Prompt
I'm building a customer analytics platform and need centralized reporting storage; what should I use?
Latest observation
For centralized reporting storage in a customer analytics platform, the best default choice is usually a data warehouse.
Recommended options
- Data warehouse: Best for BI/reporting, dashboards, SQL analytics, and centralized governed data.
- Examples: Snowflake, BigQuery, Amazon Redshift, Azure Synapse
- Data lake + warehouse/lakehouse: Best if you also need raw event storage, flexible schema, ML, and cost-efficient retention.
- Examples: Databricks Lakehouse, BigQuery + GCS, Snowflake + stages, Delta Lake
What to use in practice
If your main goal is centralized reporting, choose:
- Snowflake if you want strong ease of use, separation of compute/storage, and broad analytics support.
- BigQuery if you're on Google Cloud and want serverless scaling.
- Redshift if you're heavily on AWS and want tighter ecosystem integration.
Typical architecture
- Ingest customer events/data from app, CRM, support, billing
- Store raw data in object storage or a lake
- Transform/clean into modeled tables
- Load curated data into a warehouse
- Expose semantic/reporting layers for dashboards and business users
Key requirements to look for
- Fast SQL querying
- Role-based access control
- Column-level / row-level security
- Audit logs
- Data modeling support
- Good BI tool integration
- Scalability and cost controls
If you want, I can recommend the best warehouse for your cloud stack and budget or sketch a reference architecture for customer analytics.
Observation history
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