Course Outline


  • Overview of AWS QuickSight
  • What is AWS and QuickSight

Getting Started with AWS QuickSight

  • Creating an AWS and QuickSight account
  • Understanding the QuickSight workflow
  • Navigating the QuickSight UI

Preparing Data in QuickSight

  • Understanding data preparation in QuickSight
  • SPICE vs. direct query
  • Uploading and importing data to QuickSight
  • Working with columns and fields
  • Understanding calculated fields, functions, and operators
  • Adding calculated fields using strings to our project
  • Extracting information out of strings
  • Using conditional functions
  • Creating calculated fields with numeric values
  • Adding different filters to a project

Analyzing and Visualizing Data

  • Understanding the difference between preparing and analyzing data
  • Creating the data analysis
  • Creating visuals
  • Understanding dimensions and measures
  • Adding additional data sets
  • Field formatting, aggregation, and granularity
  • Formatting visuals
  • Creating a story and treemap
  • Using filters and tables
  • Adding a KPI visual

Exporting and Sharing Project Data

  • Understanding refresh and schedule refresh
  • Exporting project data as .csv files
  • Adding users to an account
  • Sharing data set and analysis
  • Creating and sharing dashboards

Using Databases as Data Sources

  • Setting up a database
  • Preparing dummy data
  • Connecting QuickSight to a database
  • Importing data into SPICE
  • Importing data as a Query
  • Importing calculated fields and query
  • Using NoSQL databases

Summary and Next Steps


  • Basic knowledge and understanding of data analysis


  • Data analysts
  • Anyone who is interested in data analysis and visualization
  14 Hours


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