Big Data, a term to describe the exponential growth and availability of data, has become increasingly more important to businesses due to large-scale and location-aware social media and mobile applications. These applications generate massive amounts of data, much of it in real-time. This drives the need for scalable, real-time platforms, which can process humongous data volumes and can derive real time analytics. Unfortunately, Big Data may contain bad data which causes organizations to make poor decisions. Even worse for testers is the fact that Big Data testing is challenging due to a[WU3] embraces complex technology stack, numerous data sources, real time events and streams, complex transformations, and more. Karen Pruitt and Sushmitha Geddam describe the critical testing of focal areas with[WU4] in Big Data batching and real-time data processing. They describe frameworks that support Big Data testing and help frameworks that support Big Data testing which helps to strengthen data quality. Join this session to learn how to handle big data integration challenges and the skill sets you’ll need to be successful. Take away valuable insights for testing your Big Data implementations.te
Sushmitha Geddam
Cognizant Technology Solutions
Sushmitha Geddam is a Big Data test architect with the Data Testing Centre of Excellence of Cognizant’s Quality Engineering & Assurance practice. In her eleven years of IT industry experience, Sushmitha has delivered multifaceted enterprise business software projects in the investment banking, telecom, healthcare, and insurance domains. At Cognizant, she is responsible for developing internal talent and for providing the TCoE with delivery oversight, thought leadership, and best practices.
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