• Academic / Journal Article

Role of Big Data Analytics in Power System Application

  • Source : LatentView Analytics
  • 1 January 1970
This academic paper investigates the significant role of big data analytics in various power system applications. It explores how the increasing volume, velocity, and variety of data from smart grids, sensors, and other sources can be leveraged to enhance power system operations, efficiency, and reliability. The paper likely covers applications such as fault detection, predictive maintenance, load forecasting, and optimized energy management, demonstrating how big data analytics is transforming traditional power systems into more intelligent and resilient infrastructures.
  • Book

Leveraging Data Science for Global Health

  • Source : SpringerLink
  • 1 January 1970
This book explores the transformative potential of data science in addressing complex global health challenges. It covers various applications, from disease surveillance and outbreak prediction to optimizing healthcare resource allocation and personalized medicine. The text highlights how data-driven approaches can lead to more effective interventions, improve health outcomes worldwide, and contribute to achieving global health equity. It serves as a comprehensive resource for understanding the intersection of data science and global health initiatives.
  • Case Study

Using Blended Finance to Access Commercial Finance

  • Source : World Bank
  • 1 December 2020
This World Bank report outlines how blended finance can be effectively utilized to attract and access commercial finance for development projects. It details various structuring approaches that combine public or philanthropic funds with private capital to de-risk investments and enhance financial viability. The paper provides practical insights into how these financing models can bridge funding gaps, encouraging private sector participation in high-impact initiatives.
  • Paper / Report

Needs Assessment on Resources for Use of Routine and Other Secondary Data for Health Evaluation and Research

  • Source : Data for Impact Project
  • 1 December 2020
This article examines the use of routine and secondary health data, identifying key challenges and training needs that impact the effectiveness of data management in health programs. It highlights the increasing demand for capacity building in health data management, particularly in areas related to data governance, quality assurance, and analysis. The article stresses the importance of building the skills of health practitioners to ensure that routine data can be used effectively for program evaluation, policymaking, and continuous improvement. It offers practical recommendations for addressing the training gaps and challenges faced by health organizations in managing their data systems.
  • Blog

Diversity in Data Science: A Systemic Inequality

  • Source : Towards Data Science
  • 1 December 2020
This blog post examines the systemic inequalities prevalent in the field of data science, particularly concerning diversity in terms of race, gender, and ethnicity. It delves into the various factors contributing to the lack of representation, such as unconscious bias in hiring, limited access to education, and exclusionary workplace cultures. The article advocates for a critical examination of these systemic issues and proposes strategies to foster a more equitable and inclusive environment within the data science community, emphasizing its importance for ethical AI development.
  • Case Study

What is blended finance, and why it matters

  • Source : Bank of America
  • 1 November 2020
This article from Bank of America defines blended finance as the strategic combination of public, philanthropic, and private capital to fund sustainable development initiatives. It explains why blended finance is crucial for addressing the significant funding gap to achieve the Sustainable Development Goals (SDGs), especially in emerging markets. The piece highlights how this approach leverages limited public funds to attract larger volumes of private investment, benefiting both investors and communities.
  • Blog

Data Science in Mental Health

  • Source : Towards Data Science
  • 1 November 2020
This blog post explores the emerging role of data science in mental health. It discusses how data analytics and machine learning can be used to identify patterns in patient data, predict mental health conditions, personalize therapeutic interventions, and evaluate treatment effectiveness. The article highlights the potential for data-driven insights to improve diagnostic accuracy, support early intervention strategies, and enhance the accessibility and quality of mental healthcare services. It also touches upon the ethical considerations involved in handling sensitive mental health data.
  • Case Study

Introduction to Green Finance

  • Source : Global Environment Facility
  • 1 October 2020
This document provides an introduction to green finance, illustrating its application through various case studies. It highlights different green finance instruments, including debt financing and equity investments, and discusses how these can be structured to support environmental projects. The examples showcase how organizations like the GEF use blended finance approaches to de-risk investments for private sector participation, encouraging capital flow into sustainable initiatives like forestry, fisheries, and energy efficiency.
  • Media Article

Why Social Workers Need Data Science

  • Source : socialworker.com
  • 1 October 2020
This article emphasizes the increasing role of data science in the field of social work. It outlines how social workers can leverage data to improve outcomes in areas like case management, resource allocation, and decision-making. The piece discusses how data analytics can help social workers better understand the needs of their clients and improve service delivery.
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