🗄️
Engineering
Microsoft SQL Server, PostgreSQL
Relational databases, indexing, partitioning, stored procedures.
T-SQL
query optimization
pgAdmin
available for projects
Mauro Morales
BI Developer & Data Specialist
I turn data into decisions with modern pipelines, BI dashboards, and programmatic analysis.
Explore my portfolio projects built with public datasetsmy data ecosystem
The Stack
⚙️
Integration
Alteryx, Docker, Python
Workflow automation, containerized pipelines, data transformation scripts.
Alteryx Designer
Docker Compose
pandas
requests
📊
Visualization
Power BI, Apache Superset
Interactive dashboards, row-level security, embedded analytics.
DAX
Power Query
SQL Lab
RBAC
🐍
Exploration
pandas, matplotlib, numpy
Data cleaning, statistical analysis, custom plots, and notebooks.
DataFrames
visualization
linear algebra
Jupyter
Data Modeling
ETL Design
Data Warehousing
Git
Version Control
case studies
Portfolio Projects
Personal projects using public data to showcase data analytics & BI skills.
Predictive Analytics
Python · SQL · Power BICustomer Churn Analysis
Context
Personal project using a public telecom customer dataset (IBM Telco Churn). Goal: identify churn drivers and build a predictive model.
Tools Used
Microsoft SQL Server (data exploration), Python / pandas / matplotlib (EDA & logistic regression), Power BI (interactive dashboard).
Process
Cleaned and transformed 7,000+ records, created churn risk segments, and built a classifier with 82% recall.
Simulated Business Impact
In a real scenario, this approach could reduce churn by 10–15%, saving an estimated $200K+ annually for a mid-sized company.
SQL Server
Python
Power BI
View code
Churn by Contract Type
43%
Month-to-
month
month
11%
1-year
3%
2-year
Actual vs Forecast
Actual
Forecast
Forecasting & Optimization
ETL · Forecasting · SupersetSales Forecasting & Inventory Optimization
Context
Personal project using a public retail dataset (Superstore Sales, 4 years). Goal: forecast monthly sales by category and recommend inventory levels.
Tools Used
PostgreSQL (data warehouse), Alteryx (ETL workflow), Docker (containerized pipeline), Python / numpy / matplotlib (forecast with Prophet), Apache Superset (dashboard).
Process
Built a repeatable ETL pipeline, compared ARIMA vs Prophet, and achieved a MAPE of 12% on holdout data.
Simulated Business Impact
Improved forecast accuracy could reduce overstock by 18% and stockouts by 22% in a typical retail setting.
PostgreSQL
Alteryx
Docker
Python
Superset
View code
BI & Cost Control
Data Warehouse · Alteryx · Power BIReal-time Cost Monitoring Dashboard
Context
Personal project simulating a multi-department company's operational costs. Goal: build an automated dashboard with anomaly detection.
Tools Used
PostgreSQL, Alteryx, Docker, Power BI (DAX, row-level security), Git.
Process
Designed a star schema data warehouse, automated cost ingestion with Alteryx, and created alerts for budget deviations >10%.
Simulated Business Impact
In a real scenario, this dashboard would enable 15–20% cost reduction through early anomaly detection.
PostgreSQL
Alteryx
Docker
Power BI
Git
View code
Cost by Department (Actual vs Budget)
Budget
Actual
Let's work together?
Have data waiting to become decisions? Let's talk about your next project.
mauro@mauromorales.tech