Everyone everywhere is talking about Data Science these days. When we say “everyone,” we mean every business, every institution, every economy in almost every geography.
Data Science is a wave that has caught the world by a rave storm and is taking the technological revolution to newer heights. So, where will this revolution go by 2025?
Some fear that Data Science may result in Data Scientists becoming redundant. While others say that it may fizz out.
But experts who are aware of the momentum that this field of science has caught say that – Data Science is here to stay for the better and for a very long time to come.
A Quick History
In 1962, American mathematician John Wilder Tuket used the term “Data Analysis” for the first time to describe what we know as modern data science.
However, only after two decades in the 1980s the Chinese statisticians in the Chinese Academy of Sciences in Beijing used “Data Science” for the first time to mean “statistics.”
C.F. Jeff Wu, the same Chinese statistician in the year 1997, emphasized the need to replace “statistics” with the word “Data Science.”
While Statistics was sometimes considered to be limited to reading data and accounting, “Data Science,” according to him, was a much wider, dynamic, and interdisciplinary field.
This field of Data Science involves – Statistics, mathematics, computer science, information science. In Data Science, one not only collected data but designed it and analyzed it.
Growth of Data
It is unknown to anyone that the data available to man in current times is growing exponentially and can be measured in zettabytes.
One zettabyte is equal to the twenty-first power of ten bytes or one sextillion bytes, which means one zettabyte is equal to a trillion gigabytes.
We understand the enormity of the data that is available to us. Every day, humans are producing 2.5 quintillion bytes of data (a quintillion has 18 zeroes behind it) through emails, tweets, posts, videos on the internet traffic.
While “how do we store this data” is one aspect of the reality of this “data deluge,” “how should we effectively utilize this data” is another aspect of it.
To deal with the second aspect, Data Science came into the picture to analyze these extremely large data sets of Big Data.
Data Science – Where it stands today?
One of the most puzzling things for mankind is the “uncertainty” of the future. If they can find a tool that will lend them a peek into the future, it will be magical. Data Science does just that.
This is why every individual would love to invest in reading the future by studying the “trends” of the present.
Data science uses Big Data (a voluminous variety of dynamic data that can be structured or unstructured). It feeds the data into the algorithms and models to spell out patterns and possibilities in the future.
This is where Data Science becomes multidisciplinary and blends into Machine Learning and Artificial Intelligence.
Two primary contributors to this Data Explosion are – a growing number of devices under IoT (Internet of things) and Social Media.
As of 2018, there were 7 billion global devices connected through the Internet of things, which produced enormous amounts of data.
This number is expected to be 21 billion this year. The social media records show that in 2012, 72 hours of video were being uploaded to YouTube every minute. That number went up to 65 years of video per day in 2020.
Data Science today is being used by all businesses that want to utilize this data to build models that will help them grow their businesses by understanding trends, buyers’ choices, and emerging patterns. This is what organizations are doing currently, which shows the important role data science plays:
- Creating Data Science Units: Even companies that are not directly linked with Data Science have created a unit where they hire Data Science professionals to work on analytics
- Standardize the processes: This process of standardization helps make good data science systems that can create better models due to the availability of good data that are structured and somewhat cleansed already.
- Data Science related skillsets: In every process and every role, there is an increase in hiring employees with analytical skills. For example, even in the Human Resource roles, companies want to hire applicants who have been previously exposed to analytical tools that enable them to slice and dice data and draw meaningful conclusions from such analysis.
- The building of apps: Almost every service provider owns their apps – banks, telecom, insurance. This enhances more digital interaction with customers and streamlines the digital processes that capture the data in one place later for data modeling.
These trends clearly show the increasing focus on Data Science in the current times.
The Future of Data Science
The market size of Data Science platforms is expected to reach 178 billion US Dollars by 2025. And this is just the Data Science platform that provides open-source software and computing resources which Data Scientists can use and remain updated with the latest developments in the field.
The main reason behind pushing this huge rise is that, with the growth of data size, businesses are ready to invest any amount they can in processing the structured and unstructured data and seeing how they can meaningfully put that data to their use.
To increase revenue, push market boundaries, enhance customer base, companies want to use efficient means to sort the available data and see how they can create prediction models to study consumer trends, growth in demand, a possible slump, competitor analysis.
While many fears that Data Science jobs will be lost in the future due to automation, experts predict that jobs for Data Scientists will change from the way it is today.
The skills will change, and that they will not be lost. Think of computers and computer science engineers’ jobs 15 years back and where technology and computer scientists stand today.
Their skill requirements have changed because newer technology is coming up in the field. Therefore, more specialized skills are emerging. The same thing is likely to happen for Data Scientists in the coming 5-10 years.
