The following is an excerpt from the book, "Data Juice: 101 Real-World Stories of How Organizations Are Squeezing Value From Available Data Assets."

StubHub, an eBay company and one of the world's largest ticket marketplaces, enables users to buy and sell different types of tickets to various sports and entertainment events worldwide. Managing global customers and monitoring millions of transactions coming from over 25 different data sources is a significant challenge for the platform. The company needed to process and analyze volumes of big data efficiently to address daily churns, fraudulent activities, customer-related concerns, and more. To help address these issues, StubHub tapped into big data to acquire valuable insights about their customers' ticket buying patterns and behaviors.

To achieve this, StubHub implemented a single data warehouse to store and process information on millions of customers from multiple data sources. The system delivered insights about churn prediction, fraud notification and alerts, and product recommendations. It also enabled faster, smarter, and more efficient data analysis of customer transactions and online shopping behaviors. StubHub had quick access to customer-related data, including ticket purchase history, patterns, demographics, and exploring this data to build, deploy, and multiple data-mining models, create predictions, and improve responsiveness. Furthermore, it enabled calculation of 180 million customers' lifetime value compared to just 20,000 values at a time previously possible, and fraud issues were reduced by up to 90%.

By leveraging the power of big data and analytics, StubHub continues to grow and expand in the online sports, concert, theater, and other live-entertainment events ticket marketplace, serving millions of customers worldwide. According to Dr. James Short, Director of the Center for Large Scale Data Systems Research (CLDS) at the San Diego Supercomputer Center, University of California San Diego, StubHub's evolution from a data warehouse to the operating platform for the world's largest ticket market shows what can be accomplished in building out a modern, real-time data analytics platform: market leadership, business return on investment, customer knowledge, and predictive modeling about where to go next.

For organizations like StubHub that need to manage vast amounts of data, starting with scale is essential. A data systems infrastructure that can scale as the business pressure-tests it is crucial. Going forward, StubHub's business systems will need to support the full range of analytics use cases, from self-service visualization and exploration to guided analytics apps and dashboards, custom and embedded analytics, mobile analytics, and reporting for its business ecosystem partners and their customers. By starting with scale and sustaining investment and strategy intent, StubHub can grow its platform across other live-entertainment ticket marketplaces, leveraging its real-time capabilities.