What is meant by a data science boom?
Data science is considered by most of the professionals as a modern field that has been discovered by the tech-savvy generation. But that’s not the case at all. Data science has been around for decades now, but the implementation was only for small-scale problems. Data science could not be used on larger systems back then due to the lack of availability of adequate processing power.
With the advancement in technology in recent years, we now have the processing power to implement data science analytic methods on large data for industrial purposes. But that’s not the reason for the phenomenon which we are calling ‘data science boom’. The real reason behind the increase in the popularity of data science course in recent years is our large-scale migration towards the digital world.
With each passing day, an increasing number of companies are moving towards full automation of their services for faster and better consumer satisfaction. This means that most of their transactions are being done digitally which generates a considerable amount of data on a daily basis. This generation of large amounts of data on a daily basis has emphasized the need for data science for analyzing the patterns of the data and obtain important decision-making results.
We are living in a digital age today. Our presence is on numerous internet platforms which not only includes social media platforms like Facebook, Instagram or Snapchat, but also other entertainment platforms like Netflix, Amazon, YouTube and many more. The data stored for every account on these platforms are never stagnant and keep on increasing every moment. This large amount of data is commonly referred to as ‘big data’.
With the increase in the size of data, the storage options are also advancing. As time is progressing, the size of data storage devices is getting smaller and the storage capacity is increasing. We have even moved beyond any kind of physical storage device with the invention of cloud storage services. The amount of data used by people is increasing every day, which leads to more and more people opting for cloud storage services for safely storing their data.
Now that we have overcome the challenge of storing this large data, we can use different analytic methods to process relevant information from the huge set of data at our disposal. So, this sudden need for people who can handle and process such big data led to a boom in the market for data scientists and it resulted in a boom in the field of data science, although there is a common debate going on whether this boom in data science is actually a fad or a fact.
What is the reality?
Most of the senior professionals in any business field are not ready to acknowledge the credibility of data science as a permanent factor. A major portion of them has the opinion that this boom in the field of data science is due to the overindulgence of people in digital transactions and is just a temporary trend in the market. However, the attitude of the market expansion of many businesses is indicating the truth to be otherwise.
In today’s time, numerous companies are fighting to gain the largest market share in every field of business. As the competition gets harder, the room for errors also gets smaller, making the firms more cautious with every step and business strategy. Although it is true that wisdom and intuition is very much necessary for any business to succeed, what if we could avoid repeating past mistakes and predict future outcomes by applying mathematical and statistical methods to the data already at our disposal? This is precisely the service that data science provides to us.
As mentioned earlier, the number of people using online services is increasing day by day because the amount of consumer data at the disposal of large companies is huge. So, now it has become a competition of which company makes the best utilization of its consumer data. Google and Amazon are some of the major companies which are leading the foray because they are employing efficient data scientists to gain insights into the consumer data which helps them in making their future business strategies.
On the other hand, enterprises like Bing are lagging far behind in the competition due to its lack of implementation of data science methods for analyzing consumer patterns. This gives us a pretty clear picture of the market scenario and how data science is impacting it. It has clearly become a question of efficient utilization of the data at your disposal to gain an edge in the competition.
So, why is data science being underestimated?
Data science may be very valuable and beneficial for any business or for your career, but it is very hard to attain which makes it less lucrative in the eyes of many individuals. It is not something one can gain mastery of by just finishing a course and getting a degree. It needs discipline and creative insights to fully understand. Also, as the name itself suggests, for being a data scientist you need to have a Ph.D. in a corresponding subject, most preferably math or statistics.
Due to this factor, many people see data scientists mainly as a research fad and nothing important to be implemented for commercial purposes. Data science is very hard to master and often people have to wait for a long time even for a single answer. This has led to the field being less appreciated by individuals.
Being a data scientist is not easy at all and constructing helpful results from data analysis is one of the hardest jobs in the programming world. Someone does not become a data scientist just by getting a degree. They have to gain some work experience to develop the creative ability to handle and process the data in order to obtain useful information, which is very hard to attain.
What is the market scenario? Why is data science still being considered a fad instead of fact?
Most of the large scale companies have woken up and taken notice of the advantages of the implementation of data analytics course for devising its business strategies. This has led to an exponential rise in the demand for data scientists at various major enterprises and firms. According to various market research outlets, data science is being listed as a high demand skill as perceived from the employment records of various companies.
Most of the companies are paying a hefty amount for appointing a data scientist. Some economists are of the opinion that data science has become a major game-changer in the industrial field and will continue to be so, with more and more companies fighting to appoint the best data scientist in order to stay ahead of its competitors. Despite of all this encouragement from the employers, why is data science still not getting the appreciation it deserves?
The answer to the above question is the disparity in the demand and supply of data scientists. According to some media outlets, the demand for data scientists has increased nearly 29% in the past year and the total increase since 2013 has been that of nearly 344% which, needless to say, is a phenomenal amount.
However, the number of qualified and skilled data scientists is far below the necessary amount. As mentioned earlier, being a data scientist requires much time and dedication, which slows down the production of efficient data scientists.
Right now AI and machine learning are the hottest trends in the market and most of the companies are looking upon data science as an efficient way to embrace it. Most of the companies are striving to personalize the consumer experience in order to create a loyal and bigger consumer base, which can be only be done by data scientists.
The hurdle for data scientists is different than that of normal coders. A company or enterprise requires a coder to be skilled in any kind of programming language among which Python and R are the most favorite. However, in the case of a data scientist, they are required to be skilled in not only a programming language, but also in using and implementing various analytics tools like AWS, Spark, Hadoop, Hive, etc. and should also have experience in using machine learning and statistical modeling.
So, to conclusively answer, the reason for the existing disparity between the nature of the field and market relevance is that the requirements asked by the companies are very hard to be fulfilled by the existing data scientists. Most of the companies are looking for data scientists with efficient knowledge about mathematics and statistical modeling and also with a sense of formulating business strategies. This approach is a little flawed as it is nearly impossible for a single individual to imbibe all these skills in him or herself. This is the main reason for data science being considered a fad when in reality it is a fact, and needless to say, it is here to stay for the foreseeable future.
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Senior Data Scientist and Alumnus of IIM- C (Indian Institute of Management – Kolkatta) with over 25 years professional experience ,Specialised in Data Science, Artificial Intelligence, and Machine Learning.
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