Orchard <> Magicspoon
Date: February 17, 2026 Source: Granola Meeting ID: e928df2d-3447-458e-9b3e-002c0c9b6371 URL: https://notes.granola.ai/t/e928df2d-3447-458e-9b3e-002c0c9b6371
Participants:
- Uttam Kumaran (Brainforge)
- Ryan Brennan (Skio/Orchard Analytics)
- Roland Cassirer (TireAgent/Orchard)
- Anne (Magicspoon)
- Mary (Magicspoon)
- Nelle Lightbourn (Magicspoon)
- Amelia (Magicspoon)
- Alexa Minotti (Magic Spoon)
- Justin Tabarini (Magicspoon)
- Alejandro (Magicspoon)
- Michael Thorson (Magicspoon)
- Demilade Agboola (Brainforge)
Summary
Data Infrastructure Overview & Reliability
- Stitch connectors generally stable
- Google Sheets most error-prone due to manual data entry
- Shopify and Ads Manager connectors reliable
- Prefect deployment solid overall
- Business Central API pipelines only consistent problem area
- Frequent timeouts, both full refresh and incremental queries
- Retry improvements may help but won’t fully solve
- Alternative: Work with Lid team for custom endpoints
- All syncs clearly named for easy identification
- No memory or infrastructure issues
- Business Central API pipelines only consistent problem area
- Token/credential management
- Amazon updates keys every 6 months to 1 year
- Environment file with all credentials coming via 1Password note to Mary
- No frequent rotation requirements (nothing every 30 days)
DBT Models & Data Architecture
- Core failure points minimal
- Only fails on bad Google Sheets inputs or dev branch references
- YAML config issues occasionally but easily fixed
- Shopify data structure
- Historical Canadian storefront unioned in (4+ years old data)
- Current focus on US storefront
- Custom “units” logic explodes line items into individual components
- Multiple fulfillment methodologies handled over time
- Component categorizations managed via Google Sheets
- Well-documented but complex due to historical changes
- Revenue model recently simplified
- Now gross, net, and discount amounts
- Unit-based revenue approach (non-standard)
- Returns handling built into revenue model
- Amazon integration straightforward
- Orders become line items, same mapping logic as Shopify applies
- Fulfilled shipments contain customer address data
- Legacy cleanup opportunities
- Retail data, Parabola workflows, House data all deprioritized
- Data science folder no longer relevant
- Some snapshots unnecessary
Key Transitions & Technical Debt
- Major revenue metrics transition in progress
- Moving from existing to new revenue definitions
- All pieces ready, needs strategic execution
- Business Central API migration
- V2 endpoints built parallel to old ones
- Transition timing depends on team comfort level
- Shopify API version updates
- Recent change (4-6 months ago) required ID parsing adjustments
- Full historical backfill completed for US storefront
- Canadian storefront still requires old joins
- Klaviyo reverse ETL
- Only reverse ETL process running
- Three Prefect syncs, very stable
- Profile updates infrequent
- Redshift performance adequate
- Most models don’t need incremental processing
- No capacity issues
- Some incrementality on Klaviyo events and BigQuery events only
Next Steps
- Mary: Provide DBT admin permissions to Brainforge team
- Roland: Send environment file with credentials via 1Password note to Mary
- Brainforge: Set up email alerting for DBT failures
- Brainforge: Consider Metaplane alert cleanup and customization
- Roland available for follow-up questions (include Mary for coordination)