Enhanced Business Intelligence using EROCS

  • Authors:
  • M. Bhide;V. Chakravarthy;A. Gupta;H. Gupta;M. Mohania;K. Puniyani;P. Roy;S. Roy;V. Sengar

  • Affiliations:
  • IBM India Research Lab., New Delhi, India - 110070. abmanish@in.ibm.com, mkmukesh@in.ibm.com;IBM India Research Lab., New Delhi, India - 110070. vechakra@in.ibm.com, abmanish@in.ibm.com, mkmukesh@in.ibm.com;IBM India Research Lab., New Delhi, India - 110070. ajaygupta@in.ibm.com, abmanish@in.ibm.com, mkmukesh@in.ibm.com;IBM India Research Lab., New Delhi, India - 110070. higupta8@in.ibm.com, abmanish@in.ibm.com, mkmukesh@in.ibm.com;IBM India Research Lab., New Delhi, India - 110070. mkmukesh@in.ibm.com, abmanish@in.ibm.com;Language Technologies Institute, CMU, PA, USA - 15213. kpuniyan@cs.cmu.edu;Aster Data Systems, CA, USA - 94065. prasan.roy@asterdata.com;IBM India Research Lab., New Delhi, India - 110070. souraroy@in.ibm.com, abmanish@in.ibm.com, mkmukesh@in.ibm.com;Microsoft Research, Bangalore, India - 560080. vibhutis@microsoft.com

  • Venue:
  • ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
  • Year:
  • 2008

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Abstract

The EROCS technology automatically links unstructured data with relevant structured data from an external relational database. We demonstrate how EROCS can be used for enhancing Business Intelligence by allowing OLAP tools to analyze structured and unstructured data in a consolidated manner. Our demonstration showcases the use of EROCS in exploiting latent information in customer emails, which helps in building a complete view of the customer. This results in new insights about the business which are not possible with the existing state of the art.