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05 INFORMATION SYSTEMS / RESEARCH TOOLING

Lakehouse Signal.

A Databricks-first cloud and data intelligence terminal for public updates, research and project watchlists.

Private source · Public demoÉTUDE DE CAS TECHNIQUESANS DONNÉES CLIENT
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01 / CONTEXTE

Le problème à résoudre

Relevant cloud and data engineering updates arrive across many publishers and formats, making it easy to lose the connection between news and ongoing projects.

02 / INGÉNIERIE

Du besoin au système

  • Aggregate public publisher feeds into a focused reading environment.
  • Support project watchlists, topic filtering, source health and briefing workflows.
  • Keep local research notes and source links available for follow-up.
  • Serve the public application through a Netlify Function and a minimal static asset bundle.

03 / CHOIX TECHNIQUE

Un choix structurant

Favor attributed source material and deterministic signals over unsupported AI-generated assertions.

04 / PREUVES ET LIMITES

Ce qui est réellement documenté

The private repository contains the feed parser, tests and Netlify deployment configuration. A public Netlify deployment is live; source availability and external adoption are not measured.

05 / PROCHAINES VALIDATIONS

Comment renforcer la démonstration

  • Measure source availability and feed freshness.
  • Add clearer failure-state reporting.
  • Publish a safe video tour.

Ces points sont des pistes de validation, pas des résultats déjà mesurés.

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