Course Outline
Introduction
- Overview of AWS QuickSight.
- Understanding AWS and QuickSight.
Getting Started with AWS QuickSight
- Creating an AWS and QuickSight account.
- Understanding the QuickSight workflow.
- Navigating the QuickSight user interface.
Preparing Data in QuickSight
- Understanding data preparation in QuickSight.
- SPICE versus 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 from strings.
- Using conditional functions.
- Creating calculated fields with numeric values.
- Adding various filters to a project.
Analyzing and Visualizing Data
- Distinguishing between preparing and analyzing data.
- Creating data analysis.
- Developing visuals.
- Understanding dimensions and measures.
- Incorporating additional data sets.
- Field formatting, aggregation, and granularity.
- Formatting visuals.
- Creating stories and treemaps.
- Using filters and tables.
- Adding a KPI visual.
Exporting and Sharing Project Data
- Understanding refresh and scheduled refresh.
- Exporting project data as .csv files.
- Adding users to an account.
- Sharing data sets and analyses.
- 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 queries.
- Using NoSQL databases.
Summary and Next Steps
Requirements
- Basic knowledge and understanding of data analysis.
Audience
- Data analysts.
- Anyone interested in data analysis and visualization.
Testimonials (5)
That it was very practical.
Alfonso Ramos - Banco de Mexico
Course - Fundamentos de Integración de Datos Pentaho
Machine Translated
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
he was well prepared - and he is very sympathetic
Oliver - Post CH AG
Course - Splunk Fundamentals
Used good examples, good pace of the training and covered most things
David - McGraw Hill
Course - Data Preparation with Alteryx
lots of pratical exercises
