Course Outline
Introduction to the Stratio Platform
- An overview of Stratio’s architecture and its core functional modules
- The role of Rocket and Intelligence modules within the broader data lifecycle
- Procedures for accessing and navigating the Stratio user interface
Utilizing the Rocket Module
- Establishing data ingestion and creating effective pipelines
- Linking data sources and setting up necessary transformations
- Employing PySpark to execute preprocessing tasks within Rocket
PySpark Fundamentals for Stratio Users
- Understanding PySpark data structures and fundamental operations
- Mastering looping constructs, including for, while, and if/else statements
- Defining custom functions using def and applying them in practical scenarios
Advanced Application of Rocket with PySpark
- Managing streaming ingestion and dynamic transformations
- Integrating loops and functions in both batch processing and real-time contexts
- Applying best practices to optimize performance in PySpark pipelines
Exploring the Intelligence Module
- A review of data modeling capabilities and analytical features
- Techniques for feature selection, transformation, and data exploration
- The contribution of PySpark to custom analytics and insight generation
Constructing Sophisticated Analytics Workflows
- Developing user-defined functions (UDFs) within the Intelligence module
- Implementing conditionals and loops to manage complex data logic
- Practical use cases covering segmentation, aggregation, and prediction models
Deployment and Team Collaboration
- Processes for saving, exporting, and reusing established workflows
- Strategies for collaborating with team members within the Stratio environment
- Evaluating outputs and integrating results with downstream tools
Conclusion and Future Pathways
Requirements
- Proficiency in Python programming
- Solid comprehension of data analytics or big data processing principles
- Foundational understanding of Apache Spark and distributed computing architectures
Target Audience
- Data engineers focused on Stratio-based platforms
- Analysts and developers utilizing the Rocket and Intelligence modules
- Technical teams adopting PySpark workflows within the Stratio ecosystem
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
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.
