Data warehouses power analytics and decision-making—but poorly planned projects lead to overruns, performance issues, and unhappy users. At Essid Solutions, we’ve rescued many failing warehouse projects. Here are 7 common mistakes to avoid.

❌ 1. Lack of Clear Ownership

Nobody owns the pipeline, schema, or cost. Fix it with data product ownership and documentation.

❌ 2. Overengineering Early

You don’t need 6 layers of abstraction and real-time ETL on day one. Start simple, then scale.

❌ 3. Ignoring Governance and Access Controls

Anyone can write, delete, or query everything? That’s a recipe for disaster.

❌ 4. Treating SQL Like a Programming Language

Avoid unreadable, 500-line SQL. Modularize with dbt, use CTEs, and document logic.

❌ 5. Not Testing Your Data

Bad data is worse than no data. Add dbt tests, constraints, and freshness checks.

❌ 6. No Cost Visibility or Controls

Warehouses like Snowflake or BigQuery charge per compute/query. Add dashboards and alerts early.

❌ 7. No Dev/Test/Prod Environments

Working directly on production tables is risky. Use branching and promotion workflows.

💼 Use Case: Media Analytics Project Rescue

A media company was running slow dashboards and spending too much on Snowflake. We:

• Audited pipelines, added dbt testing
• Introduced CI/CD for dbt models
• Tuned queries and suspended unused warehouses

Result: 30% faster dashboards and 40% cost savings in 1 month.

📅 Avoid These Mistakes in Your Warehouse Project

We’ll help you audit, fix, or launch your data warehouse with best practices.

👉 Book a warehouse health check
Or email: hi@essidsolutions.com