Samsonite LATAM unifies regional Data and builds an analytics and AI foundation with Snowflake

Samsonite is one of the world’s most recognized luggage companies, with regional operations spanning multiple brands, physical stores, digital channels, and markets.

To strengthen its data capabilities across Latin America, Samsonite partnered with Exomindset, a Snowflake Select Partner, to design and implement a unified regional data platform on Snowflake.

The project at a glance

7

markets

8

brands

350+

physical stores and 20 online stores

8

data ecosystems integrated

15+

automated pipelines

8

dbt projects

~4 months

from design to implementation

The Challenge

Samsonite LATAM operated with data scattered across multiple systems and tools, limiting visibility, trust, and agility.

Disconnected data

Information lived in different systems and tools, making consolidation complex and time-consuming.

Low trust and visibility

Inconsistent data definitions and limited governance affected the accuracy and reliability of reporting.

Siloed operations

Each area worked with its own reports, making collaboration and decision-making across the region difficult.

The Solution

A regional platform built on Snowflake. Exomindset designed a platform that centralizes Samsonite LATAM’s commercial, operational, and digital data in Snowflake, integrating the region’s e-commerce, web analytics, order management, point of sale, product catalog, and customer service systems.

The architecture organizes data into distinct layers and maintains end-to-end traceability. Data enters in its original format, is then standardized, and is finally published as curated datasets with consistent definitions for consumption.

Source systems

Shopify

Google Analytics 4

Oracle OMS

LINX & LINX OMS

Retail Pro Prism

JasperX PIM

Gorgias

→

Ingestion & Orchestration

Apache Airflow (AWS MWAA)

⇅

dbt Transformations

→

Data Platform

Snowflake

Raw data
(Landing)

→

Curated data
(Trusted)

→

Semantic
layer

Data protection by design: masked in development, dynamic role-based policies in production.

→

Consumption

Marketing activation
(initial use case)

Analytics & BI
(Dashboards, self-service)

AI & Advanced Analytics

Unified data foundation

End-to-end governance

Scalable & secure

AI-ready architecture

Data ready for marketing activation

Commercial data is published segmented by market and brand, and feeds the marketing platform through change data capture mechanisms, so campaigns use information updated daily from the source transactional systems.

Data protection by design

Personal data protection was addressed through a differentiated approach:

In development: personal information is irreversibly masked during ingestion, preserving its usefulness for testing.
In production: Snowflake’s dynamic policies determine what information each user can view based on their role.

An inventory of sensitive columns makes it possible to identify and control the information that requires protection.

The Impact

A single source of information

Commercial, operational, and digital data from seven markets and eight brands, organized under consistent definitions.

Automated updates

Scheduled, staggered pipelines with alerts for potential failures.

Auditable protection

Personal information protected by design through environment- and role-based controls.

More actionable marketing

Campaigns powered by transactional data updated daily.

A foundation built to grow

A curated layer that enables new advanced analytics and AI use cases without rebuilding the platform.

Technologies

Snowflake

dbt

Apache Airflow

AWS MWAA

Python

BigQuery

Oracle

SQL Server

MySQL