I. Common Data Infrastructure: help teams set up the right infrastructure to improve efficiency and lower costs.

  • Integration and management of open-source project data
  • Support setting up cloud computing and storage
  • Assistance with managing scripts and repositories

II. Data Science Support: help program teams turn data into insight through analysis, visualizations, and machine learning

  • Data Cleaning, analysis and visualization: manage and analyze data; work with other teams to design and build creative charts and maps to tell the data story.
  • Data Tool Development: build data analysis software and applications that support research and program implementation.
  • Statistics, machine learning and AI consulting: help programs understand new machine learning methods and adopt AI solutions to boost productivity in work.

III. Data product design, acceleration and management: support new data-enabled products and solutions while also maintaining existing data products

For data products, we provide technical support throughout the whole product life cycle, helping increase products’ impact while improving sustainability.

IV. Data Strategy Guidance: when starting a new project, guide program teams to harness data and technology to reach their impact goals while avoiding common pitfalls

  • fundraising for data-driven projects
  • parsing data policies
  • consulting with the Data Lab to develop teams’ data strategy