Part 2

This analysis explores which NOAA‐recorded weather event types have historically caused the most fatalities and injuries, and which have produced the greatest property/crop damage costs.

This project performs an in-depth clustering analysis on the Wholesale Customers Dataset using R. The objective is to segment wholesale clients based on their annual spending on product categories such as fresh products, milk, grocery, frozen foods, detergents, and delicatessen. The analysis includes data preprocessing and normalization, exploratory data analysis with visual insights, hierarchical clustering to identify natural customer groupings, dimensionality reduction using Principal Component Analysis (PCA) and interpretation of clusters from a business perspective. The findings reveal distinct client profiles, such as high-spending businesses and product-specific buyers, which can be leveraged for targeted marketing, personalized service strategies, and optimized sales efforts.

A spatial analysis of high-tech firm clustering in Warsaw, comparing 2012 and 2021. Sectoral differences and proximity to the business core areas are explored using Poisson point process models.

Pengunaan 7 QC Tools yang disajikan dengan flexdashboards

Preliminary Data Exploration