Processed Galicia and Mercado Pago transactions

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Processed Galicia and Mercado Pago transactions

  • Day: 2025-07-05
  • Time: 20:05 to 20:50
  • Project: Accounting
  • Workspace: WP 2: Operational
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Transactions, Data Processing, Python, ETL, Financial Reporting

Description

Session Goal

The session aimed to map and process transactions from Galicia and Mercado Pago into a universal format for financial reporting and analysis.

Key Activities

  • Mapping and Processing: Mapped Galicia transactions into a raw_transactions table, detailing transaction types, column mappings, and parser scripts.
  • Library Imports: Imported essential Python libraries for data manipulation and file handling, including pandas, os, json, math, textwrap, and random.
  • Data Loading: Loaded CSV data into Pandas DataFrames and performed initial data exploration using head() and transaction type counting.
  • Data Grouping and Analysis: Grouped data by transaction type and payment method, calculated sums of real amounts, and analyzed positive and negative values in financial data.
  • ETL Guide: Developed an ETL guide for Mercado Pago transactions, including mapping to a universal schema and outlining sanity checks.
  • 7-Stage Pipeline: Outlined a comprehensive 7-stage pipeline for financial data ingestion, from parsing to output generation.
  • Schema Planning: Planned a canonical column set for storing atomic transaction data, focusing on essential columns for reporting.

Achievements

  • Successfully mapped and processed Galicia and Mercado Pago transactions into a structured format.
  • Established a robust ETL process for financial data ingestion and reporting.

Pending Tasks

  • Finalize the implementation of the 7-stage pipeline for full automation of financial data processing.
  • Conduct further testing on the ETL process to ensure data integrity and accuracy.

Evidence

  • source_file=2025-07-05.sessions.jsonl, line_number=1, event_count=0, session_id=4a686f0bb52ab81dd3cb745f69d0a7078ca7aa58696319bb0e40612d7d4b9f91
  • event_ids: []

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