In fact, analytics seems to be one of the fastest changing areas of data warehouse technologies. One key to understanding analytics is that there are at least three types, which IBM refers to as deep analytics, time series data analytics and operational analytics. Deep analytics includes one-time analyses that try to provide insight into enterprise decision making. An example of time series data analytics is gaining insight from collected smart utility meter data. An example of operational analytics is real-time fraud detection.
Traditional data warehouse solutions are not necessarily enough. In fact, IBM feels that traditional architectures have become too complex and were not designed for big data, which consist of enormous data sets and may include structures different from traditional relational databases around which traditional data warehouses are built.
To address this situation, IBM talked at IOD about smart consolidation that leads to a "logical data warehouse." This includes a "data bridge" that IBM defines as pre-integration and optimized software for data movement and migration among analytics solutions, including IBM's Analytics System, InfoSphere Warehouse and Netezza, as well as Oracle Database.
This latter instance is interesting. On the one hand, IBM is in the midst of a competitive war where it wants to displace Oracle Database with DB2, but that the companies also collaborate shows IBM’s practical side. The fact is that Oracle’s database solutions are not going away anytime soon (even if DB2 makes inroads), so if smart consolidation using IBM’s data bridge is to succeed, then that reality has to be accepted. Naturally, IBM had loads of specific announcements on analytics, but space does not permit getting deeply into the details.
InfoSphere
InfoSphere is the third area IBM focused on at IOD. In contrast with enterprise content management and data management and data warehousing solutions, InfoSphere is an IBM-specific brand the company refers to as "the trusted platform for trusted information." It is leveraged for integrating various data warehousing, application consolidation/retirement, governance and big data processes.
