Using Time Series Forecasting to Improve Access to Safe Sanitation
More accurately forecast future waste volume collected across Sanergy’s FLT network.
Using Time Series Forecasting to Improve Access to Safe Sanitation Read More »
More accurately forecast future waste volume collected across Sanergy’s FLT network.
Using Time Series Forecasting to Improve Access to Safe Sanitation Read More »
During the high-energy, three-day marathon-style DataDive® event that took place March 4-7, 2021, volunteers on this project set out to do the following:
Develop and provide Thresholds with a data warehouse to house, scale and process raw data from various sources including Thresholds internal systems, the Illinois Department of Healthcare and Family Services, the Cook County Jail and other potential future data sources.
Automate the process of data flow from a central database and create tools to help make managing patient data, generating reports and dashboards easier and more efficient for Thresholds staff, allowing them to better serve their patients.
Explore the possibilities of using predictive analytics to help Thresholds better tailor care to people suffering from mental illness.
De-siloing Data to Help Improve the Lives of those Suffering from Mental Illness Read More »
Gain basic insights about what newly released data shows about UK companies
Uncover flaws in the data to improve future data collection efforts
See whether the data points to any promising leads for further investigation
Using Open Data to Uncover Potential Corruption Read More »
Using Microcred’s loan application data and internal loan status information, build statistical models to help predict customer default and better inform decision making about lending to make it more efficient and inclusive.
Identify whether loan application data and factors such as past repayment behavior or late payments during the early stages of a loan cycle could predict default.
Advancing Financial Inclusion in Senegal Using Predictive Modeling Read More »
Partner with New York, Seattle, New Orleans, and Microsoft to explore how data science can help the Vision Zero movement, which aims to reduce traffic-related deaths and severe injuries to zero
Help New York City’s Department of Transportation improve traffic safety on its streets by understanding what existing safety interventions are working and where there is potential for improvement so the city can better allocate resources
Inform Seattle’s Department of Transportation’s Bicycle and Pedestrian Safety Analysis to provide policy makers and engineers with actionable information to best allocate funding for future safety interventions and to find out what factors may contribute to crashes–such as traffic volume, street characteristics and environmental variables
Help the City of New Orleans’ Office of Performance Accountability understand how effective street treatments, like bike lanes, traffic signage and other interventions, are at preventing traffic injuries and fatalities to inform future efforts
Creating Safer Streets Through Data Science Read More »
Data Integrity and the Future of Intelligent Community Health Systems in Uganda One billion people lack access to healthcare because they live too far from a health facility, so digitally-enabled Community Health Workers (CHWs) have been a lifeline in communities where health infrastructure is lacking. For instance, it’s estimated that …
By Afua Bruce, Chief Program Officer, DataKind This is the second blog post in our ethics blog series. Read about how DataKind defines data ethics and embeds ethical checks throughout the project process in this introductory blog on our ethical and responsible data science practices at DataKind. This blog includes …
By Rachel Wells, Senior Manager, Center of Excellence, DataKind At DataKind, we take an expansive definition of data ethics and responsible data science as broad terms that can be used to describe the appropriate handling of data, use and performance of models, inclusion of stakeholders, staffing of teams, and more. …
Our Ethics + Responsible Data Science Practices at DataKind Read More »