As the world entered the era of big data, the need for its storage also grew. It was the main challenge and concern for the enterprise industries until 2015. The main focus was on building a framework and solutions to store data. Now when Hadoop and other frameworks have successfully solved the problem of storage, the focus has shifted to the processing of this data. Data Science is the secret sauce here. All the ideas which you see in Hollywood sci-fi movies can actually turn into reality by Data Science. Data Science is the future of Artificial Intelligence. Therefore, it is very important to understand what is Data Science and how can it add value to the business. Data Science is a field that covers data cleansing, preparation, and analysis. It is an umbrella term that includes several scientific methods, such as mathematics, statistics, and many other tools scientists apply to extract knowledge from data sets.
According to International Data Corporation IDC’s Global DataSphere Forecast, Productivity/embedded data is the fastest growing category of data creation with a 40.3% CAGR for the 2019–2024 forecast period. By 2024, entertainment data will be 40% of the Global Data Sphere and productivity/embedded data will be 29%, stalled somewhat by COVID-19 dynamics. This also means that there is going to be a bigger gap in demand and supply of data scientists, including professionals for information management, software development, data analytics, artificial intelligence, and data discovery. Hence, Python, R, SAS, Machine Learning, etc. have become the most sought after skills.
According to Glassdoor’s Best Jobs in America list in 2016 and 2017, with 4,84 positions were available and with a median base salary of $110,000. DevOps engineer came in second, with a median base salary of $110,000 and 2,725 job openings. Data engineer rounded out the top three, with 2,599 job openings and a median base salary of $106,000. The average salary for a data scientist with fewer than five years’ experience in 2016 was $92,000.
The IT industry is expecting to add around 180000–200000 fresh job vacancies that are related to recent technologies like Data Science and Machine Learning. This job profile offers great opportunities to freshers who have the relevant skills and they have an extremely bright future ahead. As per TeamLease Services – a popular staffing solutions co. – by the year “2020, India will face a demand-supply gap of 2,00,00 data analytics professionals”
There will be a sharp increase in demand for data scientists by 2020. According to IBM, an increment by 364,000 to 2,720,000 openings will be generated in the year 2020. This demand will only grow further to an astonishing 700,000 openings.
Data Science is predicted to grow over the next decade. It is a staggering fact that over 90% of the data in the world was generated in just 2 years. It is unimaginable to realize the amount of data that will be generated in the next decade. The demand for data scientists will rise by 28% by 2020 alone. More and more industries are becoming data hungry and they need data to hold specialized data scientists who can craft products for the customers. About 11.5 Million jobs will be created by 2026 according to U.S. Bureau of Labor Statistics
Become A …
- Data Administrator
- Data Analyst
- Data Scientist
- Machine Learning Engineer
- Machine Learning Scientist
- Applications Architect
- Data Architect
- Enterprise Architect
- Business Intelligence Analyst
Dr. Satheesh A.
Ph.D., Post-Doc (NTPU, Taiwan)
Dr. Satheesh Abimannan received his Ph.D. Degree from the Department of Computer Science and Engineering at the Periyar Maniammai University in 2015. He has done a Postdoctoral Fellow in Research Centre on Big Data and Smart City from National Taipei University, Taiwan. He has more than 20 years of teaching, research, and administrative experience. Currently, he is working as a Professor & Director at the School of Data Science of Symbiosis Skills & Professional University (SSPU), Pune. His area of research interest includes Deep Learning, Cloud Computing, Big-Data analytics, and information security. He has published more than 40 research articles in high-quality journals and international conference proceedings. He has filed four patents in the area of soft computing, cloud computing, and IoT. He is also a Reviewer of many IEEE, Elsevier, Springer, and Inderscience Journals.