Training AWS

Training goals

code: AWS-AVAUAQ

In this 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

Intended audience

This course is intended for:

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

Conspect Show list

  • 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
  • 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
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Additional information

Prerequisites

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
Difficulty level
Duration 2 days
Certificate

The participants will obtain certificates signed by AWS (course completion).
Trainer

AWS Authorized Instructor (AAI)

Other training AWS | Data Analytics

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Sessions organised at Compendium CE are usually held in our locations in Kraków and Warsaw, but also in venues designated by the client. The group participating in training meets at a specific place and specific time with a coach and actively participates in laboratory sessions.

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