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Course Outline
Introduction to the Stratio Platform
- Overview of Stratio’s architecture and core modules.
- The role of Rocket and Intelligence in the data lifecycle.
- Logging in and navigating the Stratio user interface.
Working with the Rocket Module
- Data ingestion and pipeline creation.
- Connecting data sources and configuring transformations.
- Using PySpark for preprocessing tasks within Rocket.
PySpark Essentials for Stratio Users
- PySpark data structures and operations.
- Looping constructs: application of for, while, and if/else logic.
- Writing custom functions using 'def' and applying them in workflows.
Advanced Usage of Rocket with PySpark
- Streaming ingestion and transformation techniques.
- Implementing loops and functions in both batch and real-time scenarios.
- Best practices for optimizing performance in PySpark pipelines.
Exploring the Intelligence Module
- Overview of data modeling and analysis features.
- Feature selection, transformation, and exploration.
- The role of PySpark in generating custom analytics and insights.
Building Advanced Analytics Workflows
- Creating user-defined functions (UDFs) within Intelligence.
- Applying conditionals and loops for complex data logic.
- Practical use cases: segmentation, aggregation, and prediction.
Deployment and Collaboration
- Saving, exporting, and reusing workflows.
- Collaborating with team members via the Stratio platform.
- Reviewing outputs and integrating with downstream tools.
Summary and Next Steps
Requirements
- Proficiency in Python programming.
- Fundamental understanding of data analytics or big data processing concepts.
- Basic familiarity with Apache Spark and distributed computing principles.
Target Audience
- Data engineers working with Stratio-based platforms.
- Analysts or developers utilizing Rocket and Intelligence modules.
- Technical teams transitioning to PySpark-based workflows within the Stratio environment.
14 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
