Analysis of Financial Data Descriptions about Investment and the Stock Market Based on Gender and Age Attributes

The recent surge in data science or analytics in finance is crucial for informed decision-making in financial operations. Its integration is instrumental in helping businesses mitigate operational risks, identifying and preventing potential threats such as system failures and lapses. The study methodology involves case investigations and tests utilizing K-Means, K-Nearest Neighbors (KNN), and Decision Tree algorithms. Data visualization, using various graphical representations like graphs, diagrams, maps, and other techniques, is essential to simplify data interpretation and foster intuitive analysis. Common forms include heat maps, scatter plots, pie charts, bar graphs, line graphs, and maps, contributing significantly to presenting data comprehensively, offering insightful analyses, and achieving research objectives..