Future of Data Science : Trends & Future Scope

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The term 'data science' has become ubiquitous in recent years, often linked to the scope of data science and pondering does data science have a future. It's used to describe everything from the collection and analysis of data to predictive modelling and machine learning. But what, exactly, is data science, and what does the future hold for this field?

In this article, we will delve into the scope of data science in India and its promising data science future scope, discussing how it is poised to reshape the country's economy in the forthcoming years.

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What is data science?

At its core, data science is about using data to answer questions, which underscores the significant scope of data science and the future scope of data science. To do this effectively, data scientists need to be adept at collecting, processing, and analysing data. They also must utilize various tools and techniques to develop models for making predictions or recommendations.

The potential of data science was first realised in the early 2000s when companies like Google and Facebook started using it to mine user data and improve their services. Since then, the scope of data science has evolved rapidly, and the future of data science is now leveraged across various industries to drive business decisions.

In India, data science is rapidly revolutionising many industries. With the advent of big data, there is a growing scope for data science, and the demand for data science in India is at its peak, reflecting the country's commitment to embracing this innovative field.

According to a recent report by IBM, the demand for data scientists in India will surge by 28% by 2024, highlighting the robust data science scope. As more organisations realise the importance of data, the need for data scientists will continue to escalate. With the right skills and training, you can position yourself to take advantage of the future scope of data science.

The future scope of data science in India looks very promising, with several factors driving the growth of this field.

Factors driving the growth of data science in India

1) The growing volume of data

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‍The data science and its impact on big data in the future is becoming increasingly significant with the proliferation of devices and the surging internet usage. By 2025, it is projected that there will be 180 zettabytes of data globally, highlighting the expanding scope in data science. This vast amount of data can be leveraged to gain insights into customer behavior, foster the development of innovative products and services, and propel informed business decisions.

2) The availability of talent

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India boasts a burgeoning pool of skilled data scientists, with a recent NASSCOM report indicating the presence of over 200,000 data science professionals in the country. With targeted training and development, this talent pool can be effectively utilized to accelerate the growth of data science in India.

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3) The government's push for digitisation

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The Indian government's drive towards the digitisation of various sectors is carving out numerous career opportunities in data science in India. Initiatives like the development of a National Health Stack underscore the need for data scientists to devise algorithms that enhance the efficiency of healthcare service delivery, thereby expanding the scope of data science in India.

4) The growth of startups

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Startups are pivotal in propelling the growth of data science in India, with a NASSCOM report citing over 4,200 startups employing data science to tackle diverse challenges and advance their business objectives. These data science companies are at the forefront of innovation and problem-solving, marking a significant trend in the industry.

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5) The increasing investment

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Investments are pouring into the data science sector in India, a trend underscored by a NASSCOM report that forecasts the data science market to burgeon from $1.3 billion in 2018 to $2.9 billion by 2024. This surge in investment is a testament to the dynamic data science trends shaping the industry's growth in India.

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Industries likely to be impacted by data science in India

1. Healthcare

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In the healthcare industry, data science in India is instrumental in developing sophisticated algorithms that enhance the delivery of healthcare services, demonstrating its transformative potential.

2. Banking and financial services

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Within the realm of cyber security, data science is increasingly employed to construct predictive models that are pivotal in detecting and preventing fraudulent activities.

3. Retail

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In the ecommerce industry, data science in India is pivotal for crafting recommender systems that personalize the shopping experience for customers.

4. Manufacturing

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Data science can optimize production processes and improve product quality.

5. Agriculture

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Within the agriculture industry, data science is instrumental in developing yield prediction models that assist farmers in increasing their crop yields.

How to become a successful data scientist in India?

To excel in data scientist roles, understanding data science and having a good grasp in the below things is necessary;

1. Learn how to code

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Core Python and R programming are essential for data scientists working effectively with data, as most rely on these languages for data analysis. However, other programming languages like Java, Scala, and Julia are also viable options for data science.

2. Understand statistics

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Data skills such as a strong understanding of statistics are essential for data scientists, enabling them to analyze data effectively and draw meaningful conclusions.

3. Know how to use data visualisation tools

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Data visualization tools, including Tableau and D3.js, are vital to data scientists as they allow the transformation of complex data sets into easy-to-understand visuals.

4. Be able to work with big data

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Big data analytics is a crucial aspect of data scientists' roles, requiring the use of specialized tools and techniques like Hadoop and Spark to work effectively with large data sets.

5. Understand machine learning

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The intersection of artificial intelligence and data science scope is epitomized by machine learning, a pivotal component of AI that focuses on crafting algorithms adept at learning from data and forecasting outcomes. To thrive as a data scientist, a profound understanding of machine learning and its broader field, artificial intelligence, is indispensable. Data science and artificial intelligence knowledge helps to build effective models.

Job prospects of data science in India

Data science is one of the most sought-after skills in the job market today. The growing scope of data science will create many job opportunities for data scientists in India.

LinkedIn's recent study underscores the expanding data science in India, with an astonishing 400% increase in the demand for data science talent over the past two years. Job listings are on the hunt for skilled data scientists, data analysts, business intelligence analysts, and the highly coveted data engineers.

The promising data scientist scope in India is mirrored in the average annual salary, which hovers around Rs 7-8 lakhs. Nonetheless, seasoned data scientists with the right expertise can earn upwards of Rs 20 lakhs, reflecting the lucrative nature of data science in India.

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Given the escalating volume of data, the pool of adept professionals, and the government's commitment to digitisation, it's evident why data science is the future in India and why it's considered a good career path. Should these favorable conditions continue, data science is set to revolutionize a myriad of sectors throughout the country.

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