Templates

dbt + BigQuery Starter for Retail Sales Forecasting
A production-shaped dbt project on BigQuery that turns raw Corporación Favorita grocery data into clean, tested, forecast-ready models. Clone it, point it at your warehouse, and you have a working analytics-engineering layer in an afternoon.
Time to Implement:
4 - 8 Weeks
dbt
BigQuery
Vertex
MLflow
Prefect
XG-Boost
Optuna

Favorita: dbt + Prefect Orchestration
Wrap the Favorita dbt project in a Prefect flow so your transformations run on a schedule, retry on failure, and tell you when something breaks — instead of someone running dbt by hand and hoping.
Time to Implement:
One to two days

Favorita: Vertex AI for ML
Take the forecast-ready Favorita tables and train, evaluate, and serve a sales-forecasting model on Google Vertex AI — a managed path from clean data to predictions you can actually call from production.
Time to Implement:
Two to four weeks
Favorita: XGBoost Train & Predict
A focused XGBoost pipeline for forecasting Favorita grocery sales — feature engineering, training with cross-validation, and prediction. The fast, interpretable baseline every forecasting project should start with.
Time to Implement:
Three to five days