Transform data management
Your data are the foundation for research and decision-support. Ensure interoperability, transparency and probity by using readable, auditable crosswalks.
Derive schemas from source data
Import CSV, XLS or XLSX source files. Derive or coerce unruly data into a defined schema.
Define schema-to-schema crosswalks
Drag 'n drop sequential actions to define structured and readable schema-to-schema transform methods.
Manage data science research teams
Manage teams with authentication, and assign rights and tasks. Schedule and track a calendar of data updates and transforms.
Execute and fetch data transforms
Make API calls to bulk create tasks or export transformed data for local automation. Download restructured data as CSV, Excel, Parquet or Feather.
Ensure interoperable standards and validation
Document BibTeX-compliant metadata for projects, collections and source data. Validate output data against an associated transformation method.
Integrate Whyqd into your workflows
Deploy the open source Whyqd stack as a standalone data science hub on your own infrastructure, or integrated as a Python package in your software.