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Development and test organizations face major challenges when building robust automated tests around their mobile applications. With limited testing resources and increasingly more complex projects, stakeholders worry about the risk and quality of mobile products. So how do you plan a mobile test automation project to prioritize testing resources and efforts? Tarun Bhatia used big data analytics to understand where customers spend most of their time on their apps out in the wild. See how you can analyze massive amounts of mobile usage data to create an operational model of carriers, devices, networks, countries, and OS versions. Based on real-user data, they developed automation strategies to create better tests and focus on the right priorities. Learn how you can use big data analytics to apply mobile automation in areas of continuous integration, performance, benchmarking, compatibility, stress, and performance testing.