Structuring Quality Data at Scale
Data-science tech developer Hivemind designed a quantitative experiment to determine which type of workforce completed a series of increasingly complex tasks to deliver the highest-quality structured datasets. Which workforce performed better?
Was it CloudFactory’s managed workforce or a top crowdsourced workforce?
This webinar reveals the study’s results and dives into the:
- Strategic implications of using different types of workforces for structuring data
- Positive impact of paying workers by the hour as opposed to the task
- Pros and cons of an anonymous crowdsourced team versus a managed team of data workers
Philip Tester Moderator
Philip is Director of Business Development at CloudFactory, where he creates partnerships to help solve data-production problems for AI innovators.
Daniel is CEO of Hivemind, a software company that helps its clients build, clean, and enrich datasets from messy or unstructured information.
Mark Roulston Presenter
Mark is Co-founder and Senior Data Scientist for Hivemind.