In AWS QuickSight course, you will build a data visualization solution using Amazon QuickSight. QuickSight allows everyone in your organization to understand your data by exploring through interactive dashboards, asking questions in natural language, or automatically looking for patterns and outliers powered by machine learning. This course focuses on connecting to data sources, building visuals, designing interactivity, and creating calculations. You will learn how to apply security best practices to your analyses. You will also explore the machine learning capabilities built into QuickSight.
Course Objectives:
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
Course content
Authoring Visual Analytics Using Amazon QuickSight
Introduction and Overview of Amazon QuickSight
- Introducing Amazon QuickSight
- Why use Amazon QuickSight for data visualization
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
- Lab: Create your first dashboard
Tables
- Introduction to Tables
- Sorting and Formatting
- Cross Filtering
- Working with Dates
- Conditional Formatting
- Lab: Tables
- Lab: Methods of Aggregation
Pivot Tables and KPI’s
- Introduction to Pivot Tables and KPI
- Create Pivot Tables
- Methods of Aggregation
- Percentage Calculations
- KPI Visualization
- Lab: KPI and Pivot Tables
Tables and Calculations
- Introduction to Table Calculations
- Running Totals and Rankings
- Difference From Calculations
Filters
- Introduction to Filters
- Numeric Filters
- Date Filters
- Lab: Filters
Controls
- Introduction to Controls
- Text Controls
- Numeric Controls
- Date Controls
- Parameters and Actions
Graph Visualizations
- Introduction to Graphs Visualizations
- Line graphs
- Area Graphs
- Column and Bar graphs
- Pie graph
- Other Graphs
- Lab: Visualizations
Dashboards
- Introduction to Dashboards
- Create dashboards
- Publish and Share dashboards
- Work with Themes
- Lab: Create Dashboard
Calculated Columns
- Introduction to Calculations
- Download Training Data File
- Creating a Calculated Column
- Date Calculated Fields
- IFELSE Function
- Lab: Calculated Columns
Measures
- Introduction to Measures
- Creating Measures
- SUMIF Function
- Lab: Measures
Relationships
- Introduction to Relationships
- Download Training Data Files
- Create relationships
- Lab: Human Resource Data
Data Preparation
- Introduction to Data Preparation
- Data Preparation
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
- Lab: Enhancing your dashboard
Preparing Datasets for Analysis
- Working with datasets
- Demonstration: Transform your datasets for analysis
- Lab: Preparing data for analysis
Performing Advanced Data Calculations
- Transform data using advanced calculations
- Lab: Performing advanced data calculations
- Lab: Designing a Visual Analytics Solution
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
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
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Course Prerequisites
- Students with a minimum one-year experience authoring visual analytics will benefit from this course.
Who can attend
This course is intended for:
- Data and business analysts who build and manage business analytics dashboards
- People currently using Microsoft and Google tools and want to learn AWS QuickSight
Number of Hours: 30hrs
Certification
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- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
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- Materials
- Preparing for Certification
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