The history of Data Science goes as far back as 1962 when John W. Tukey discussed in The Future of Data Analysis about how data analysis is intrinsically an empirical science. Tukey was indicating a merger of Statistics and Computer Science. Since then, the evolution of the term we now refer to as Data Science had begun.
In the years that follow, Scientist Peter Naur laid the foundation of Data Science in his seminal work titled Concise Survey of Computer Methods in which he attempted to substitute Computer Science with Data Science. The term kept bandying until the beginning of this century when it actually started to take on its true meaning.
Primarily, Data Science involves the use of statistical methods to extract patterns in data. However, what distinguishes a data scientist from a statistician is the recent phenomenon of BigData. The association of Data Science with BigData is not just limited to the large volumes of data, but included shifting to new systems and methodologies for processing data and the ways data get studied and analyzed.
An effective data scientist, when compared to a statistician, has sound knowledge of software architecture and understands multiple programming languages. The fact of the matter is that today we are storing lots of data in rather cheaper and more reliable ways than ever before and this is where the need of a statistician arises so as to code equally proficiently.
The evolution of the field has made it an umbrella term which incorporates the concepts and practices such as programming, statistical modelling, story-telling and visualization. A data scientist is direly required when the company’s data volume and velocity exceeds a certain level of the control of traditional data analysts.
Only the data scientists have the capability to bring out the meaning from the silos of unstructured data. They gain deeper insights into these silos using the methods and practices of data science and its relevant sub-fields.
In the past decade, Data Science, as a discipline, has unrolled its domain to include businesses and organizations globally. Today, governments, insurers, astronomers, engineers, and biotechnologists, etc. are strongly dependent on the use of Data Science’s research findings with a growing number of other industries which are gradually realizing the significance of using it.
Touching everyday life
Surprisingly, a Data Scientist has recently created and published a song on his YouTube channel using predictive analytics on a meagre sample of 600 songs from a particular genre and this is just one example of how Data Science can be used in places where it has never been imagined to exist before.
There is rigorous research going on in the field of Data Science which has expanded to the domains of biological sciences, health care, the humanities, social sciences and medical informatics. The stock business operating world-wide is heavily influenced by Data Science, exact predictions are made using the technology when both experience and intuition fails.
Data Science is very powerful, but its real power is yet to be realized. The boom of Internet of Things (IOT), which is yet to come, when combined with Data Science will change the dynamics of traditional business intelligence. Business Intelligence (BI) platforms will make use of the data captured from sensor-driven devices by using new solutions to capture the real-time data.
As a result, the analytics provided by these BI specialists will be of unmatched quality. Afinity, a call center interaction solution has shown an enormous growth in the past few years. The solution currently optimizes the pairing of customers with employees on the basis of their past behavior. The Data Science used in Afiniti’s system sits at the convergence of computer science, neuroscience, mathematics, psychology, linguistics and philosophy.
However, the secret sauce of the success of Afinity is the continually evolving retrieval of data from a large amount of calls and other various undisclosed sources which the artificial intelligence algorithms later scan and use in making further predictions.
Since the Data Scientist is referred to as the sexiest job of 21st century in the Harvard Business Review of 2012, the profession has become a buzz word. Almost 5 years have passed but the hype has still not changed; in fact, Glassdoor, a leading job board website had rated Data Scientists as No.1 on Glassdoor’s Best 25 Jobs List.
Pakistan has recently been acquainted with Data Science, the industries in the country are in the phase of awareness of the importance of Data Science. They have not fully understood the role of the Data Scientists and how Data Science can benefit the overall business metrics.
However, the start-ups seem to be more informed about Data Science. The reason behind this trend is probably the emphasis students get during their studies in universities.
On the contrary, Data Science is inevitably the next big thing which is yet to mature. The future of Data Science, without doubt, seems unprecedented!