Data Sleuths: Vignettes
By Sabine Louët
September 30, 2011
Peter Lancett, Technology Consultant, IBM
Peter Lancett (CREDIT: Kathleen Tyler/IBM)
Peter Lancett entered business intelligence (BI) with a 1-year work placement in sales operations at IBM in London when he was an undergraduate in information management and business studies at Loughborough University. This helped him land a job, after graduating in 2010, as a technology consultant in IBM's business analysis and optimization department.
Lancett's job is to analyze company operations data for business clients, understanding what data are available and how best to integrate and exploit them. Lancett preempts problems that may arise from poor terminology, data matching, or data quality. He also acts as a bridge between IBM's technical and client-facing operations by relaying information. Overall, his job involves reviewing the clients' objectives and confirming what BI work needs to be done. The satisfaction of the job, he says, is in "giving customers information that they had not known about."
Joseph Misiti, Chief Technology Officer and Co-Founder of Social Q
Joseph Misiti (CREDIT: Joseph Misiti)
Joseph Misiti obtained a degree in electrical engineering from the University of Pittsburgh in Pennsylvania. He became acquainted with big-data algorithms when he took an engineering job at Lockheed Martin devising missile-tracking systems. Realizing he needed a stronger grounding in mathematics, Misiti pursued an M.Sc. degree in applied mathematics at the University of Maryland, College Park. He gained experience in other big-data algorithms after leaving the defense industry to work for a consultancy whose clients focused on facial recognition and natural-language processing.
But Misiti, a user of social media, was soon struck by people's growing online presence. He saw an opportunity to apply big-data algorithms to social media data sets to feed market research surveys with data about potential customers including their location, gender, and age. He launched Social Q in March 2011. "To really be involved in big data you need a multiple skill set, including an understanding of optimization theory and of algorithms similar to those used in facial recognition to find [relevant] patterns by knowing which data to extract."
Sabine Louët is a freelance writer based in Dublin. | |
10.1126/science.caredit.a1100108 |
