Case Study: Prologis Achieves Better Data Discovery and Self-Service Analytics with data.world

A global warehousing leader, Prologis leans on data.world’s knowledge graph to catalog people, processes, and decisions

Prologis, the global logistics real estate company, needed a better way to modernize its historical data warehouse and make data easier to discover and use across the business. As it moved to the cloud, the team wanted well-organized, clearly explained, self-service data that could better reflect its core domains such as customers, buildings, units, leases, and financial metrics. Prologis turned to data.world and its knowledge graph–based data catalog and collaboration platform.

Using data.world, Prologis created a centralized platform to connect data elements with business processes and decision-making, making it easier for teams to explore data, understand its meaning, and support both traditional analytics and emerging AI/ML use cases. The result was a more consolidated and understandable environment for descriptive, predictive, and prescriptive analytics, along with a strong implementation partnership that helped Prologis align its data strategy with long-term business objectives.

Prologis

Luke Slotwinski

VP Data and Analytics