🎯 Situation

Deux entreprises. Même outil SaaS — une plateforme de gestion de projet. L'entreprise A exporte les données manuellement chaque vendredi, les colle dans Excel, les reformate, et les charge dans Power BI. L'entreprise B tire via API chaque nuit, charge dans Azure SQL, Power BI s'actualise automatiquement.

👉 L'export Excel résout le problème du jour. L'API résout le problème pour les trois prochaines années. La différence n'est pas la sophistication technique — c'est si le pipeline nécessite une personne à chaque fois, ou tourne de façon autonome une fois construit.

⚠️ Challenge

📄 Excel export: what you get

  • Immediate — data available now, no setup required
  • Familiar — any team member can do it
  • No technical dependency — works even if the API changes
  • Flexible — can grab exactly the columns you want visually

🔌 API: what you get instead

  • Autonomous — runs on a schedule without human intervention
  • Consistent — same columns, same format, same logic every time
  • Auditable — every run is logged with timestamp and row count
  • Scalable — handles 100 rows or 10 million without changing the code
  • Combinable — join multiple API sources on a shared key in the database

🔍 Analyse

The real cost calculation over 12 months:

Excel export approach: - 90 minutes/week × 52 weeks = 78 hours of analyst time/year - At $50/hour fully loaded cost: $3,900/year in labor - Plus: 3 incidents of broken files requiring investigation = ~6 hours = $300 - Plus: 1 format change requiring 2 hours of rework = $100 - Total cost: ~$4,300/year (ongoing, every year)

API approach: - Initial build: 4–6 hours (one-time) = $200–300 - Maintenance: ~2 hours/year for minor updates = $100/year - Azure SQL storage: ~$75/month = $900/year - Total cost: ~$1,300 first year, ~$1,000/year after - Break-even: approximately month 4

After month 4, the API approach costs less and delivers more — fresher data, no human dependency, fully auditable. The Excel export never improves; it keeps costing the same every year.

✓️ Bonne pratique

When to use each:

Excel export is fine when: - You need data once, for a specific analysis, with no plan to repeat it - The SaaS tool has no API or the API is too restricted to be useful - You're evaluating whether the data is worth automating before committing time to build the pipeline

API is the right choice when: - The export happens more than once a month - The data feeds a recurring report or dashboard - Multiple people depend on the data being current - You need to join data from this source with data from another system

💡 Synthèse

The Excel export is a prototype. The API is the production system. Both have their place — but the mistake is treating a prototype as permanent infrastructure. Every recurring export that's been running manually for more than six months is a pipeline waiting to be built.

👉 The manual export isn't free. It costs analyst time every single time it runs.

The API costs time once. Then it runs itself.