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Course Outline
Introduction
Installing and Configuring Cloud-Native Apache Superset
- Using Docker to initialize development environment
- Using Python's setup tools and pip
Overview of Basic Features and Architecture of Apache Superset
- Rich visualizations
- Easy-to-navigate user interface
- Integration with most databases
Connecting Data to Apache Superset
- Configuring data input
- Improving the input process
Conducting Advanced Data Analytics
- Getting a rolling average of the time series
- Working with Time Comparison
- Resampling the data using various methods
- Scheduling queries in SQL Lab
Performing Advanced Visualization
- Creating a Pivot Table
- Exploring different visualization types
- Building a visualization plugin
Creating and Sharing Dynamic Dashboards
- Adding Annotations to Your Chart
- Using REST API
Integrating Apache Superset with Databases
- Apache Druid
- BigQuery
- SQL Server
Managing Security in Apache Superset
- Understanding provided roles and creating new roles
- Customizing permissions
Troubleshooting
Summary and Conclusion
Requirements
- Experience with business intelligence and data visualization
- Familiar with Apache Superset fundamentals
Audience
- Data analysts
- Data scientists
- Data engineers
14 Hours
Testimonials (1)
Without a doubt, learn the general environment of and put the tool into practice Apache Superset.
Saul - N/A
Machine Translated
