Organización chilena — ETL Integration of Multinational Customs Data

The challenge

The organization managed customs information from seven Latin American countries—Colombia, Chile, Peru, Ecuador, Mexico, Argentina, and Uruguay—in heterogeneous, scattered formats. This fragmentation prevented timely consolidation, comparative analytics, and traceability of operations at a regional scale. The lack of a common integration layer caused delays in decision-making, misinterpretation of figures, and a heavy reliance on manual processes to normalize data coming from each national customs authority.

The solution

We designed and implemented a proprietary ETL platform that ingests, integrates, and normalizes customs information from the seven countries into a single structured data model. The platform standardizes catalogs, unifies tariff codes, and delivers clean data ready for advanced analytics at an international scale. As a result, teams access comparative dashboards and custom queries without manual intervention, with traceable, auditable information that supports operational and strategic decisions in a timely manner.

Why does a common integration layer change the way decisions are made?

When customs information arrives in heterogeneous formats from each national authority, every consolidation depends on manual processes that take time and increase the risk of error. A common integration layer replaces that handcrafted work with an orderly flow that ingests, integrates, and normalizes data systematically.

By unifying catalogs and tariff codes, the figures from the seven countries can be compared without prior adjustments. This lets decisions rest on a single reference, avoiding divergent interpretations between teams and making it easier to trace each operation at a regional scale.

The result is a clean, auditable database that serves both day-to-day operations and strategic planning. With that foundation, the organization can respond in a timely way to the questions that arise in its foreign trade.

Technologies used

• Python
• SQL
• Sharepoint
• Next JS
• Nest JS

Results

• 7 Countries integrated — Consolidated customs information
• 100% Normalized data — Ready for international analytics
• +80% Time reduction — In consolidation and normalization