Why Sudden Boom in Data Science? Amazing Future of Data Science

Why Sudden Boom in Data Science? Amazing Future of Data Science

Harvard calls Data Science as the sexiest job of 21st century. Every era has its own technology and there will be some booming technologies of that era, now that is Data Science. There is nothing like data science which people have invented in these recent years. Field of data science was with us for years and the implementation was by a little scale only but the recent boom was amazing. Data science is considered by professionals as modern field or future technology. The hype in the number of job opportunities, job satisfaction, salary and the fun of statistics is the reason behind the boom in 2020.  Every company in the technology like Healthcare, manufacturing and finance wants to strengthen their business and data, that increased the boom of data science. With the advanced technologies, the processing power of data has changed and powered to implement data science analytic methods on large data for industrial purposes has increased. The real reason behind the increase in the popularity of data science in recent years is our large-scale migration towards the digital world.

The first Industrial revolution was started around 1760s, which actually triggered the major inventions like steam engine, everything started from there. First industrial revolution witnessed all major inventions which actually powered the world. In 1960s it was the start of third industrial revolution also referred as Digital revolution. Digital revolution was actually the beginning of new era; everything seems to be changing from there. Most precious invention in this revolution was transistors, which then gave birth to all these tiny super processors or computers. Now it is believed that we are stepping foot towards forth revolution and that will be Artificial intelligence (AI).  Backbone of Data science is data, according to the researches size of data generating every single day is around 2.5 quintillion bytes and as forecasted by scientist the size of the data will reach around 163 Zettabytes by 2025 and 90% of data present in the world at present were generated in the past 2–5 years. Out of these data present today only 4-5% of data is refined or cleaned, this is the situation where the need of data science comes. People are moving from physical storage to cloud and also in this digital world, people are processing their data on cloud machines which is much faster and cheaper and much mobile and thus the need of clean data comes and the solution is with data science. The exponential increase in the amount of data has boosted the boom of data science.

What is Data Science?

The field is growing so rapidly, and revolutionizing, it's difficult to fence in its capabilities with a formal definition, In simple words data science can be defined as the extraction of actionable insights from raw data or it is the meaningful answers to the queries on the raw data. Data science uses scientific methods, statistics, and algorithms to extract insights from both structured and unstructured data. Structured data is only around 15% and most of the data is unstructured data as of now. 


Data science helps us achieve some major goals that either were not possible or required a great deal more time and energy just a few years ago.  Data scientist must be having knowledge with multiple items. Below diagram shows some of the disciplines a data scientist should have. Data scientist should have some knowledge on data, statistics, domain and programming languages like R, Python and also should some knowledge on any visualization tools.


What is Data Science

Data Scientist not only does the exploratory analysis to discover insights from it, but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future.  Earlier data science was providing explanatory analysis to the quarries on data but now Data Science is primarily used to make decisions and predictions analysis, now it is focusing to predict the outcome. Data scientists must be skilled in everything from data engineering, math, statistics, advanced computing and visualizations. Data scientist relies heavy on Artificial intelligence and its inner topics like Deep learning or Machine learning.

Where Data Science can be used?

Data science is the key solutions to many major problems, even in this covid-19 pandemic situation you all have analysed the important of data science and how it is beneficiary. Data science can be used in almost all industries, today many of the human tasks are automated using machine learning and AI. Data Science is used to classify emails and easily detection of spam mails, which saves human time and effort. Forecasting of stock exchange is an excellent application of data science and the persons dealing with stock exchange knows the important of charts and predictions. Pattern detection and facial recognition is one of the boom techs in data science. Automation, fraud detection and recommendations are other applications. Natural language processing (NLP) is also an application of data science when humans can be replaced and human effort can be reduced, a person who always gives same answers to same queries may get bored but due to machine learning algorithm these human effort can be reduced.

Where Data Science can be used

Healthcare is one of the major industries where data science is widely used, as per the researchers the major implementation of data science is happening in healthcare industries as of now. Data science has led to a number of breakthroughs in the healthcare industry find new ways to diagnose diseases, fitness tracking, bed availability, detection of errors and implemented many new methods of treatment. Entertainment is another major field of data science, ever wonder how streaming platforms like Netflix or prime comes with your favourite shows or movies or how YouTube recommends you with the content you like to watch all these possible with data science only. Era of Self Driving Cars has began companies like Tesla, Ford are ahead of the race with the implementation of the techniques in data science like machine learning, AI.  Machine learning and data science have saved the Financial Industry millions of dollars, and unquantifiable amounts of time. Thanks to data science, what would take around 360,000 manual hours to complete is now finished in a few hours. These are just a few examples of data science there are thousand more to discuss. Everything in the Smartphone you use to the aeroplane you travel everything have some data science in it.

Future of Data Science

The world today is data-driven, and the future of data science is growing. According to studies average person on earth is expected to generate 1.7 megabytes of data per second by the end of 2020. Industries are more concerned about their data and data privacy which creates the future for data science. Onset of the digital era, data is continuing to grow at an exponential rate, with very little sign of slowing down which adds fuel to data science creating a breeding ground for improved data science models. Fuelled by big data and AI, demand for data science skills is growing exponentially, according to job sites.

AI and ML has witnessed an exponential demand, machine learning and deep learning is considered as the true future of data science. The demand of skilled jobs will be increasing by the years, since only 25% of the industries is using data science wisely which also improved their productivity and the predictive models helped them to predict their faults. Other 75% is looking forward about their data which will again increase the demand of data science. By 2024, a shortage of 250,000 data scientists is predicted in the United States alone. In 2020 organizations are in a hunt to hire candidates with data science and big data analytics skills. This shows that this highly paid hottest job will be having a great future. According to researchers there will be a exponential increase in demand for data scientists by end of 2020. According to IBM, an increment by 364,000 to 2,720,000 openings will be generated in the year 2020. This demand will only grow further to an astonishing 700,000 openings. India alone, there was a 417% increase in the requirement of proficient data scientists.

Case study with linked in data shows that United States is having larger number of profiles with data science, followed by San Francisco Bay area and India at 3rd position.

Data science has critical applications across most industries. Starting a career in data science is a smart move, not just because it is sexy and pays well, but because data very well may be the key point on which the entire world turns. Now its era for graphs or plots to do the talking.

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