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Innovative Data Anomaly Detection and Transformation for Analysis Applications

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-15-C-0118
Agency Tracking Number: N132-096-0726
Amount: $749,998.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N132-096
Solicitation Number: 2013.2
Timeline
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-03-11
Award End Date (Contract End Date): 2017-01-02
Small Business Information
75 Aero Camino, Suite A
Goleta, CA 93117-3134
United States
DUNS: 153927827
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Joel Luna
 Principal Investigator
 (937) 429-3302
 jluna@fti-net.com
Business Contact
 Rhonda Adawi
Title: Technical Point of Contact
Phone: (805) 685-6672
Email: radawi@fti-net.com
Research Institution
N/A
Abstract

The overall objective of this topic is to develop a software toolset to transform extracted data from different database systems and convert it into data packages that create model specific input files that support future modeling, simulation, and analysis tasks. Specifically, the main objective of the Phase II research project is to develop, demonstrate and validate an operational prototype of the Phase I design. The Phase II research will address the problem described in the research topic by developing an innovative data transformation toolset that can be used to create model inputs for selected Navy models. The innovation in FTIs approach is the development and use of building blocks to implement any generic data transformation process that can provide the same or better results than current data transformation processes that are more manually intensive and require much greater time and analyst manhours. FTI will develop a data transformation toolset prototype for use by the customer, including software components, data representations, and user interface to develop data transformation processes. FTI will develop data transformation processes based on existing customer processes in case studies using the prototype software, provide a demonstration of the data transformation capability, and validate the results.

* Information listed above is at the time of submission. *

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