Supply Chain Analytics using Power BI

The company's supply chain analysis revealed strengths in certain markets and products, but also highlighted areas for improvement in planning, inventory, shipping, and logistics. Recommendations include expanding market reach, optimizing product portfolio, enhancing customer loyalty, and improving operational efficiency. 

Predicting Character Depletion: A Python-Based Analysis 

Based on the analysis, assuming consistent consumption rates, all market segments, except for "Company", are projected to have sufficient inventory for over 100 years. However, Company's reserves are expected to deplete within approximately 15 years.

Veiladati's Supply Chain Challenge: A Tender for Optimal Transportation 

Veiladati, an Italian calcium carbonate company, is expanding into the Middle East. They require a solution to devise the most efficient and cost-effective transportation plan for their equipment and raw materials from various global suppliers to their new facility. After a thorough analysis of various transportation options, the most optimal plan was selected based on factors such as cost, lead time, and route efficiency. 

Investigating Netflix Movies and Guest Stars in The Office

Explore Netflix movie data and perform exploratory data analysis for a production company to uncover insights about movies from a particular decade. 

Analyzing Demand Trends from 2016 to 2019 using Time series techniques - Excel Software

This company examines monthly demand data from 2016 to 2019 to identify patterns, trends, and potential factors influencing demand fluctuations. By analyzing the data, i aimed to gain insights into seasonal variations, growth rates, and outliers that could inform strategic decision-making. 

A Comparative Study of Time Series and AI Models for Predicting High Variance Retail Data

The paper compares time series and AI models for retail sales forecasting. It finds that ANNs outperform time series models for high-variance data. Incorporating product stock and price information further enhances ANN prediction accuracy by 35%. 

Optimizing Production Capacity in a Pharmaceutical Manufacturing Facility  

This case study analyzes the production capacity of a pharmaceutical manufacturing facility to identify potential bottlenecks and areas for improvement. By examining the required number of cartons for each product type and set size, the analysis highlights the need for a more efficient allocation of resources to meet demand and reduce costs. 

LogiLess - Streamlining Logistics Operations  

LogiLess is a project aimed at reducing logistics delays within an organization. By developing a new operating system, the project seeks to optimize workflows, improve efficiency, and enhance overall supply chain performance. 

Optimizing Production for Veiladati  

Develop a profitable production plan for Veiladati's Italian company in 2020, considering demand forecasting, production capacity, and raw material sourcing including annual production plan for product categories A and B, detailed analysis of production capacity and demand alignment, profitability statement demonstrating financial viability, presentation outlining the strategic approach and key findings. 

Research Proposal for Master’s Degree

Sales forecasting is a cornerstone of retail management, influencing decisions at all levels. Given the vast product range and geographic distribution of most retailers, historical sales data often exhibit substantial variability. This variability can undermine confidence in traditional forecasting methods like time series analysis and Artificial Neural Networks. Consequently, identifying optimized techniques tailored to the unique challenges of retail sales forecasting is essential. 

Test the matching of aggregating data with non aggregating data  

The project aims to automate the process of extracting data from an FTP site, saving it to SharePoint and locally, performing a macro operation, and implementing logging and unit testing. It involves pulling .csv files, executing a macro, and generating new files. The script will be configured using YAML files and include unit tests to ensure its reliability.