The mistake most startups make
Most startups build their first dashboards directly on top of the production database. This works until it doesn't — usually around Series A when the database starts slowing down from analytics queries, or when the schema changes break every report at once. The fix is always the same: a proper data warehouse. But by that point, you're also paying the cost of migration.
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What to build at each stage
Pre-seed: Use whatever you have. Google Sheets and Metabase off the production database is fine. Seed: Add a simple ETL to a lightweight warehouse like DuckDB or BigQuery. Stop querying production directly. Series A: Introduce dbt for transformation and a proper ingestion tool. Define your core metrics properly. Series B+: Add data quality monitoring, a semantic layer, and self-serve analytics for the business.
The tools that matter at each stage
The right stack changes with your scale. At seed, Fivetran + BigQuery + Looker Studio is often enough and costs very little. At Series A, dbt becomes essential. At Series B, you need data quality tooling and more sophisticated access controls. The mistake is building a Series B stack when you're pre-seed.
Ankit Parihar
Founder & Principal Data Consultant · Paris, France