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Automatización de Reportes Operativos en Microsoft Excel
Desarrollé una solución en Excel para consolidar información proveniente de múltiples fuentes, reduciendo el tiempo de generación de reportes operativos y minimizando errores manuales.
Responsabilidades:
Depuración y validación de datos.
Creación de tablas dinámicas.
Automatización mediante fórmulas avanzadas.
Generación de indicadores clave.
Herramientas utilizadas:
Microsoft Excel
Power Query
Tablas dinámicas
Fórmulas avanzadas (BUSCARX, SI, SUMAR.SI.CONJUNT)
Resultado:
Reducción del tiempo de elaboración de reportes en un 70%.
Mayor precisión en la información entregada.
Estandarización del proceso de análisis.
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Self-Created Practice Project
I worked on a practice hotel booking dataset where multiple data fields were combined into a single raw-data column.
Work completed:
Separated unstructured data into individual columns using Text to Columns
Organized Booking ID, Guest Name, City, Check-In Date, Check-Out Date, Number of Pax, Amount and Status
Improved the structure and readability of the spreadsheet
Prepared the dataset for easier filtering and further use
Tool: Microsoft Excel
Skills: Data Entry | Data Cleaning | Text to Columns | Data Organization | Spreadsheet Formatting
This is a self-created practice project and not client work
Turn Your Data Into Clear, Useful Insights
Need help organizing messy data or creating professional reports?
I can help with:
. Data Entry & Data Cleaning
. Excel & Google Sheets
. PDF/Image to Excel
. Charts & Graphs
. Dashboards & Reports
. Pivot Tables & Summaries
. Online Data Collection & Research
Accurate data. Clean spreadsheets. Professional visualizations.
DM me to discuss your project or get started!
AutoML Forge is an end-to-end AutoML platform designed to simplify the machine learning workflow by automating key stages from data preparation to model evaluation.
The platform allows users to upload their datasets and build machine learning models without manually handling every step of the traditional ML pipeline.
Key Features
Automated data preprocessing and cleaning
Automatic feature handling and transformation
Classification and regression workflows
Anomaly detection
Model comparison and evaluation
Automated model selection
Hyperparameter optimization
Performance metrics and visualizations
Model prediction and inference
Easy-to-use interactive interface
Tech Stack
Python · PyCaret · FastAI · Scikit-learn · Pandas · NumPy · Streamlit
The project focuses on making machine learning more accessible while reducing repetitive experimentation and development time. It demonstrates practical experience in machine learning automation, model evaluation, data preprocessing, and building AI-powered applications.
Role: AI/ML Developer
Project Type: Machine Learning / AutoML / Data Science
Impressive to see automated data preprocessing and cleaning built into AutoML Forge - eliminating that tedious step speeds up experimentation dramatically. The integrated model comparison and evaluation visualizations make it easy to spot the best performer quickly.