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Course Outline

Introduction to the Stratio Platform

  • Comprehensive overview of Stratio’s architecture and core modules
  • The strategic role of Rocket and Intelligence in the data lifecycle
  • Accessing the platform and navigating the Stratio interface

Leveraging the Rocket Module

  • Data ingestion strategies and pipeline construction
  • Establishing data source connections and configuring transformations
  • Executing preprocessing tasks in Rocket using PySpark

PySpark Fundamentals for Stratio Users

  • Core PySpark data structures and operational techniques
  • Implementing looping constructs: for, while, and if/else statements
  • Defining and applying custom functions using def

Advanced Rocket and PySpark Integration

  • Managing streaming ingestion and real-time transformations
  • Utilizing loops and functions in both batch and real-time scenarios
  • Best practices for optimizing performance in PySpark pipelines

Utilizing the Intelligence Module

  • Overview of data modeling and analytical capabilities
  • Feature selection, transformation, and exploratory analysis
  • The role of PySpark in driving custom analytics and generating insights

Developing Advanced Analytics Workflows

  • Constructing user-defined functions (UDFs) within Intelligence
  • Applying conditionals and loops to structure complex data logic
  • Practical use cases including segmentation, aggregation, and prediction

Deployment and Team Collaboration

  • Saving, exporting, and reusing established workflows
  • Collaborating with team members within the Stratio environment
  • Reviewing outputs and integrating results with downstream tools

Course Summary and Recommended Next Steps

Requirements

  • Proficiency in Python programming
  • Familiarity with data analytics or big data processing concepts
  • Foundational knowledge of Apache Spark and distributed computing principles

Target Audience

  • Data engineers developing on Stratio-based platforms
  • Analysts or developers leveraging the Rocket and Intelligence modules
  • Technical teams shifting their workflows to PySpark within the Stratio ecosystem
 14 Hours

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