Unified Retail Metrics & APIs
Merchandising, stores, and finance often answered the same questions—how much sold, what was on hand, what margin looked like—with slightly different numbers. Teams queried the Snowflake warehouse directly with overlapping SQL, which drove up cost and meant a small schema change could break many reports at once.
Business impact at a glance.
More than 120 analysts and app teams consumed metrics through contracts instead of raw warehouse SQL.
Snowflake compute attributed to duplicate ad-hoc exploration dropped by 28% over two quarters.
Executive metric debates caused by definition mismatch decreased sharply in steering meetings.
Mean time to restore broken dashboards fell when incidents were isolated to contract versions.
Security review signed off on field handling for employee and loyalty identifiers.
Business Challenge
- Leadership reviews were undermined when two teams presented the “same” KPI with different definitions.
- Many analysts re-created the same joins and extracts, inflating warehouse spend.
- Shared tables changed without a clear version or retirement path for consumers.
- Excel, BI tools, and internal apps needed stable, documented outputs—not ad hoc database access.
- Store and employee data required consistent redaction and access rules.
Our Approach
We worked with the client’s data engineering team to publish trusted, tested datasets (using dbt for documentation and quality checks). On top of those datasets we shipped versioned read APIs and CSV exports with FastAPI, scoped API keys by business domain, and explicit API versions when definitions changed. Finance helped lock canonical KPI meanings. We added caching for the busiest endpoints so seasonal reporting stayed responsive and affordable.
Phase 01
Discovery & alignment
Workshops, process and systems review, success metrics.
Phase 02
Design & planning
Architecture, experience and workflow design, delivery plan.
Phase 03
Build & validation
Implementation, integration, testing, demos, refinements.
Phase 04
Go-live & enablement
Controlled rollout, training, handover, post-launch tuning.
What We Delivered
- Published dbt-documented “gold” datasets for sales, inventory, and margin.
- Implemented FastAPI services with OpenAPI, rate limits, and structured error responses.
- Centralized row- and column-level security patterns for store and employee attributes.
- Built lightweight admin tooling to rotate keys and map consumers to allowed datasets.
- Added integration tests that fail CI when contract schemas drift from dbt outputs.
- Delivered analyst onboarding guides and example notebooks against the stable APIs.
Technology Stack
Everyone finally argues about strategy, not about whether two reports use the same definition of margin.
Director of Data & Analytics
Retail
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