Data-Driven Decision Making: Exploring Housing Data with RapidMiner and Tableau

This report explores the use of data-driven decision making in the context of housing data analysis. It utilizes RapidMiner for exploratory data analysis (EDA) and linear regression modeling, and Tableau for graphical visualization. The report examines the relationship between various housing attributes, including households, total bedrooms, latitude, median house values, and ocean proximity. It also investigates the impact of organizational culture on the adoption of data-driven decision making practices.