Coding Tools for Industry R&D – Development Lessons from an Analytical Lab
summary
Describes concrete development lessons from an analytical R&D lab: collect instrument metadata, shadow users as a detective to find pain points, map requirements and tradeoffs as an architect, and lock representative datasets and performance criteria early as a chef. Recommends building with R and Shiny apps in mind, handling CSV and PDF exports, and agreeing on formats, edge cases, and deployment constraints before coding to avoid repeated rewrites and missed assumptions.
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