By Claire Gilbert, Data Analyst, O2 Integrated

It’s fair to say that for those who run in business intelligence circles, many admire the work of Fast Forward Labs CEO and Founder Hilary Mason.  Perhaps what resonates most with her fans is the moniker she places on data scientists as being ‘awesome nerds’—those who embody the perfect skillsets of math and stats, coding, and communication.

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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.

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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.

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by Jason Solack, Vice President, O2 Integrated

Organizations large and small have an abundance of data at their disposal and have access to even more. The differences, however, in large part are often due to corporate governance. In fact, an increasingly growing component of this is data governance. And, when it comes to permission and utilization of data, this is certainly a case where size matters—organizational size and capacity, that is.

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by Jason Solack, Senior Director, O2 Integrated

Ask­­ the question: “Can machines think for us?” And the answer, of course, is yes.  Ask it another way: “Can machines do what humans can do?” And, the answer becomes filled with caveats and conjecture.

As a recognized scientific discipline since 1959, machine learning explores the construction and study of algorithms that can learn from data.

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