This document provides an overview and hands-on guide to using Amazon QuickSight for data analytics. It introduces the QuickSight workflow, supported data sources like Redshift, different visual types, and how to filter and sort data. The hands-on section walks through creating a connection to a Redshift database, building a dataset, developing an analysis with visualizations, and publishing and sharing a dashboard. It demonstrates features like conditional formatting, calculated fields, and parameters.

1. INTRODUCTION
TO QUICKSIGHT
D ATA A N A LY T I C S A N D T E C H N O LO G Y T E A M

2. AGENDA
• AWS QuickSight Workflow
• Supported Data Sources
• Visual Types
• Filtering and sorting data in visual
• Sample Dashboard
• Resources
• Hands-on section
– Create a connection to a Redshift account
– Create a dataset
– Create an analysis
– Create a visual and data type manipulation
– Publish the dashboard
– Advanced features like conditional formatting, calculated fields, parameters and controls
– Share dashboard and schedule reports

4. SUPPORTED DATA SOURCES

5. VISUAL TYPES

6. USING FILTERS

7. SORTING DATA IN A VISUAL

8. A SAMPLE DASHBOARD

9. HANDS-ON: CREATE CONNECTION TO A REDSHIFT CLUSTER
• On the Amazon QuickSight start page, choose Datasets.
• On the Datasets page, choose New dataset.
• From the list of available sources choose Redshift (Manual connect).
• Data source name – name of your choice
• Connection type – Public network
• Database server – url for server connection
• Port – connection port number
• Database name – name of database you wish to establish connection
with
• Username – credential username
• Password – credential password
• Validate connection on filling all the details
• On successful validation Create data source
• The data source is created as shown below

10. HANDS-ON: CREATE A DATASET
Import table Custom SQL query

11. HANDS-ON: DATASET DETAILS AND OPTIONS
Name | Size | Import Status |Rows | Last
refreshed
• Refresh Now – to initiate an instant refresh
• Schedule refresh – plan a recurring refresh
• Delete data set – remove the dataset along with all related
analyses and dashboard
• Edit data set – make changes to the data set
• Duplicate data set – make a copy of the data set for some
other application/dashboard
• Share – provide access to this dataset to other members of
the group
• Create analysis – use this data set in a new analysis
• Column and Row level security – provide selective access
to data segments

12. HANDS-ON: SCHEDULE REFRESH

13. HANDS-ON: QUERY EDITOR

14. HANDS-ON: DATA MANIPULATION
Select fields
Rename fields
Change data type

15. HANDS-ON: CREATE AN ANALYSIS

16. HANDS-ON: CREATE A VISUAL

17. HANDS-ON: CONDITIONAL FORMATTING

18. HANDS-ON: CALCULATED FIELDS

19. HANDS-ON: PARAMETERS AND CONTROLS

20. HANDS-ON: PARAMETERS AND CONTROLS

21. HANDS-ON: PARAMETERS AND CONTROLS

22. HANDS-ON: PUBLISH DASHBOARD

23. HANDS-ON: SHARE DASHBOARD

24. RESOURCES
• Home Page https://us-east-1.quicksight.aws.amazon.com/sn/start
• Documentation https://docs.aws.amazon.com/quicksight/index.html
• Slack group - #quicksight-users https://amzn-
operations.slack.com/archives/C017WCBENKG
• Sample dataset