:08)
38. Understanding Dimensions and Measures (2:55)
39. Adding Additional Data Sets to our Analysis (9:07)
40. Understanding Field Formatting, Aggregation and Granularity (5:25)
41. Formatting our Visuals (6:04)
42. Adding Drill-Down (3:28)
43. Creating our First Story (3:57)
44. Creating a Treemap (1:43)
45. Applying Filters (13:09)
46. Understanding Pivot Tables (11:17)
47. Continuing our Story (1:26)
48. Understanding Heat Maps (2:35)
49. Adding a KPI visual (8:02)
50. Adding the Final Scene to our Story (1:07)
51. Module Summary (1:17)
52. Assignment: Visualizations (Problem) (1:03)
53. Assignment: Visualizations (Solution) (10:18)

Section: Refreshing, Exporting and Sharing our Project Data

54. Module Introduction (1:08)
55. Our Ways to Continue (1:37)
56. Understanding Refresh and Schedule Refresh (6:42)
57. Exporting our Project Data as .csv Files (1:44)
58. Adding Users to our Account - Some Theory (4:02)
59. AWS - More about IAM (Optional) (1:00)
60. Adding a User to our Account - Continuing with the Project (8:07)
61. Sharing our Data Set (4:44)
62. Sharing our Analysis (4:59)
63. Creating and Sharing Dashboards (4:27)
64. Managing Capacity and Understanding Subscriptions (5:55)
65. Taking a Quick Look at the Mobile App (1:59)
66. Module Summary (1:37)

Section: Databases as Data Sources

67. Module Introduction (0:54)
68. Setting up a Database (Optional) (6:04)
69. More Information about AWS RDS (1:00)
70. Preparing Dummy Data (Optional) (4:28)
71. Connecting Quicksight to a Database (8:32)
72. More Resources about Connecting Quicksight to Databases (1:00)
73. Importing Data into SPICE (5:42)
74. Importing Data as a Query (5:58)
75. Calculated Fields & Query Imports (2:02)
76. What about NoSQL Databases? (1:35)
77. Wrap Up (1:53)

Section: Course Roundup

78. Roundup (1:58)

Course Instructor


Manuel Lorenz

Having worked as a business analyst in both a major consultancy and an investment bank, I always found myself confronted with both various and complex problem sets and challenging client demands. The rapid development of technology and business requirements forces everyone to constantly adapt and to continue learning. Since I always found it hard to find high quality, understandable and comprehensive learning materials, I decided to create such materials on my own. Together with Maximilian Schwarzmüller I founded Academind to offer the best possible learning experience on web development and data science to our more than 1,000,000 students worldwide.