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About Datahoom

Datahoom is focused on practical, maintainable data extraction work: clear specs, clean deliverables, and pipelines that don’t collapse the moment a page layout changes.

How we work

  1. Define scope: target URLs, fields, rules, volume, and output format.
  2. Prove with a sample: a small extract to validate schema and edge cases.
  3. Scale safely: robust retries, throttling, and consistency checks.
  4. Deliver clean output: CSV/JSON/DB-ready tables with documentation.

Tooling

We choose the lightest reliable approach for the job (static requests where possible, headless browsing when necessary).

  • Python / Node-based scrapers and parsers
  • Headless browsing when dynamic rendering requires it
  • Data validation, normalization, and schema documentation
  • Scheduling and maintenance plans for ongoing pipelines

Have a dataset in mind?

Send a few example URLs and the fields you need. We’ll respond with questions and a ballpark.

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