Build a Product Knowledge Graph for a Fast-Fashion Retailer
Overview
What this challenge is about.
You receive 200 sample SKUs across 4 markets (Spain, Germany, Japan, Brazil) as CSVs with country-specific attribute names. Design an OWL ontology with shared classes for Product, Garment, Material, Color, and SizeSystem, plus mapping properties from market-local terms to the shared vocabulary. Model the 200 SKUs in RDF (Turtle), load into a triple store (GraphDB or Apache Jena Fuseki), and write 8 SPARQL queries that demonstrate cross-market harmonization (e.g., 'list all cotton T-shirts in red across all markets'). Deliver: ontology file, RDF data, query notebook, and a 4-page specification.
The Brief
What you'll do, and what you'll demonstrate.
Unify product attributes across 4 country catalogs into a single queryable knowledge graph with harmonized vocabulary.
Earning criteria — what you'll demonstrate
- Design an OWL ontology for a real product domain
- Model heterogeneous catalog data in RDF
- Author SPARQL queries that demonstrate harmonization
- Communicate KG design choices in a written specification
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career paths this builds toward
Canonical rolesData Engineer
Building a product KG with harmonized vocabularies is core data-engineering work at any large retailer or marketplace.
This challenge sharpens
- knowledge-graphs
- rdf
- data-harmonization
AI Solutions Architect
Specifying the KG layer that AI features (search, recs, RAG) consume is the AI solutions architect's daily output.
This challenge sharpens
- schema-design
- knowledge-graphs
- data-harmonization
AI Engineer
Loading RDF and writing SPARQL queries to power downstream AI features is the AI-engineer skillset at any KG-driven product.
This challenge sharpens
- rdf
- sparql
- knowledge-graphs