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An Efficient Exploratory Demographic Data Analytics Using Preprocessed Autoregressive Integrated Moving Average

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Intelligent Data Engineering and Analytics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 266))

Abstract

The demographic dividend is an essential measure of the growth and development of a country. It refers to the economy’s growth due to a shift in the age structure in the country’s population. In India, around 90% of the population is under the age of 60, which is a stark contrast compared to the world, where more than 20% of the population lies above 60. Such a young population ensures that the working-age group will be vibrant in the coming years, adding to the country’s overall productivity. Today, COVID has caused much damage to an already vibrant economy, because of which millions of people have lost their jobs and have had to migrate back to their hometowns. To recover from this severe damage and take stock of the existing and incoming workforce, it is necessary to identify and analyze the current population that lies in suitable age ranges and understand how to use them optimally. Therefore, analyzing the demographic dividend to identify the workforce of the country becomes an essential task.

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Author information

Authors and Affiliations

  1. Data Science, Manipal University Jaipur, Jaipur, Rajasthan, India

    Siddhesh Nandakumar Menon & Shubham Tyagi

  2. Department of Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India

    Venkatesh Gauri Shankar

Authors
  1. Siddhesh Nandakumar Menon
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  2. Shubham Tyagi
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  3. Venkatesh Gauri Shankar
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Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia

    Peter Peer

  3. College of Computing, Michigan Technological University, Michigan, MI, USA

    Jinshan Tang

  4. Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow, India

    Vikrant Bhateja

  5. Department of Electronics and Communication Engineering, National Institute of Technology (NIT) Mizoram, Aizawl, Mizoram, India

    Anumoy Ghosh

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Menon, S.N., Tyagi, S., Shankar, V.G. (2022). An Efficient Exploratory Demographic Data Analytics Using Preprocessed Autoregressive Integrated Moving Average. In: Satapathy, S.C., Peer, P., Tang, J., Bhateja, V., Ghosh, A. (eds) Intelligent Data Engineering and Analytics. Smart Innovation, Systems and Technologies, vol 266. Springer, Singapore. https://doi.org/10.1007/978-981-16-6624-7_27

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