Developed YAML Structures for Data Management

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Developed YAML Structures for Data Management

  • Day: 2025-10-02
  • Time: 18:35 to 20:25
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: YAML, Data Management, Schema, Validation, EPH, HOGAR

Description

Session Goal

The session aimed to explore and develop YAML structures for various data management tasks, focusing on schema evolution, data mapping, and validation techniques.

Key Activities

  • Reviewed the evolution of the INDIVIDUAL schema from 2010 to 2025, focusing on core elements and standardization strategies.
  • Created a reference manual for changes in HOGAR and INDIVIDUAL data structures, including validations and normalization techniques.
  • Explored the use of YAML for defining data structures in databases, emphasizing schema definitions and data validation.
  • Developed a YAML metamodel for structuring EPH data, incorporating logical models and era-specific manifests.
  • Provided a structured YAML configuration for EPH data mapping, detailing canonical columns and validation rules.
  • Drafted a guide for YAML data ingestion and normalization, covering error handling and era detection.
  • Structured YAML files for EPH and HOGAR systems, focusing on variable mapping and data configuration.
  • Outlined YAML structures for household characteristics, survey design, and income metrics, providing templates for data management.
  • Created a compact YAML structure for business data to enhance data management efficiency.
  • Designed a declarative alignment profile in YAML for data processing with pandas, promoting reproducibility and clarity.

Achievements

  • Successfully developed comprehensive YAML structures for various data management needs, enhancing standardization and validation processes.
  • Provided detailed guides and templates for implementing YAML configurations across different data domains.

Pending Tasks

  • Further testing and validation of the YAML structures in real-world scenarios to ensure robustness and adaptability.
  • Integration of YAML configurations into existing data management systems for seamless operation.

Evidence

  • source_file=2025-10-02.sessions.jsonl, line_number=0, event_count=0, session_id=a1578a843403566db47d6f5ad6e212da5aab5af7e44153b41f50ab93c5d31de1
  • event_ids: []

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