By: Sarah Tarraf, Director, Analytics
The stereotypical image of a data scientist is that of the harried analyst, hacking away late into the night in an unrestrained startup environment, tapping into massive amounts of data to uncover interesting relationships that explain once-unexplainable phenomena. What we tend to ignore is the more common scenario—a data scientist working in an established corporate environment with a limited technology budget and an incomplete infrastructure.
By Troy Burmeister & Claire Gilbert, Data Analysts
From software development to social networking, open source software powers big companies. Surprisingly, the people behind it don’t necessarily sit within the walls of Facebook, Google or Microsoft. They reside in thriving communities of active online users’ intent on fueling advances in data science, big data, and analytics.
by Nick Wright & Sarah Tarraf, O2 Integrated Analysts
It was Aristotle who said: “A friend to all is a friend to none.” If that is the case, then Big Data has few friends, if any, with its attempt to befriend us all.
Big Data is the Holy Grail of analysis to statisticians; it is the promise of smarter, faster decisions to the business executive; and it is a good source of job security with the seemingly never ending need for extracting, transforming, and loading more data to the IT professional,.
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