What Is Data Science Anyway?

Data Science, Big Data, Predictive Analytics, Advanced Analytics…what exactly does it all mean?  What if anything does it have to do with the Academy Awards? The Awards are given for art, not science, but the awarding of the statuettes is a process undertaken by a panel of around 5,000 humans that can be understood, and dare we say forecast, using data science.

All of those fancy terms refer to the application of rigorous statistical methods, mathematical analysis, and “machine learning” to better analyze information.  And ultimately, the goal is to use that analysis for better decision-making.
Technology – computing power, data transmission, the internet, the ubiquity of computers, social networking, communications and mobile devices – all of these incredible innovations have exponentially increased our ability and opportunity to collect, store and process data.  Thus evolved, and continues to evolve, modern “data science” – the discipline of analyzing and applying data for real world business solutions.

But, as the amount of data increases, it becomes increasingly challenging to sort through it.   Some data helps us to be smarter, but some data just confuses the picture.  We call the helpful information “Signals” and the confusing or not-so-helpful information “Noise.”  There arises a paradox – with more information, we have the ability to be smarter; but we must have the capacity to sift and sort and analyze that information, which is more difficult with the abundance of data.  Data science provides the tools that empower analysis of complex information.

Data Science seeks to isolate and extract the signals, sometimes called features, from the messy noise; it is the business of helping organizations predict and adapt their strategies in accordance with data.  This discipline empowers organizations to maximize revenue, minimize costs and optimize efficiencies – in countless ways.  The various permutations of uses for data are endless – from predicting how a product will sell to identifying the right location for a new store.  It is a tool for forecasting. It assists with resource allocation. Fundamentally, data science helps us make better decisions, reaching the right consumers with the right message at the right time.

One of the most recent examples of data science comes from the world of politics.  In 2012, we watched as both the Republicans and Democrats sliced and diced data on voters.  The campaigns used predictive analytics to understand their likely supporters; they were able to tailor messages specifically to them, distributing the messages to those voters in the right place and the right time, in order to optimize their likelihood of success.  But, political pundits from CNN to Slate to The Atlantic point out that the Obama campaign maintained a superior data science operation; and, this competitive advantage was crucial in helping the President secure re-election.

In addition, the New York Times published a blog  - FiveThirtyEight – that utilized a sophisticated data science model, correctly predicting the Presidential winner well in advance – defying political pundits who claimed the race was too close to call.

Why did the New York Times’ blog suggest that Obama was highly favored to win when so many others said the race was a toss-up?  Because applying data in forecasting is a science, and like other sciences, the tools are exceptionally useful when they are accompanied by smart scientists, who understand the methods, the strengths, and the limitations of the science.  Human capital is critical for us to best utilize and apply information and data.   Data science, as a discipline, works best when the data scientists have an intuitive understanding of the industry, the organization and its strategic considerations. Without this context, it is hard for data science to unlock meaning from data and empower us to make smarter and more informed decisions.

Data science is not magic.  It doesn’t give us all the answers, but it does inform our decision-making and provides critical tools for making smart decisions.

The brain trust behind this blog, Farsite, has been at the forefront of using data science to help businesses understand what their data mean to them, and how to use data-driven insights to help their business.  And, starting tomorrow, we’ll begin exploring the real world potential data science offers the industry, through the lens of forecasting the Oscars.