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UC Berkeley, Fall 2020

Efficient fund allocation for NGOs

Partner: Cara Arellano, DaanMatch, Industry

Overview

Project Description

DaanMatch is a project to address social inequalities in fund distribution in India. Recent data shows that around 60% of organizing funding is allocated to projects in urban areas and that the most benefited are a few multinationals NGOs. But around 70% of NGOs registered in India are community-driven and operate in rural areas, which means a big amount of data and points of action that could spread social impact widely throughout the country.

How can we use data science techniques to transform the information that is currently distributed across heterogeneous data silos into a Pan India tool to aid decision making in this time of crisis?

Expected Deliverable

We hope to see a relational database to provide a semantic layer that can make/integrate all the disparate data sources searchable as one large data lake that could facilitate visibility on the following:

  • Additional potential sources of funding from the Indian diaspora who could be mobilized to help during this time of crisis.
  • Geolocation mapping of population, economic conditions, resources, medical, etc.
  • Organizations and networks in India with scope and capacity to provide emergency relief
  • PAN card/Aadhar coverage
  • Government Schemes available
  • National, State, and Municipal programs and resources that are available

What would a successful semester look like to you?

It would look like a semester where we could learn and use, at least, a functional platform that provides descriptive and inferential insights of the datasets with a friendly technical and project management support.

Data

Models

Conclusion