64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Data Science Techniques for Sustainable Development Goals in BRICS




  • EG
    Ezra Gayawan

  • GV
    Dr Gajendra Vishwakarma
  • Risk Based Modelling and Data Analysis

  • CV
    Prof. Carla Almeida Vivacqua
  • Using Data to Address Climate Action

  • AO
    PROF. DR. Olushina Olawale Awe
  • Supervised Machine Learning Prediction of Non-Communicable Diseases for Improving Health Interventions in BRICS Nations

  • JK
    Jitendra Kumar
  • Merger and Acquisition (M & A) Modelling under Bayesian framework: A case of ICICI Bank, India

  • RV
  • Predicting short-lived climate pollutants with supervised machine learning: a study for its mitigation aiding climate change actions

  • Category: International Statistical Institute


    The Sustainable Development Goals (SDGs) were established in 2015 by the UN to end poverty and to ensure gender equality, peace, and prosperity around the world by 2030. They have been planned with seventeen goals to implement sustainable development in the social, environmental, and economic domains while ensuring the inclusion of all stakeholders-national governments, international organizations, private sectors, and ordinary citizens to achieve the targets.

    SDGs have proved to be challenging missions to accomplish in less developed countries. Some of the major challenges in implementing the SDGs in developing and least developed countries include a huge population burden, a lack of infrastructure, skills, and technology, insufficient funding, and social and political disparities. As a result, greater success in achieving the SDGs requires collaborative action by all developed, developing, and least developed countries. BRICS (Brazil, Russia, China, India, and South Africa) countries in collaboration have emerged as a powerful aid to promote SDGs in developing nations. Sharing the common goals and challenges of developing countries, BRICS have been actively building support systems through collaborations and financial aid to achieve SDGs such as innovation and infrastructure, clean energy, peace establishment, healthcare for well-being, and sustainable economic growth within and beyond national borders.

    The use of Big Data (a Data Science tool) and the sharing of knowledge, technology, and experiences to meet SDGs was emphasized by the BRICS Academy of Sciences at the BRICS Forum on Big Data on Sustainable Development Goals held on April 26-27, 2022. Indeed, data-driven tools have the potential to significantly accelerate progress toward the SDGs. Monitoring the progress of SDG achievement necessitates data collection on SDG indicators, data management to deal with large amounts of data and data discrepancies, and useful analytical insights through data to identify and fill the progress gap. Thus, Data Science, a common platform that uses mathematical, statistical, and computing tools to explore hidden patterns in data and present meaningful information about it, has been used by BRICS to respond to SDG-related demands.

    In line with BRICS' acknowledgment of the need for Data Science in sustainable development, this proposed invited session includes four talks emphasizing on the Data Science methodologies and their applications in the ongoing research on the SDGs in the BRICS countries. The talks will focus on some of the SDGs- well-being and good health, economic growth, climate action, quality education, and industry innovation, which require much attention of the BRICS nations for the overall sustainable development of these nations. We hope that the session shall provide useful insights of data science tools and their possible use for achieving sustainable goals in developing countries.

    Keywords: Data Sceince, Sustainable Development Goals, BRICS