How to Find the "Golden Nugget" in Big Data?

Agenda:
6:00 pm – 6:30 pm: Registration & Networking
6:30 pm – 7:00 pm: First Use Case
7:00 pm - 7:30 pm: Twitter Use Case: Real Time Analytics
7:30 pm - 8:00 pm: Q&A

Speakers:

Sri Ambati
Sri is the co-founder and CEO of 0xdata (@hexadata), 0xdata is building H2O, the math & prediction engine for Hadoop. The promise of Big Data is better predictions, Sri will walk you through the life cycle of data science - starting first with a question & the process of exploring messy data, modeling it with simple math, scoring it on test data or a live event. Then to infer actionable insights and form informed opinions about your users and business. In the context of big data, algorithms have to predict better in the face of missing information and unbalanced datasets. Finding outliers in this context needs a more scalable and faster machinery that goes past sampling. He will take the real-world use case of predicting conversion of leads in a marketing database so businesses can focus on the ones with higher scores for convertibility, as well as to learn and identify traits from past data that lead to better predictions and better business outcomes.

DeWayne Filppi
DeWayne is a Software architect/developer/consultant at Gigaspaces with over 25 years of industry experience developing high performance distributed systems for several industry verticals. He helps customers design and prototype systems that exploit the benefits of in-memory processing, big data platforms, and cloud computing. DeWayne will discuss how to build a Twitter-like analytics system in a simple way using frameworks such as Spring Social, Active In-Memory Data Grid for Big Data event processing, and NoSQL databases such as Cassandra or Hbase for handling the managing the historical data, and provide real world examples.