Tag Archives: data mining
A lot of media reports have been surfacing lately about “secretive” data mining activities taking place within the presidential campaign. Many articles paint the efforts with a sinister caste, implying that underhanded invasions of privacy are taking place.
But to any seasoned data professional, data mining is a discovery tool that pulls nuggets of insight out of mountains of data. For any business that wants to get ahead in today’s hyper-competitive global economy, advanced data mining and analysis is not a luxury, it is a necessity. As USA Today’s Jack Gillum describes the Romney campaign’s data analytics: (more…)
I grabbed my wife’s Harvard Business Review (HBR Jan-Feb 2012) edition before a recent plane ride to a customer meeting. After diving through a bunch of case study-type narratives I ended up in a section titled “Stop Collecting Customer Data” (page 57), which was part of HBR’s “Audacious Ideas” series. This series was aimed at showcasing some proclaimed thought leaders’ very forward-thinking and, in my opinion, also some rather ill guided ideas full off naïveté. (more…)
Enterprises use Hadoop in data-science applications that improve operational efficiency, grow revenues or reduce risk. Many of these data-intensive applications use Hadoop for log analysis, data mining, machine learning or image processing.
Commercial, open source or internally developed data-science applications have to tackle a lot of semi-structured, unstructured or raw data. They benefit from Hadoop’s combination of storage and processing in each data node spread across a cluster of cost-effective commodity hardware. Hadoop’s lack of fixed-schema works particularly well for answering ad-hoc queries and exploratory “what if” scenarios.