Ported a Claude Code-developed, synthetic Netflix streaming analytics HTML dashboard (4 tabs, ~10K subscribers, 105K watch sessions) to a production Sigma workbook, rebuilding the Python data pipeline from scratch in order to generate Sigma-compatible CSVs that were added to and power a Sigma data model.

Key technical work:

  • Rewrote sigma_export.py, expanding output from four CSVs to nine; added waterfall.csv, top_titles.csv, top_titles_by_plan.csv, device_summary.csv, and monthly_views.csv as pre-aggregated files for charts that could not be derived cleanly in Sigma from grain-level session data
  • Applied all notebook transformations at row level: device watch/completion multipliers, seasonality on watch duration, plan duration/completion multipliers; device session count overrides and monthly seasonality on counts/rates handled in pre-aggregated files
  • Added subscription_plan dimension to cohort_retention.csv and waterfall.csv so that the plan filter control on the LTV tab correctly targets all three data sources
  • Completed in Sigma: LTV tab (all 4 charts + KPIs with working plan filter) and Content tab (all 5 KPIs + 4 charts across 4 data sources)