The Data Scientist In The Room
This summer I spent a lot of time interviewing the self-proclaimed big data leaders at a wide range of midmarket and enterprise companies. These are the people charged with defining their organizations’ big data strategies and new initiatives. First, let me say these are not dummies. No one gets put in the driver’s seat for these projects without knowing a lot about technology and business both.
What was a little surprising was the spectrum of views on big data. Many saw it as a chance to upgrade and modernize their server, network, and storage infrastructure. Some were focused on integration of new internal and external data sources to traditional analytics activities. A few were putting a new label of “big data machine” on their biggest, shiniest rack in the data center. More than a couple wanted to wholescale adopt new data platforms such as Hadoop and NoSQL databases. One sheepishly suggested he’d do whatever his data warehouse vendor recommended, figuring they must be the experts. Most were on a headhunt for the perfect unicorn, err, data scientist.
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