Fundamentos y Arquitectura de Datos

📰 Medium · Data Science

Learn the fundamentals and architecture of data management, including data ingestion, storage, and processing, to improve data-driven decision making

intermediate Published 12 Apr 2026

Action Steps

Design a data ingestion zone using ELT to handle structured, semi-structured, and unstructured data from various sources
Implement APIs to prioritize real-time data from call centers and CRM systems
Use connectors like JDBC or ODBC to extract data from ERP and CRM systems, and APIs REST for modern systems
Store raw data in a Data Lakehouse without modification for trazability and integrity
Process and analyze data using data processing tools and techniques

Who Needs to Know This

Data engineers, data scientists, and data analysts can benefit from understanding the proposed data architecture to design and implement efficient data pipelines

Key Insight

💡 A well-designed data architecture is crucial for efficient data ingestion, storage, and processing, enabling better decision making