Data Science Career in 2025
There are some discontented voices among those who are concerned about the future of technology. They have stated that by 2025, Data Scientists will be unemployed. The important question here is whether it is true?
KDNuggets had conducted a vote with 255 voters to the question: When will most expert-level Predictive Analytics/Data Science tasks – currently done by human Data Scientists be automated?
The voters were distributed across geographies in the following ratio : North America – 43%; Europe – 28%; Asia – 16%, Africa/ ME- 4.7%, LATAM – 4.7%; Australasia – 3.1%. 28% of the voters had stated – in 5-10 years, while 19% of the voters had said that – it will never happen.
Does this sound concern? It should be absolutely not. Because an important fact related to this poll is that it was conducted in 2015.
By that logic, Data Scientists should have become unemployed already. However, the truth is, the jobs in this field have trebled in the past 3 years.
That is the thing with data and technology. With the 2k boom, people had worried. They anticipated the end of the workforce as they feared everything will be automated by computers. Has that happened? Instead, employment has gone up.
Today, it is possible to make employment possible in different areas and take jobs to different geographies because of computers and technology. It is the same with Data Science.
Even if we accept that Data scientists can create all possible predictive models with Data Science in the next five years (according to the poll), the world will need more data scientists to use those models and improvise them.
As more and more companies start depending on data science to enhance their business possibilities, more professionals will be needed in the field. It is not too easy to reach satiety simply by automating.
Now, some good news. The US Bureau of Labour Statistics has stated that the jobs requiring Data Science skills will rise by 27.9% by 2026.
Glassdoor has announced that Data Scientist is the number one job in the US for four consecutive years. What more needs to be told about this field?
It is a smart move to choose a career in Data Science now, not just for the pay or the demand, but because economies can change simply because of data, which a Data Scientist can churn up. Below is a list of 8 Data Science jobs that will boom in the 2025 job market:
- Data Scientist
- Data Analyst
- Machine Learning Specialist
- Business Intelligence Developer
- Data Engineer
- Data Architect
- Infrastructure Architect
- Statistician
How is Data Science influencing students’ choices for the future?
After completion of higher secondary education, students are at the crossroads of many course choices. Of them, those who decide to move into science and technology, a large portion are opting for engineering courses.
Engineering students often find themselves asking whether they should opt for traditional engineering courses or go for the newer streams. Is it worth pursuing a course in Data Science?
To answer this question, we offer the following answers:
- Yes, it is worth studying Data Science and analytics because there is a sky ticketing demand for Data science professionals in every industry, and the demand will be too high to fill by 2025 if enough Data science professionals do not join the industry
- Yes, it is worth studying because the salary for a Data Science professional is quite high and will go up further by 2025.
- Yes, if you feel that you have an analytical bent of mind, a problem-solving attitude, and the perseverance to work with voluminous data sets.
In all of the above reasons, we saw that our answers were positive. That’s because it is indeed worth pursuing a career in Data Science if you think you are worth it.
The demand will only go up further. By 2025, the job market will have a large gap between the demand and availability of good professionals.
It is good to utilize this opportunity to your advantage and build a lucrative career that can be rewarding for you and the industry.
Data Science in BMU
At BMU, we are in a constant quest to build a better future, and we contribute towards that goal by strengthening our courses.
We make our courses more relevant with industry experts’ help and through our tie-up with the Imperial College, London.
We offer a specialization in Data Science and Artificial Intelligence (DS & AI) for our students in the Bachelor of Electronics and Communication Engineering course.
The course is aided by Microsoft, which ensures the best of technology. Our attempt to keep our students have an ace over the others with their knowledge of the latest developments in the field of technology, science, economies, and management.
Our students have the opportunity to create data sets and work on real-world applications in our advanced in-campus computing systems. They can also take advantage of our IoT labs to test algorithms and apply the latest techniques.
This helps them to prepare for the real atmosphere where they would work after completion of the course.
We provide simulated industry experience through interfaces, industry visits, technology, seminars where eminent faces from the business visit our campus to share corporate vignettes.
In our endeavor to create an atmosphere that inculcates experiential learning, we are keen to foster learning and problem-solving based culture.
Way Ahead
It is okay to accept that Data Science is the way forward, and by 2025, there will be many additional trends that will emerge. From wars to insurance, healthcare to education, transport, logistics, retail, telecommunication, every industry is empowered through Data Science.
There is a tremendous change in the way work is getting done. It is up to us to adapt to the change and make the most of the demand that has been created around the world in this field.
The engineers of today have a good chance to tap into that opportunity by 2025.