Walmart's Weekly Sales Analysis Part 3:
Spike Analysis and Store Segmentation

For large retail organizations like Walmart, there are periods where weekly sales can experience dramatic increases. This analysis adopted machine learning techniques to observe sales spikes and carry out store segmentation.

Credit Risk Modelling and Business Implications:
A Case Study of American Express

Financial institutions have developed various strategies to address customers' behavioural differences to ensure timely and appropriate loan recovery. This case study applies predictive modeling methods to American Express (Amex) credit card data to evaluate their effectiveness in managing credit risk.

Sales in the era of ceaseless preference:
ABC Ltd Export Sales Report

A comprehensive analysis of ABC Ltd.'s export sales data from 2019 to 2022 using Python. This analysis covered several stages, including data preprocessing to ensure accuracy and consistency, exploratory data analysis to uncover underlying patterns and trends, and statistical analysis to evaluate key metrics. The culmination of this analysis was a detailed report presenting actionable recommendations to optimise sales strategies and foster business growth for ABC Ltd.

Integrating Random Forest and SARIMA Models
for Future Export Sales Forecasting: A
Machine Learning Ensemble Approach

This analysis predicts the projected performance of ABC Ltd's export sales relative to total sales over the next 38 months. By employing a machine learning ensemble approach, valuable insights are extracted and the accuracy of forecasts is improved, thereby assisting ABC Ltd in making informed decisions and optimizing their export sales strategies.

Walmart’s Weekly Sales Analysis Part 2:
Statistical Analysis with Python

This analysis looks into the numerical variables in the dataset to address questions such as the adequacy of featured variables for predicting future sales, the significance of independent variables on weekly sales, and identifying the best predictive models.