Apache Superset is an open-source data visualization and business intelligence (BI) platform that allows users to explore, analyze, and visualize data through interactive dashboards and charts. This training program provides a comprehensive overview of Superset’s features, guiding users from the basics to more advanced functionality.

Why should you choose Nisa For Apache Superset 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 Apache Superset 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

Apache Superset 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 :

Module 1: Introduction to Apache Superset

• Overview of Apache Superset and its capabilities
• Installing Apache Superset locally or on a server
• Understanding Superset’s architecture and components
  • Frontend, backend, and database integration
• User interface walkthrough: main sections, navigation, and features

Module 2: Setting Up Data Sources

• Connecting to databases: SQL and NoSQL data sources
  • Supported databases (PostgreSQL, MySQL, Oracle, etc.)
  • Using SQLAlchemy for database connections
• Setting up data connections and creating datasets in Superset
• Data source management: importing, editing, and maintaining datasets
• Writing custom SQL queries to extract data
• Understanding database schema and structure within Superset

Module 3: Exploring Data with SQL Lab

• Using SQL Lab for querying data
  • Writing complex SQL queries and using filters
  • Sorting and aggregating data
• Exploring datasets: understanding tables, columns, and metadata
• Saving and sharing SQL queries and results
• Using the Explore feature to visualize data directly

Module 4: Data Visualization Basics

• Introduction to visualizations in Superset
• Available chart types and their use cases
  • Bar charts, line charts, pie charts, area charts, and more
• Creating basic visualizations: step-by-step guide
• Customizing charts: adding labels, legends, colors, and more
• Setting visualization parameters like timeframes, metrics, and filters

Module 5: Advanced Visualization Techniques

• Advanced chart types and their use cases:
  • Heatmaps, Sankey diagrams, Geospatial maps, and Pivot tables
• Adding drilldowns and interactivity to charts
• Configuring custom metrics, dimensions, and filters
• Leveraging Superset’s charting libraries for custom visualizations
• Using annotations and overlays on charts
• Best practices for designing effective and intuitive visualizations

Module 6: Creating Dashboards

• Understanding dashboards and their role in BI
• Creating dashboards and adding visualizations
• Organizing dashboards with filters, widgets, and layouts
• Adding interactivity: global filters and interactive charts
• Designing for performance: optimizing dashboard load times
• Saving, sharing, and exporting dashboards

Module 7: Managing Users and Permissions

• Setting up user roles and access control
• Creating and managing roles for different users
• Configuring permissions for datasets, dashboards, and visualizations
• Setting up authentication methods (LDAP, OAuth, etc.)
• Understanding Superset’s security features and best practices

Module 8: Advanced Data Handling and Customization

• Customizing visualizations using Python, JavaScript, or other tools
• Creating calculated columns and metrics
• Using virtual datasets and managing large datasets
• Integrating Superset with other BI tools or data sources
• Customizing Superset’s UI and adding custom components
• Extending Superset with plugins and extensions

Module 9: Reporting and Alerts

• Setting up and scheduling reports in Superset
• Configuring alert notifications based on defined thresholds
• Automating report delivery to stakeholders
• Customizing alert formats (email, Slack, etc.)

Module 10: Performance Optimization and Troubleshooting

• Performance tuning for large datasets and complex queries
• Indexing strategies and optimizing queries
• Analyzing and troubleshooting Superset logs
• Scaling Superset for high availability and large user bases
• Backup and recovery strategies for Superset data and configurations

Module 11: Deploying Apache Superset

• Deployment options: On-premises, cloud-based, or hybrid setups
• Installing and configuring Superset in production environments
• Configuring Superset with Docker or Kubernetes
• Best practices for securing Superset in production
• Managing Superset updates and migrations
• Monitoring and maintaining Superset in production