Augmenting z Analytics by leveraging the Hadoop Ecosystem

Content: Complementing z Analytics by using Big Data analytics and Natural Language Processing (NLP), integration of BigInsights with z Systems, customer use case scenarios, keeping DB2 for z/OS as control point for enriched z Analytics

 

Abstract: This presentation will illustrate how to complement existing 'traditional' DB2 for z/OS based analytical capabilities with Big Data analytics, e.g. by using text analytics and Natural Language Processing (NLP) as part of IBM InfoSphere BigInsights. This leverages key Hadoop components (MapReduce programming model, HDFS, HBase, Zookeeper, etc.) to analyze data from Enterprise-owned systems of engagement (e.g. call center transcripts, e-mail traffic, Facebook), and data from external social media sites (e.g. Twitter tweeds, Facebook sites, Blogs) and putting this in context with transaction insight from data on IBM z Systems. We will provide examples on how Hadoop systems - by using HBase and Hive with corresponding connectors to existing z Systems – and Big SQL on HDFS and Hive will enrich analytical insight.