“Data Scientists” have been the unsung heroes behind corporations since the 60’s, but suddenly, they hold the title of “America’s Hottest Job.” The data scientist is not a new job, in fact, the early data scientist evolved from a statistician. Michael Dickenson, Ironbridge Software CEO, speaks about his tenure in this field, as well as why it holds such a high value that is sought after today.
The Early Days
In the ‘80s, Michael Dickenson was working for a company that was a leader in business intelligence (BI). It was the experience he gained in this position that led him to create his own company and build a product combining computer technology – a brand new concept! – with Michael’s BI know-how. It was this very product that was purchased by A.C. Nielsen Company, which was one of two corporations that collected large sets of data and published it to the consumer goods industry. Michael’s product increased data collection from thousands of data points monthly to hundreds of millions, thus creating what is now known today as “Big Data.”
The Modern Age of Big Data
Today’s data scientist has the capability to analyze unbelievably large sets of data, nimbly navigating the information to pull out solutions that will increase business efficiency. This is especially prevalent in consumer packaged goods (CPG), one of the most efficient industries in the world. The ability to take incomprehensible data and turn it into game-changing business solutions is obviously valuable.
The Qualities of a Data Scientist
What began as a BI specialty has too often become miscommunication between this entity and the world of information technology (IT). While both are essential to the success of a business, they often clash when it comes to working together due to their vastly different nature. Fortunately, data scientists are able to provide a bridge in communications between the two fields, making sense of the data that is collected from IT and turning it into solutions for BI. Syncing up BI and IT is largely beneficial to any company and analyzing data and finding solutions is an essential aspect of being a data scientist.
The data scientist is an amalgamation of many different skills and disciplines: speaking across business entities; identifying client and business pain points; and learning how to collect, analyze and understand large sets of data. The position may have evolved over the years, but, at it’s core, a data scientist must keep up with the latest technologies and industries involved.
