Course Outline


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


Summary and Conclusion


  • Experience with business intelligence and data visualization
  • Familiar with Apache Superset fundamentals


  • Data analysts
  • Data scientists
  • Data engineers
 14 Hours

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