Monday, April 29, 2013
08:30 AM - 11:45 AM
Not all analytical projects are implemented using relational database technology especially when it comes to very large data volumes including unstructured content and clickstream. This session looks at BIG data analytics using Hadoop, Map/Reduce and NoSQL DBMSs and how these new Big Data platforms can be integrated into existing analytical environments. It also looks at how data governance can be extended to incorporate and manage Big Data environments.
- Types of BIG Data
- Popular BIG data use cases
- The BIG data challenge – Data and Analytical complexity
- Hadoop and HDFS versus Relational DBMS
- What is Map/Reduce and how can it be used in analytics?
- Approaches to using Hadoop and Map Reduce for analytics
- NoSQL Graph DBMSs
- Analytical databases and Map/Reduce – how do they integrate?
- Using external table functions
- Cloudera, MapR, IBM BIGInsights, Hortonworks, EMC GreenPlum, Oracle, Teradata Aster, SAP HANA and Sybase
- Using Map/Reduce to process BIG data to supply insight into a data warehouse
- Data management in a Big Data Environment
Mike Ferguson is the Managing Director of Intelligent Business Strategies. An independent IT analyst and consultant, he specialises in BI/Analytics, big data and data management. He has over 35 years of experience with 27 years in BI/Analytics, 36 years in Data Management, 13 years in Smart Business and six years in Big Data Analytics on Hadoop and NoSQL.
Mike works at board, senior IT and detailed technical IT levels on a strategy for BI/Analytics, technology selection, enterprise architecture, data strategy, MDM and Big Data. He has spoken at events all over the world and written numerous articles.
Formerly a principal and co-founder of Codd and Date Europe Limited, the inventors of the Relational Model, he was also Chief Architect at Teradata on the Teradata DBMS and European Managing Director of Database Associates. He teaches popular master classes in Big Data Fundamentals, Big Data, New Technologies for DW and BI, Operational BI, Data Governance, Master Data Management and Big Data Management.