The term “Big Data” will fade away, the title “Data Scientist” will lose value, but the importance of “Data Science” will continue to grow..

This post contains my predictions for “Big Data”, “Data Scientist” and “Data Science”. Rather than start each sentence with “in my opinion” or “my best guess is”, I will state everything that follows as if it were fact. Please argue with me if you disagree with any of it.

“Big Data” has been a buzzword recently and is actually a useful term right now to use when talking about advances made in technologies and methods for handling and utilizing large data sets. Many business and others are leveraging statistical analysis of large data sets for the first time. As data analytics advocates across the world test their influence while navigating budget committees and corner offices, they benefit from the memory-locking powers of talking points and buzzwords. Since I am a fan of the growth of data analytics I support any tool that helps spread its prevalence, including buzzwords. Over time, however, as “Big Data Science” approaches the asymptote of ubiquity, the term “Big Data” will be less useful as a buzzword. Another problem for the term “Big Data” is that the size that a data set must be to qualify as “Big Data” is temporally bound, always growing as a function of time. Data storage hardware is analogous in this respect. We generally do not refer to a piece of data storage hardware as “big”. Instead, we specify its size when expressing its bigness. For these reasons the use of the term “Big Data” will decline.

The title “Data Scientist” is destining to befall a similar fate as the title “<fill-in-the-blank> Architect”. With no universally accepted definition the continuum between an Analyst and a Data Scientist will blur.  The term will succumb to market pressures from job seekers who will prefer a title that is perceived to have status and improve career prospects. There are already positions posted for entry level “Jr. Data Scientists”.

“Data Science” itself is not going anywhere. As more and more data is available, understanding that data is increasingly necessary for organizations to succeed. Statisticians and data architects will be in increasing demand. People that can bridge those skills will be more valuable still.