Data Warehousing Solutions
From "The Big Elephant" to "The Cloud Brain": Transforming Raw Data into Strategic Intelligence
The Central Repository for Business Truth
Modern warehousing has moved beyond massive, expensive appliances in basements. Today, we separate Compute from Storage. This allows you to store petabytes of history for pennies in object storage while paying for processing power only when you actually execute a query.
The Modern Shift: From ETL to ELT
Traditional ETL
Extract, Transform, Load. Data was cleaned on a separate server before loading due to high storage costs. This created massive scaling bottlenecks.
Modern ELT
Extract, Load, Transform. Dump raw data into the warehouse immediately. Use the massive SQL power of the warehouse to transform later. Agility is key: Mistakes can be fixed without re-fetching data.
The "Secret Sauce": Separation of Compute & Storage
This is why platforms like Snowflake and BigQuery dominate. By decoupling these layers, you gain infinite flexibility:
- Storage Layer: Sits in cheap S3/Blob storage (~$20/TB).
- Compute Layer: Spin up "Virtual Warehouses" on demand and shut them down when finished.
- Concurrency: Marketing and Data Science teams share data but use separate, dedicated compute resources.
The "Big Three" Technologies
Snowflake
Superpower: Zero-Copy Cloning. Create a 10TB test database in seconds without duplicating actual data. Perfect for cross-cloud agility.
Visit SnowflakeGoogle BigQuery
Superpower: Serverless Scale. No server sizes to choose. Google allocates thousands of slots dynamically for sub-second ad-hoc queries.
Visit BigQueryAmazon Redshift
Superpower: AWS Integration. Deeply linked with S3, Glue, and Kinesis. Best for high-performance workloads within the AWS stack.
Visit RedshiftSchema Design: Star vs. Snowflake
Organization is speed. We specialize in:
- Star Schema: Simplicity and speed for joins between sales facts and dimensions.
- Data Vault: Agile modeling designed for long-term auditability and change tracking.
Data Warehousing Toolkit
| Category | Tool | Usage |
|---|---|---|
| Transformation | dbt (data build tool) | The industry standard for ELT. SQL-based modeling that automatically generates tables. |
| Ingestion | Fivetran / Airbyte | Zero-config pipelines to sync Salesforce, Stripe, and ERP data into the warehouse. |
| Lakehouse | Databricks | Blending SQL Warehouse performance with Data Science Python flexibility. |
Consolidate Your Intelligence
Download our "Modern Data Warehouse Selection Framework" to evaluate your TCO for Snowflake vs. BigQuery.
Download Warehouse Guide (.docx)