To quote the Economist, in the year 2017, “The world’s most valuable resource is no longer oil, but data.” As we look closer at this comparison, it becomes apparent that data has now become as important to businesses as oil once was. As business moves closer to digitalization, data has become more important than ever.
Many businesses have turned to analytics to discover significant insights, and data is referred to as the fuel for meaningful insights. The future application of data science is largely carried by the potent mix of both.
Organizations are developing new strategies all across the world to harvest data and employ this potent instrument to propel their enterprises. Research estimates, by 2030, the annual data analytics market is expected to reach $24.63 billion, growing at a CAGR of 25%.
Let’s take a closer look at how data science is set to develop over the next few years.
Data Science – What is it?
Data Science is a diverse and rapidly growing field of study that merges data mining, data analytics, data engineering, machine learning, and data visualization. It has revolutionized the way businesses make decisions by pulling data from many different sources to develop deeper insights.
Data Science jobs continue to be in high demand as companies recognize the need for employees with specialized data extraction, analysis, and communication knowledge. Data science skills are applicable across multiple industries, from medical research to financial services and beyond. As a result, companies are on the lookout to become data-driven to remain competitive and gain an advantage over their rivals.
Importance of Data Science in the Coming Years
The scope is immense in data science, meaning it will be increasingly important to businesses. With actionable tools like data analytics and data modeling, data science can help turn data into valuable insights, enabling businesses to make data-driven decisions that can increase their competitiveness in today’s data-rich environment.
With the combination of data science with artificial intelligence, even greater value can be extracted from data, as AI algorithms learn from data patterns and recommend more accurate and efficient decisions. Data science has already reached a point where it enables researchers to rapidly increase their understanding of data. This allows data scientists to accurately predict outcomes and trends to support decision-making.
With data being generated at an ever-increasing rate and advances in technologies such as AI and machine learning, data science will only become more impactful in the years ahead as businesses seek faster outcomes with greater accuracy. Companies cannot afford to neglect the possibilities of data science in the upcoming years and need to start investing to reap the full benefits quickly.
The Demand Curve for Data Science
As data becomes the future oil of organizations, analytics have become an engine for gaining meaningful insights. It is the powerful combination of these two factors that drives the future scope of data science. Data is proving to be a powerful tool that organizations are using to drive their businesses all over the world. Massive data influx combined with the need to harness this enormous amount of data has created a huge job market in data science.
Data science jobs are among the most sought-after and fastest-growing in the global industry. Data scientist positions have had a 650% increase since 2012, according to Linkedin. The U.S. Bureau of Labor Statistics estimates that there will be a further 27.9 percent growth in demand for data science expertise with a steady market growth of $322.9 billion by the year 2026.
The growing sophistication of data technology is driving a shift toward data science jobs in India. By the Times of India, India ranks second in the world in terms of attracting young people for data science and associated research. Additionally, the World Economic Forum predicts that by the end of 2022, data scientists and analysts would rank among the top-growing professions.
As data science technologies further develop and expand, there will be a requirement for skilled data scientists to continue to maximize the potential of data analytics, in India. Companies that recognize the importance of data science expertise and invest in data experts will remain at the forefront of the industry and capitalize on the opportunities presented by data technology.
Scope in the Data Science Industry in India
Large Indian corporations in legacy industries like power, steel, and energy have a good overall adoption rate of around 74.5% for analytics and data science. However, for businesses, the supply-demand imbalance is a serious concern. At the moment, India has never had more of a need for data scientists.
Let’s look at some of the statistics to determine the scope of data science jobs in India.
- Analytics Insights predicts that by 2026, India will account for 32% of the global big data market and produce USD 20 billion.
- AIM Research’s latest study indicates that India now accounts for 9.4% of all worldwide analytics job vacancies, up from 7.2% in 2020 January.
- Furthermore, according to projections, the Indian analytics market is expected to grow to $ 98 billion in 2025 and around $ 119 billion in 2026.
- By 2026, analysts estimate that India alone will have almost 11 million employment opportunities in the field of data science.
Data science is an interdisciplinary field that goes beyond technological expertise. The commercial world offers several opportunities for the young people of India. In practically every division of a business, they can also assume leadership roles. Thus, aspiring data scientists might make use of these chances to seize the greatest possibilities available and hit career milestones.
What are the Career Options in Data Science?
To explore data science as a career, a data scientist needs to have a strong mathematical and statistical background. Some of the widely sought career options in data science include:
1. Data Scientist
2. Data Architect
3. Business Intelligence Analyst
4. Data Analyst
5. Big Data Engineer
6. Machine Learning Engineer
7. Data Warehouse Engineer
8. Data Visualization Specialist
9. Data Modeler
10. Database Administrator
11. Data Mining Specialist
12. Artificial Intelligence Engineer
13. Predictive Analytics Specialist
14. Natural Language Processing Engineer
15. Cloud Data Engineer
16. Cybersecurity Analyst
17. Deep Learning Engineer
18. Data Engineer
19. Business Analyst
20. Marketing Analyst
Estimated Salary Structure for Data Science Jobs in India
One can begin as a data analyst, business analyst, or data engineer at the entry level. A business analyst may earn an average income of INR 7 LPA with a broad range of INR 3 LPA to 15.3 LPA depending on their experience, while a data analyst can expect to make INR 4.3 LPA on average with a band of INR 1.8 LPA to 11.9 LPA. The income range for a data engineer is INR 3.5 LPA to 21 LPA, with an average of INR 8.3 LPA.
Apart from the aforementioned entry-level jobs, a data scientist can also work as a business intelligence developer with an annual data science salary of INR 3.5 LPA TO INR 16.5 LPA bandwidth. Additionally, a machine learning scientist’s salary range ranges from INR 4 LPA and 52 LPA.
(Source – Times Of India)
Overall, if you wish to work with data-driven decision-making, a career in data science is a fantastic choice. With its expanding future potential, data science is a choice that is worth considering. Data science jobs typically pay well and offer exciting career opportunities.
Training Basket is a one-stop platform to curb your needs for data science with Python.
With best in class innovative curriculum, Training Basket is equipped with the best faculties to help data science aspirants make the best out of the institution.
Get in touch with the experts today!