Walmart has a complex system architecture distributed across multiple geographies, organizational boundaries, and technologies. Accessing multichannel information about buying patterns and consumer needs was prohibitively time consuming. Walmart recognized an opportunity to be more responsive to their customers with a more personalized shopping experience by taking advantage of the data that was just beyond their fingertips.
Walmart brought in the experts at Cognitect to design and implement an architecture that would scale to support over 5,000 stores in the U.S., would scale with the growth of the company, could support transaction volumes on a “Black Friday Scale,” and would integrate in-store, online and mobile data.
Design to Deployment in 6 Months
Cognitect’s developers worked side by side with WalmartLabs to develop an adaptive data infrastructure that works with and aggregates data from Walmart’s existing systems. A small team of just 4 developers built the robust data management system—from design to deployment—in just six months.
Rapid Delivery of New Customer Apps
The new architecture enables Walmart to easily add new applications spanning multiple backend systems and data stores as customer’s shopping needs evolve. For example, Savings Catcher, Walmart’s consumer application for price matching, uses the data platform to power automatic rebates to consumers.
Real-time customer data from over 5,000 stores, integrated with online and mobile transactions creates a wealth of marketing opportunities.
Using Clojure as the programming language and Cassandra as the backend data store, Cognitect and WalmartLabs created a robust data management system that enables faster decision making and improved responsiveness to its customers: