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Extracting New Added-Value Information From a Sea of Data
From 1989 until now, my research has focused on data mining, where we analyze huge volumes of textual
and numerical data for useful information. Since 2010, as a part of Fujitsu’s push to make the “Human Centric
Intelligent Society” a reality, my research has sought to develop a cross-functional way to collect, compile and
analyze data on individual lifestyles, corporate activities and social conditions using social media, sensors and
other tools. The object is to bring a range of viewpoints to complex social problems for solutions that would be
impossible for individuals and companies working alone to achieve. Take, for example, the problem of food
product loss, which can happen with overproduction or when consumers purchase more than they need. By
closely analyzing consumer buying behavior, we can show the locations and times when food is most in
demand, making it possible to reduce waste.
Even if the target for analysis is a massive pool of data, it’s not uncommon to only end up with the same
results that you initially anticipated. Going beyond that hurdle to find new added-value information is a chal-
lenging task, and one that can put a lot of pressure on me at times. But having customers agree with our
approach and ultimately remark on the impressive power of Fujitsu technology is what really motivates me to
move forward.
Isamu Watanabe
Director
Social Solution Laboratory
Software Systems Laboratories
Fujitsu Laboratories Ltd.
MANAGEMENT
005FUJITSU LIMITED ANNUAL REPORT 2011