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 Duration 35 hours

Course Outline

  • Introduction
  • Installation of Apache Superset
  • Overview of Apache Superset Capabilities and Structural Design
  • Establishing Connections to Custom Data Repositories
  • Examination and Visualization of Information
  • Development of Custom Dashboards and Generation of Reports
  • Integration of Apache Superset with SQL Database Systems
  • Deployment and Configuration of Cloud-Native Apache Superset
    • Utilizing Docker to initialize the development environment
    • Leveraging Python setup tools and pip
  • Examination of Core Features and Structural Design of Apache Superset
    • Comprehensive visual representations
    • User-friendly interface navigation
    • Compatibility with a wide range of database systems
  • Data Integration into Apache Superset
    • Configuration of data ingestion parameters
    • Optimization of the data intake workflow
  • Execution of Advanced Data Analytics
    • Calculation of rolling averages for time-series data
    • Implementation of temporal comparative analysis
    • Data resampling via diverse methodologies
    • Scheduled query execution within SQL Lab
  • Execution of Advanced Visualization Techniques
    • Pivot table construction
    • Investigation of various visualization modalities
    • Development of visualization plugins
  • Creation and Distribution of Dynamic Dashboards
    • Annotation addition to visual charts
    • Utilization of REST APIs
  • Integration of Apache Superset with Database Systems
    • Apache Druid
    • BigQuery
    • SQL Server
  • Security Administration in Apache Superset
    • Comprehension of predefined roles and creation of custom roles
    • Adjustment of access permissions
  • Troubleshooting Procedures

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