Скачать или смотреть The intersection of business rules management and big data

As available data grows, the challenge of harnessing information for business decisions becomes more critical in all industries. Big data provides a wealth of information that businesses often struggle to parse and utilize. Red Hat JBoss BRMS provides a lightweight and powerful way to create and manage business rules to infer and make sense of critical business data. Integrating JBoss BRMS into an existing big data stack provides an enterprise the ability to use data-driven rules to make instantaneous, market-relevant decisions. Especially interesting to enterprises in the financial services industry is using the intersection of data and rules to classify money laundering. In this session, Anurag Saran, David Murphy, and Sal Elrahal will detail the architecture used to update real-time requests with analytics derived from a big data provider. Attend this session to learn how to integrate JBoss BRMS with the Hadoop big data platform to automatically update rules that drive anti-money-laundering decisions. Both Pig and Hive are used in conjunction with the underlying MapReduce interface in Hadoop to transform historical data that BRMS can apply in real time to incoming transactions for money laundering classification. In the session, Red Hat customer NTTData will show how a Japanese fashion retail company (START TODAY CO., LTD / ZOZOTOWN) used JBoss BRMS and JBoss Data Grid to create a real-time offer system.