Developed Operational Plan for FCEN Intelligence

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Developed Operational Plan for FCEN Intelligence

  • Day: 2026-02-01
  • Time: 21:25 to 22:05
  • Project: Business
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: FCEN, Data Management, Translation, Data Normalization, Python

Description

Session Goal

The primary goal of this session was to develop a comprehensive operational plan for transforming the FCEN intelligence dataset into a valuable asset through exploratory data analysis, CRM dataset hardening, and generating actionable circles lists.

Key Activities

  • Operational Planning: Outlined a structured operational plan focusing on EDA, CRM dataset hardening, and actionable circles.
  • Data Product Specification: Detailed the data product contract for FCEN intelligence, including data structure, tables, rules, and quality checks.
  • Database Design: Proposed a modular database design for survey data, with normalization recommendations for Google Sheets, SQLite, and DuckDB.
  • Translation Tasks: Translated promotional messages and interface instructions for software applications, enhancing accessibility for different language users.
  • Data Normalization: Developed a process for mapping original dataset columns to standardized slugs, including a Jupyter notebook skeleton for analysis.
  • Data Analysis and Segmentation: Conducted a detailed analysis of data segmentation and program design, identifying errors and opportunities for improvement.
  • Data Cleaning and Classification: Implemented tokenization and classification of educational degree data, and sanitized degree and subject data using Python and pattern matching.

Achievements

  • Completed the operational plan and data product specification for FCEN intelligence.
  • Proposed a database design framework for survey data.
  • Completed translation of software messages and interface instructions.
  • Established a process for data normalization and cleaning.

Pending Tasks

  • Further testing and validation of the data normalization process.
  • Implementation of the proposed database design in a live environment.
  • Ongoing monitoring and refinement of the operational plan.

Labels

FCEN, Data Management, Translation, Data Normalization, Python

Evidence

  • source_file=2026-02-01.sessions.jsonl, line_number=2, event_count=0, session_id=a19c3c0860d83cd169bc9566ea2dd8c0ca3a498094f5b14c351e46c931db72af
  • event_ids: []

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