Course Outline
Introduction
Installing and Configuring Cloud-Native Apache Superset
- Using Docker to initialize the 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
- Calculating a rolling average of time series data.
- Working with time comparisons.
- Resampling data using various methods.
- Scheduling queries in SQL Lab.
Performing Advanced Visualization
- Creating pivot tables.
- Exploring different visualization types.
- Building a visualization plugin.
Creating and Sharing Dynamic Dashboards
- Adding annotations to charts.
- Using the REST API.
Integrating Apache Superset with Databases
- Apache Druid.
- BigQuery.
- SQL Server.
Managing Security in Apache Superset
- Understanding existing roles and creating new ones.
- Customizing permissions.
Troubleshooting
Summary and Conclusion
Requirements
- Experience with business intelligence and data visualization.
- Familiarity with the fundamentals of Apache Superset.
Audience
- Data analysts.
- Data scientists.
- Data engineers.
Testimonials (2)
Gunnar was a great trainer. He pitched the training at the right level given the varying levels of experience and expertise of the attendees. He was very personable and injected as much as excitement and humour as he could across the 2 days. He made sure that we were engaged throughout and tried to ensure that all our questions were answered in an open and honest manner.
Seaman - PowerX Technology Ltd
Course - Getting Started with Apache Superset
The trainer was knowledgeable and interacted well with the participants.
