Learn AWS Quicksight Data Visualization and Analytics With Practical Lab Exercises

This course covers basic to advanced data visualization techniques. This course is for students with no or little experience in data analytics. The course is broken down into 11 modules. The course begins with an introduction to data visualization and analytics. It also explains the differences between the two. The course also covers how to set up Quicksight and AWS accounts to enable students to use the visualization tool. The course will include an overview of Quicksight and AWS. Data analysts deal with all types of analysis and visualizations every day. This section also covers the types of data that can be effectively represented using visuals.

This course covers data preparation, transformation, and import from multiple sources. Lab sessions provide a detailed look at various visualization structures, such as pivot tables and tables. This aspect of data analysis is very important and has been discussed in detail throughout the lab sessions. Quicksight also has filters and controls, which are described with examples. Practical lab sessions are used to cover each section.

The capstone project is the final part of the course. It explains the process from start to finish for data visualization with Quicksight. After that, the student can gain practical insight into the course.

Students will have a solid knowledge of data visualization and analytics with AWS Quicksight by the end of this course. They will also have practical experience in designing analysis and visualization.