The massive influx of data from IoT, social media, and transactional systems has rendered traditional on-premise data warehouses obsolete. Organizations stuck with rigid, legacy appliances are finding themselves unable to keep up with the speed of modern business.
The Case for Cloud Native
Migrating to cloud-native platforms like Snowflake, Databricks, or Google BigQuery is no longer just an option; it's a necessity. These platforms offer separate storage and compute scaling, meaning you only pay for the queries you run, not the idle time.
- Elasticity: Scale up for end-of-month reporting, scale down for the weekend.
- Data Sharing: Seamlessly share live data sets with partners without ETL or copying.
- Zero Management: No more tuning indexes or managing partitions manually.
Migration Strategies
A "lift and shift" approach rarely works well for data warehouses. We advocate for a "lift and modernize" strategy:
1. Audit & Cleanse: Don't move garbage. Use the migration as an opportunity to clean
your data and retire unused tables.
2. Redesign Schema: Move from rigid Star Schemas to more flexible Data Vaults or One
Big Table implementations where appropriate for columnar stores.
3. Automate Pipelines: Replace brittle stored procedures with modern orchestration
tools like Airflow or dbt (data build tool).
Real-world Impact
We recently helped a global logistics firm migrate from an on-prem Oracle warehouse to Snowflake. Query times for their daily operational dashboards dropped from 4 hours to 15 minutes. Moreover, they enabled self-service analytics for their branch managers, a capability that was technically impossible with their old stack.