Learning Amazon Web Services (AWS) QuickSight
5.0 /5- Offered byLinkedin Learning
Learning Amazon Web Services (AWS) QuickSight at Linkedin Learning Overview
Duration | 5 hours |
Total fee | ₹899 |
Mode of learning | Online |
Difficulty level | Beginner |
Credential | Certificate |
Learning Amazon Web Services (AWS) QuickSight at Linkedin Learning Highlights
- Earn a sharable certificate
- 1 exercise file
- Access on tablet and phone
Learning Amazon Web Services (AWS) QuickSight at Linkedin Learning Course details
- Amazon Web Services (AWS) QuickSight is a powerful data analytics and visualization tool for monitoring data, analyzing trends, and making decisions
- Learner can leverage ETL processes to get data, shape it into a viable form for calculations and analysis, then load the data into the visualization interface
- Learn how to connect to data sources, including Excel files, S3 buckets, and SQL Server; transform data and add calculations; load data into the QuickSight visualization interface; and create and format engaging visualizations and dashboards
Learning Amazon Web Services (AWS) QuickSight at Linkedin Learning Curriculum
Introduction
Understand your data with QuickSight
What you should know
Getting Started with AWS QuickSight
Introducing Amazon Web Services (AWS) and QuickSight
Comparing cloud vs. desktop applications
Introducing visual components
Extracting Data
Overviewing supported data sources
Leveraging super-fast, parallel, in-memory, calculation engine (SPICE)
Connecting to files
Connecting to AWS cloud services
Connecting to corporate data sources
Connecting to SaaS
Understanding data source limitations and settings
Challenge: Connecting to data
Solution: Connecting to data
Transforming Data
Renaming fields
Removing fields
Filtering rows
Changing data types
Creating calculated fields
Adding conditional fields
Setting up geospatial grouping
Challenge: Transforming data
Solution: Transforming data
Loading Data
Creating data sets
Sharing data sets
Refreshing data
Joining tables
Deleting data sets
Creating Visualizations
Creating visuals
Exploring visualization options
Aggregating measures
Formatting visuals
Sorting data logically
Filtering visuals
Adding color themes
Leveraging conditional formatting
Creating table calculations
Challenge: Creating visualizations
Solution: Creating visualizations
Configuring Dashboards
Introducing visualization best practices
Interacting between visualizations
Drilling down into visuals
Utilizing parameters
Adding on-screen controls
Creating stories
Leveraging ML Insights
Challenge: Configuring dashboards
Solution: Configuring dashboards
Sharing Your Analysis
Navigating dashboard of visualizations
Emailing reports
Viewing on a mobile device
Exporting reports and data
Setting up anomaly alerts
Embedding dashboards
Conclusion
Next steps for understanding your data
Learning Amazon Web Services (AWS) QuickSight at Linkedin Learning Faculty details
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