Visualizing data in Java environments is critical for making better business decisions, but presents a host of challenges that require careful consideration. Security, networking, clustering, non-standard data stores, and Big Data sources are common problem areas in Java visualization. Specifically with Big Data, how do you make any sense of this huge treasure trove of unstructured and semi-structured information? With several (i.e., hierarchical or flat) methods to connect to Big Data sources, how do you choose the right way? Join us to discover the best practices and gotchas when visualizing data with Java. Learn how you can easily embed visualization and analytical functionality into your applications, all while avoiding the pitfalls.
Leo Zhao has been leading sales engineering at Jinfonet as a Senior Systems Engineer for over 10 years. From guiding prospects through the JReport product suite, to creating proof-of-concepts, to onsite trainings, Leo's extensive product expertise ensure that customers' needs are met. Prior to working at Jinfonet, he has been involved with the systems integration and business intelligence industry for almost a decade. Leo holds a degree in Computer Science from the Beijing Institute of Technology.