The vast volumes of data generated in the world every day are unimaginable. According to Eric Schmidt, Google’s former executive chairman, this is more data generated in just two days than has ever been generated from the dawn of civilization up to the year 2003. Today, about 2.5 quintillion bytes of data are generated every day, and the figures are rising. No wonder data is famously dubbed the new oil of the 21st century. Data has revolutionized the world, transformed industries, and literally made life simple for humans. Big data is behind all the trends, innovations, and some of the biggest technological advancements happening today, including social media, gaming, the cloud, 3D printing, IoT, and more. This is because data holds information that can change the world.
What happens in between the vast volumes of data collected every day and the actionable information that we get?
This is where data science comes in? In data science, data is collected from various sources, processed, analyzed, modeled, and then interpreted to extract valuable information.
Demand for data science in India
India is renowned for its software and IT industry which has evolved over the years thanks to the rapid technological developments happening in the industry globally. With trends like automation, cloud computing, and others gaining traction and fast, the awareness of the importance of data and the need to make data-driven decisions has grown remarkably. Today, more organizations are in need of data science solutions just as much as there are more learning providers offering the data science course in Bangalore, India, and the world over to fill the now growing data science skills gap.
With the help of data science, organizations are discovering trends and hidden patterns in the markets they operate, learning customer behavior and building stronger customer relationships, mitigating risks, and optimizing growth in many ways. With the demand for data scientists at more than 93,000 in India alone and 2.9 million across the globe, India is poised to be a part of the solution providing qualified talent to India and the world.
The Scope of Data Science in India
Data science is a multidisciplinary field that encompasses mathematics & statistics, computer science & programming, and domain knowledge. Using data science techniques and other technologies like artificial intelligence, machine learning, and deep learning, organizations collect and analyze data to draw insights that are important for decision-making.
In India, just like in other countries across the world, data science is one of the most highly demanded skills, just as data scientists are among the highest-paid professionals. A data scientist typically has a bachelor’s degree in computer science, mathematics, statistics, information science, or other relevant disciplines.
In terms of training, education, and remuneration, India has made leaps, with an entry-level data scientist earning an average annual salary of $89,000 and an experienced data scientist attracting an average salary of up to $109,000 per year, which is way better than many developed countries. India ranks 67th globally in data science skills and 16th in the Asian continent. This explains why India’s IT and data science skills are recognized worldwide.
Over the years, data science has grown to become a broad field. Some of the most demanded data science roles include:
Entry-level data science roles
- Data analyst. The data analyst leverages insight from data to identify areas of improvement in business processes to achieve efficient delivery of products and services.
- Data scientist. The data scientist collects, processes, analyzes, interprets, and models data to recommend effective solutions to business challenges.
- Business analyst. The business analyst manipulates, visualizes, and makes sense of data to help in strategic decision-making.
- Data architect. The data architect plans, visualize, and designs the organization’s data infrastructure and implements data acquisition, processing, storage, maintenance, retrieval, archival, and management solutions into the system.
- Statistician. A statistician uses statistical techniques and models to interpret data analysis results and make recommendations for the business.
Experienced-level data science roles
- Data engineer. A data engineer designs and builds scalable data management systems that collect, process, and convert data into useful information.
- Big data engineer. They design, build, maintain, and manage complex scalable big data processing systems and solutions.
- Machine learning engineer. ML engineers design and build intelligent AI-powered systems that develop algorithms that discover patterns and learn from data to make accurate future predictions.
The scope of data science across various sectors
Data science has penetrated all, if not most, industries of the world. However, data science has impacted some sectors more than others, thanks to the wider adoption of digital technology in these sectors.
Here are six sectors that are enjoying the fruits of data science.
- Data science consulting
There is a dire need for data science consulting services. This is because data science is still a relatively new field to many existing enterprises and startups. Another reason why data science consulting has gained traction is that it is considerably cheaper to enlist consulting services compared to hiring full-time data science professionals.
Data science consulting firms help businesses to leverage insights from the data available to them to better understand their customers and market, project demand, mitigate risks, and more.
- Information technology
In IT, data scientists help in developing tech solutions, software, services, and others that are used for data analysis and management.
Healthcare is arguably one of the greatest beneficiaries of big data and data science and one of the fastest-growing industries with more opportunities for data scientists. From mapping, the spread of a viral infection, efficient diagnosis and treatment procedures, and better patient monitoring and care to health and drug research, the high volumes of data collected from medical and billing records, wearable devices, clinical systems, and equipment carries valuable information that has the potential to transform healthcare operations and improve human lives.
- Financial services
Financial services companies like banks and insurance companies rely on data scientists to help detect fraud, assess risks, and identify opportunities for optimizing revenue. This field requires data science professionals with strong business acumen and excellent analytical skills.
Finding the right candidate for a position amidst hundreds or even thousands of applications can’t possibly lack bias when done manually. Using resume and social media data along with data mining, machine learning, and other techniques, data science models run through vast volumes of prospective candidates’ data to identify the right candidates for the job accurately, cost-effectively, and within a short time.
- Advertising and marketing
Marketing and advertising approaches have shifted away from the masses to target individual customers or specialized groups with customized advertisements based on their needs, interests, preferences, and expectations of value. Today, sales conversions are a function of personalized advertising and targeted marketing campaigns.
The future of data science in India
Since 2012, the data science job market has experienced over 650% growth, and a projected 11.5 million jobs will be created by 2026, according to the U.S. Bureau of Labour Statistics. Data is shaping the future of enterprise operations. Already, routine, repetitive tasks are being automated using AI and robotics technologies. Thanks to digital transformation, automation, and ultimately fast-evolving IT roles, the wave of digital bloodbath currently being witnessed across India has pushed professionals to consider upskilling or reskilling to take on in-demand roles like data science.
As more professionals shift their careers to data science and other in-demand roles, the data science skills gap is seemingly still widening, an indication of the rising demand in the job market. This clearly points to data becoming more crucial in business operations while at the same time being generated in such high volumes, velocity, and variety that enterprises cannot handle unless with the help of professionals.
Finally, the passing of the General Data Protection Regulation (GDPR) in May 2018 gives businesses a stronger ground to hire data scientists. Consequences of non-compliance have become too dire and costly for businesses to want to go down the path. Among other roles, data scientists are also responsible for data protection compliance.