A small and interesting project, combining techniques as Data Cleaning, Data Transformation, Statistical Analysis and simple Machine Learning models. Exploring the world of movies and how can producers look into data to make sure their new creation will become a success.
In this project, I utilized SQL Server to efficiently merge multiple CSV files into a structured database table, ensuring data integrity and consistency. Using SQL queries, I transformed the raw data by creating new calculated columns to enhance its usability for analysis. Once the data was properly structured, I transitioned to Python, leveraging libraries like Pandas and Scikit-learn to perform statistical analysis and implement machine learning algorithms for predictive insights. Finally, I used Power BI to design an interactive dashboard, providing a clear visualization of key patterns and trends, enabling data-driven decision-making.
For this project, instead of using a pre-existing dataset, I opted to design and implement a custom database using SQL Server. The objective is to develop a comprehensive database for a technology business that manufactures and sells products composed of multiple components, while also managing key operational areas such as inventory and workforce.
The final phase of the project involves visualizing the dataset through multiple Power BI dashboards, with each dashboard providing insights into different aspects of the business, including sales, inventory management, and staffing. This approach ensures a data-driven decision-making process and a structured analytical framework for business operations.
This project is not yet uploaded. Stay tunned!