What do you need to do in college for a strong future?
Data plays a very important role in understanding our world, physical, biological, social, economic as well as ourselves. Availability of data generally reduces uncertainty and ambiguity in our understanding. Our reliance on data for clearer understanding and decision-making has increased with scientific and industrial revolutions. With increased confidence in data, seven hundred years ago the global data growth curve began to become more vertical and five hundred years ago modern statistics, primarily related to demographics, began to illuminate politics and even to reform society. Almost seventy years ago, computers began to transform our ability to encode, store, analyze and even later share data. Thirty years ago, the Internet began to help create a flood of data. Broadband networks, mobile devices, streaming media and IoT on the one hand, and trends such as urbanization, e-governance, e-commerce, e-learning, e-health , open government data, etc. turn into a crushing deluge.
In 2012, we started to enter the zettabyte era when the total global digital data exceeded one zettabyte, or one trillion gigabytes. According to some estimates, the global volume of data will reach 180 zettabytes by 2025, 572 zettabytes by 2030, and it could even reach 5,00,000 zettabytes by 2050, with 90% of the data being in real time. Data has become more important than ever in today’s industries, driving a growing demand for data science professionals who play a pivotal role in helping businesses and organizations generate actionable insights. Converting this big data will require a lot of effort from data scientists, however, technologies such as machine learning and predictive analytics make the process faster and more efficient. Although dealing with such amounts of data is a challenge, it will also create many opportunities and jobs.
What is Data Science?
Simply put, data science encompasses the preparation of data for analysis, including cleaning, aggregating, and manipulating data to perform advanced data analysis. It is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. According to a 2021 ACM report on data science, it is the field that brings together domain data, computing, and statistical tools to query the data and extract useful insights. Domains create and deliver structured and unstructured data; statistics and mathematics provide tools for analysis, modeling and inference; and computing brings algorithms and technologies for data access, management, protection, and efficient processing in modern computing architectures.
What do data scientists do?
Data scientists have become necessary assets and are present in almost every organization these days. These data-driven professionals identify problems or goals that can be solved through data analysis by identifying relationships and trends that help develop solutions to business, engineering, governance, or scientific problems at the using mathematical theories and techniques and recommending data-driven solutions to key stakeholders. . This filtered information can be used to answer questions and guide the strategy of an organization or business. In this process, they clean and process large data sets, apply feature selection algorithms, compare, test, validate, and reformulate models, create visualizations, and write new programs or applications to perform analysis. They may even have to design instruments to collect data.
What are the career prospects in data science, globally and in India?
According to Michael Page’s report from July 2021, the increase in data science needs will create 11.5 million jobs by 2026 worldwide. According to Analytics India Magazine, in 2022, India contributed 11.6% of the total number of open jobs globally in the field of data science and analytics. With a large pool of STEM graduates, India has a huge opportunity to emerge as a global leader in this field. Analytics India Magazine’s June 2022 report estimates that the overall analytics industry will surpass US$200 billion by 2027 and Indian companies are focusing on increasing the share of new hires to increase their share in this growth.
What Students Need to Learn for a Successful Data Science Career
In order to serve in the fields of data analytics, data science, or business analytics in business, consulting, industry, government, healthcare, education, research, etc. , students must essentially develop the ability to:
- identify, extract and collate available and relevant heterogeneous data and use appropriate computational principles, platforms and technologies to discover new relationships and provide insights into the research problem and/or organizational processes.
- conceive, design, implement and manage data analytics, data management and information systems, services and processes using the principles of computing, data management, learning automation, computer statistics, software engineering and state-of-the-art platforms, components and tools.
A good UG education in computer science, engineering, statistics or mathematics prepares students with the fundamental knowledge and skills needed to develop the above abilities through further education or training. Many universities now offer MTech, MSc, MBA or PG Diploma programs in Data Science, Data Analytics or Business Analytics. A good technology-focused master’s program in data science will normally include courses such as computational statistics, data mining, machine learning, deep learning, big data, cloud computing, web analytics, large graph analysis, natural language processing, computer vision, software engineering, etc. Depending on their strengths in a few application areas, some programs may also include a few area-specific analysis courses, such as financial analysis, e-commerce analysis, manufacturing analysis, sales and marketing analysis, transportation analysis, tourism analysis, human resources analysis, health analysis, agriculture. analytics, etc. Some universities also offer UG programs in these areas. Many online programs are also available, but online programs usually only work for highly motivated students. However, online courses can surely be a great complement to regular university programs. Some universities have already partnered with online platforms like Coursera or edX to enhance their students’ learning.
Students should focus on building their knowledge and skills in statistics, algebra, calculus, programming, machine learning, big data, cloud computing, and software engineering. They must learn computer platforms, technologies and tools such as Linux, Python, R, Java, SQL, Tableau, TensorFlow, Apache Spark, Hadoop, Docker, etc. They need to sharpen their critical thinking skills to ask interesting questions and understand issues and situations from multiple points of view. They must develop their interpersonal skills to communicate with others about complex processes and possibilities. They must also learn to adapt well to teamwork.
Data science is crucial at a time when India aims to become a global hub for manufacturing, artificial intelligence (AI) and related technologies. A large number of data science jobs are expected to be in demand in India as well as abroad in the coming years and students interested in this field should acquire adequate skills during their college studies to build a successful career. . Furthermore, expertise research has shown that it normally takes about ten years of rigorous commitment and deliberate practice in any field to become an expert. Students must therefore exercise patience, stay motivated and engage enthusiastically in the discipline to develop their knowledge and skills. They must also complement their university studies through participation in professional networks, conferences, competitions, training camps and commitments to projects and internships.
The opinions expressed above are those of the author.
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