At StampedeCon 2014, Jean-Luc Chatelain (DDN) presented 'Big Data: Infrastructure Implications for “The Enterprise of Things”.'
The amount of data in our world has been exploding, and storing and analyzing large data sets—so-called big data—will become a key basis of competition for the new “Enterprise of Things”, underpinning fresh waves of productivity growth, innovation, and consumer surplus. Leaders in every sector – from government to healthcare to finance – will have to grapple with the implications of big data, as data growth continues unabated for the foreseeable future. The quest to make sense of all this big data begins with breaking down data silos within organizations using the cost appropriate, shared infrastructure to ensure optimal extraction and analysis of data, knowledge and insight.
As the leading global e-commerce service, PayPal has transformed the way the company leverages big data storage and hyper-scale analytics to help improve both the safety and purchasing experiences of its online customers. In this discussion, using real-world customer examples such as PayPal, we will explore what Big Data Storage is from high performance file sharing to long-term archiving, as well as ways to break down data silos to reduce the cost and storage complexity of managing demanding workflows and data environments. We will demonstrate how hyperscale storage can enable near-real-time, stream analytics processing for behavioral and situational modeling, as well as for fraud detection, marketing and systems intelligence. We will ask what the greatest barriers to effective business analytics are and how today’s data analytics platforms, including Hadoop, Vertica, Python and Java, can be optimized to enable machine learning, event streaming, forecasting, and reduce overhead associated with human intervention. You’ll come away from this session understanding the infrastructure implications and options for organizations looking to maximize their big data for competitive advantage.