Machine VS the Intern

This doesn’t mean that our tasks are necessarily easy to execute, but rather that they are more efficiently facilitated by gadgetry.  Being a young person in San Francisco, I exploit technology to exert as little effort towards any duty I need to manage on any given day.  I am infantile in that I cannot wake myself every morning but rely on an alarm.  I’ve lived here for a month but I need to use a GPS for my 1 mile commute.  Recently, I broke my foot and now plan to purchase an electric wheelchair so I’ll never have to walk anywhere ever again.  

Data Science, now, is an important element for any business that doesn’t want to get left behind.  The process of obtaining data, interpreting it, and then magically creating useful recommendations revolutionises decisionmaking.  Those who understand this process on a fundamental level affectionately refer to themselves as “Data Scientists”. They are the ones who actually understand the algorithms and statistical thinking behind data mining.  They are a curious folk who will dive into raw data to draw their own conclusions.  While this profession sounds like it would be fitting for a stodgy number cruncher, the savvy and conversant scientists normally receive the most praise.  One type of data scientist is relatable and addresses mass audiences of corporate bigwigs.  They are teachers who can explain something as complicated as data science to whomever they choose.  Other Scientists are archetypical nerds.  They are fluent in algorithms and python but experience difficulty saying hello to their co-workers.  Either way, when experienced enough, they can track the performance of their company and the progressions of their industry on a daily basis.  Knowledge of minutia like this puts a data scientist at the table to help make decisions with executives.  Human intuition drives this knowledge.  People make themselves aware of their own market like no black box software ever could.

So, how can this human element work well with software?  Speed is essential in business.  When one thinks economically, time is the most valuable asset a company has.  Opportunities change rapidly.  The sooner decision makers know what they need to do the better.  We believe that when a data scientist works with business intelligence (BI) software, that that is what enables businesses to make the best decisions as soon as possible.  Analytics companies like DecisionNext transform raw data into complex models that are so stupidly simple to use that even I, an intern, can understand them.  Simplicity = Speed.  Data Scientists and executives both know that the fortunes of their businesses can change in the blink of an eye. We do the grunt work, data mining and model presentation, to quickly make recommendations to business leaders.  The quicker they can strategize, the more they maximize their opportunity.

Jack Alden