In this course, you will learn to:

• Explain the benefits, use cases, and key features of Amazon QuickSight
• Design, create, and customize QuickSight dashboards to visualize data and extract business insights from it
• Select and configure appropriate visualization types to identify, explore, and drill down on business insights
• Describe how to use one-click embed to incorporate analytics into applications
• Connect, transform, and prepare data for dashboarding consumption
• Perform advanced data calculations on QuickSight analyses
• Describe the security mechanisms available for Amazon QuickSight
• Apply fine-grained access control to a dataset
• Implement machine learning on data sets for anomaly detection and forecasting
• Explain the benefits and key features of QuickSight Q to enhance the dashboard user experience

Day 1

Module 1: Introduction and Overview of Amazon QuickSight

• Introducing Amazon QuickSight
• Why use Amazon QuickSight for data visualization

Module 2: Getting Started with Amazon QuickSight

• Interacting with Amazon QuickSight
• Loading data into Amazon QuickSight
• Visualizing data in Amazon QuickSight
• Demonstration: Walkthrough of Amazon QuickSight interface
• Practice Lab: Create your first dashboard

Module 3: Enhancing and Adding Interactivity to Your Dashboard

• Enhancing your dashboard
• Demonstration: Optimize the size, layout, and aesthetics of a dashboard
• Enhancing visualizations with interactivity
• Demonstration: Walkthrough of dashboard interactivity features
• Practice Lab: Enhancing your dashboard

Module 4: Preparing Datasets for Analysis

• Working with datasets
• Demonstration: Transform your datasets for analysis
• Practice Lab: Preparing data for analysis

Module 5: Performing Advanced Data Calculations

• Transform data using advanced calculations
• Practice Lab: Performing advanced data calculations

Activity: Designing a Visual Analytics Solution

Day 2

Module 6: Overview of Amazon QuickSight Security and Access Control

• Overview of Amazon QuickSight security and access control
• Dataset access control in Amazon QuickSight
• Lab: Implementing access control in Amazon QuickSight visualizations

Module 7: Exploring machine learning capabilities

• Introducing Machine Learning (ML) insights
• Natural Language Query with QuickSight Q
• Demonstration: Using QuickSight Q
• Lab: Using machine learning for anomaly detection and forecasting

End of day challenge labs

• Join data sources together
• Create a dashboard
• Enhance the dashboard and add interactivity
• Perform advanced data calculations
• Integrate machine learning tools into the dashboard

This course is intended for:

• Data and business analysts who build and manage business analytics dashboards

Students with a minimum one-year experience authoring visual analytics will benefit from this course.

We recommend that attendees of this course have:

• Completed Data Analytics Fundamentals