You will get E-Commerce Analytics Pipeline: ETL, ML Predictions & Live Dashboard
Project details
Are you losing customers without knowing why? I build end-to-end
data pipelines that turn raw business data into actionable insights.
Deliverables include: automated ETL pipeline, PostgreSQL data warehouse
with 1.6M+ records, 30+ engineered features, a RandomForest ML model
(AUC-ROC 0.74) that predicts bad customer experiences before they happen,
and a live Grafana dashboard with revenue trends, delivery KPIs, and
product performance — all production-ready on your infrastructure.
Stack: Python, PostgreSQL, Scikit-learn, Grafana. No cloud fees required.
data pipelines that turn raw business data into actionable insights.
Deliverables include: automated ETL pipeline, PostgreSQL data warehouse
with 1.6M+ records, 30+ engineered features, a RandomForest ML model
(AUC-ROC 0.74) that predicts bad customer experiences before they happen,
and a live Grafana dashboard with revenue trends, delivery KPIs, and
product performance — all production-ready on your infrastructure.
Stack: Python, PostgreSQL, Scikit-learn, Grafana. No cloud fees required.
Machine Learning Tools
Apache Spark, Google Data Studio, MLflow, NumPy, pandas, Python, Python Scikit-Learn, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$200
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 4 | 8 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Graph/Chart
(+ 1 Day)
+$25
Model Validation/Testing
(+ 3 Days)
+$75
Model Documentation
(+ 2 Days)
+$50
Data Source Connectivity
(+ 3 Days)
+$100Frequently asked questions
About Douglas
SQL Analyst and Dashboard Developer in Looker Studio PostgreSQL
Barquisimeto, Venezuela - 1:36 pm local time
I specialize in building production-ready data systems: automated ETL pipelines, PostgreSQL and BigQuery data warehouses, RandomForest ML models, and real-time dashboards in Looker Studio and Grafana. My stack: Python, SQL, Scikit-learn, BigQuery, Docker, and Linux.
Currently working in BI and Analytics at a casino tech company, where I built automated BigQuery pipelines processing millions of daily transactions and a fraud monitoring dashboard used by the operations team.
Projects I have shipped: an e-commerce analytics pipeline on a 100K+ order dataset with a RandomForest model reaching AUC 0.74, and a real-time token intelligence platform ingesting live blockchain data via WebSocket with PostgreSQL and Grafana.
If you need clean data, reliable pipelines, and dashboards that actually drive decisions — let's talk.
Steps for completing your project
After purchasing the project, send requirements so Douglas can start the project.
Delivery time starts when Douglas receives requirements from you.
Douglas works on your project following the steps below.
Revisions may occur after the delivery date.
Kick-off call
We align on your data sources, business goals, key metrics and delivery format.
ETL pipeline
Raw data is extracted, cleaned and loaded into a PostgreSQL database. You receive a progress update.