Timely Analytics for Business Intelligence (TABI)
Overview
Timely Analytics for Business Intelligence (TABI) is a system that delivers near real-time business intelligence for customers relying on massive amounts of data. Such customers are prevalent in fields such as telecommunications, banking, and transportation. The project integrates two research assets from IBM Research – Haifa: the Massive Collection System (MCS) from the Software and Services department; and the Parallel Machine Learning (PML) toolbox developed jointly by ML group and the Data Analytics department at the IBM T.J. Watson Research lab.
TABI connects to the data stream of the customer, extracting only relevant information and making rapid business intelligence decisions using methods such as prediction, clustering, social connectivity graph analysis, and association rules.
TABI has demonstrated that it can learn from hundreds of millions of records per day, with relatively modest hardware requirements.
Contact: Amir Ronen (amirro@il.ibm.com)