As the world’s largest retailer, Walmart relies on data to power the best shopping experience across the Web, mobile, and stores at scale. Every week, more than 240 million people visit a Walmart store or website around the world. Jaya Kolhatkar explains how Walmart is using that transactional data to make shopping more seamless and personalized.
But to make data work for the customer, Walmart first had to make data work for its business. Jaya shares how Walmart created a structure around its large volume of shopping data that includes the company’s multipetabyte storage, self-maintained Hadoop ecosystem components (Hive, Spark, and Mesos), and a constant flow of experimental technologies including file systems, Hadoop distributions, NoSQL data systems, virtualization, and packaging technologies. Jaya also discusses the culture Walmart created that enables data scientists and engineers to use data to quickly build and launch new shopping experiences to customers.
Jaya Kolhatkar is vice president of engineering with @WalmartLabs, the Silicon Valley-based tech arm of Walmart’s ecommerce division, where she is responsible for defining and testing a predictive intelligence platform that allows data scientists to build and deploy predictive algorithms that can influence customer experience in real time and reduce fraud. Jaya joined Walmart when they acquired Inkiru, the company that she cofounded and served at as the chief analytics officer, which focused on leveraging data to create business value, particularly through the use of predictive analytics. Prior to Inkiru, Jaya spent four years at eBay Inc., at both eBay and PayPal, developing infrastructure to facilitate real-time linking of customers across eBay properties to enhance customer experience. Jaya holds a master’s of business administration from Villanova University.
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