Case study 05 / 06
Bravo Sierra
CPG · Personal care
Every data source, one dashboard
- Data engineering
- Software engineering
- Cloud & infrastructure
Key figures
- Warehouse for DTC, wholesale and ad data
- 1
- Source platforms DataSync connects
- 19
The brief
The challenge
KPIs compiled by hand from disparate vendor dashboards across DTC, wholesale, and advertising.
What we built
A centralized data layer: DTC, wholesale and advertising data brought into one BigQuery warehouse behind Looker Studio dashboards shaped around how the business actually runs. Its scheduled syncs now run on DataSync, DataGem's ingestion platform.
Outcome
One place for the KPIs the team used to compile by hand, shaped around how the business runs.
Related services: Data collection and analysisCloud infrastructure
Expertise
What it took.
Data engineering
- Connectors for DTC and advertising platforms, landing each source in BigQuery for the dashboards; incremental tables can be staged and merged into history by key.
- Asynchronous report orchestration, automatic OAuth token refresh (with expiry alerts where a token must be renewed by hand) and back-off on the most rate-limited APIs.
- Backfills over any date window, one table at a time, launched from the console.
Software engineering
- Bravo Sierra's syncs now run on DataSync, DataGem's ingestion platform: a Flask API with JWT and OIDC, and an AES-encrypted credential vault.
- A React ops console to launch backfills and follow each run's live logs.
Cloud & infrastructure
- Once onboarded, each client's syncs run as Cloud Run Job executions in its own GCP project, so compute is isolated and billed to the client.
- Per-connector Cloud Scheduler crons over OIDC, and one container image rolled out to every client project.
Project 01
Centralized data platform
Python · BigQuery · Looker Studio · DataSync
DataGem brought the DTC, wholesale and advertising data the team used to compile by hand into one place: a BigQuery warehouse behind Looker Studio dashboards shaped around how the business runs. Python connectors handle authentication, pagination and asynchronous ad reports, and now run on DataSync, DataGem's ingestion platform.
- Goal
- Stop compiling KPIs by hand: one warehouse, refreshed on a schedule.
- Highlights
- DTC, wholesale and advertising data in one place
- Looker Studio dashboards shaped around how the business runs
- Scheduled refresh with live run logs and cancellation
- Stack
- Python
- BigQuery
- Looker Studio
- DataSync
- Cloud Run Jobs
Pierre and his team were a delight to work with. Before working with them, we were relying on a bunch of disparate analytics dashboard from different vendors and sources to compile our business KPIs and metrics. Pierre was able to create a simple interface, centralizing and aggregating all our data sources (DTC, wholesale, advertising, etc) in a way that makes sense for our specific business and needs. The project was seamless and efficient. Great people, great work!