Business Analytics Case Study: Boston Housing Data Analysis Report

This report presents a business analysis of the Boston Housing dataset, focusing on data mining techniques to solve real estate business problems. The analysis begins with understanding the dataset, including its attributes and their significance. The report then explores the relationships between features using the Weka machine learning tool, employing preprocessing steps like data selection, sorting, and normalization. The core of the analysis involves applying Association Rule Mining to identify patterns and trends within the data. The Apriori algorithm is utilized to generate rules, with a focus on identifying the best rules for improving business processes, decision-making, and achieving business benefits. The report concludes by summarizing the applied methodologies and the key findings, which offer insights for the real estate consulting firm. The analysis successfully addresses the business problem by applying the evaluation process on the real estate housing datasets.