Amazon QuickSight is a cloud-powered business intelligence (BI) service that makes it easy to deliver insights from your data. A training course on Amazon QuickSight would typically cover the following content to ensure you can effectively use the tool for data visualization, analysis, and reporting.

Why should you choose Nisa For Amazon QuickSight Training?

Nisa Trainings is the best online training platform for conducting one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and happy to clarify your doubts anytime. Our teaching style at Nisa Trainings is entirely hands-on. You’ll have access to our desktop screen and will be actively conducting hands-on labs on your desktop.

Job Assistance

If you face any problem while working on Amazon QuickSight Course, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.

The Process we follow for our Online Job Support Service:

• We receive your inquiry for Online Job
• We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re
• If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, we will only agree to provide service. And then you have to make the payment to get the service from
• We will fix the timing for Online Job Support as mutually agreed by you and our consultant.

Course Information

Amazon QuickSight Training

Duration: 25 Hours

Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)

Training Method: Instructor Led Online One-on-One Live Interactive

Sessions.

COURSE CONTENT :

1. Introduction to Amazon QuickSight

• Overview of Amazon QuickSight and its capabilities
• Key benefits of using QuickSight for business intelligence
• Understanding the architecture of QuickSight (e.g., data sources, datasets, analyses)

2. Setting Up Amazon QuickSight

• Signing up for Amazon QuickSight
• Understanding QuickSight’s pricing and user management
• Navigating the QuickSight interface (dashboards, analyses, data sets)
• Setting up AWS permissions (IAM roles)

3. Data Preparation and Importing Data

• Connecting to various data sources (e.g., Amazon S3, RDS, Redshift, Athena, Excel)
• Importing datasets from different sources
• Data transformation and cleaning in QuickSight
• Data wrangling using built-in tools (e.g., filters, aggregations)

4. Creating Datasets

• Creating datasets from various data sources
• Understanding different types of datasets: SPICE (Super-fast, Parallel, In-memory Calculation Engine) vs. Direct Query
• Data field types and custom calculations
• Setting up data refresh schedules

5. Building Visualizations

• Introduction to different types of visualizations (e.g., bar charts, line graphs, pie charts, heat maps)
• Choosing the right visualization for your data
• Customizing visualizations (colors, axes, labels, etc.)
• Adding filters, controls, and parameters for dynamic analysis
• Drill-down and drill-through capabilities

6. Advanced Visualization Techniques

• Using custom visuals (e.g., KPI, bullet chart)
• Working with geospatial data and maps
• Combining multiple visualizations in a dashboard
• Implementing calculated fields and advanced metrics

7. Creating Dashboards

• Designing and arranging interactive dashboards
• Using dashboard controls (filters, drop-down menus)
• Sharing and publishing dashboards
• Embedding dashboards in other applications or websites

8. Data Sharing and Collaboration

• Sharing QuickSight analyses and dashboards with team members
• Setting up email reports and automatic scheduling
• Permissions and access control (viewers, authors, admins)

9. Advanced Features

• User management and roles in QuickSight
• Setting up row-level security (RLS) for controlling data access
• Advanced analytics with ML Insights and forecasting
• Using AWS Lambda functions with QuickSight

10. Performance and Cost Optimization

• Optimizing dataset performance with SPICE
• Managing costs of data storage and query execution
• Monitoring usage and performance through the QuickSight console

11. Best Practices

• Designing effective visualizations for business intelligence
• Organizing datasets and analyses for ease of use and collaboration
• Tips for troubleshooting common issues