Adeel Nasir's Projects
Analyze NCDC weather records to compute sky ceiling height range and average visibility distance, aggregating data by USAF weather station ID using Hadoop, PySpark, Pig, and Hive.
This project entails the development and implementation of a comprehensive business plan for a cosmetics company, Darma Glow Cosmetics. It focuses on producing gluten-free and organic makeup to cater to individuals with allergies, with an emphasis on quality, transparency, and consumer education.
The objective of this code and project is to analyze Bay Area real estate data using Python. The goal is to clean, visualize, and analyze the data to gain insights into property prices and trends.
To integrate data from "Orderline.csv" and "Product.csv" using Talend, filtering based on price, and performing inner and left joins to extract insights and facilitate data warehousing integration with Microsoft SQL Server.
Clustering Analysis for Targeted Marketing Campaigns: Insights from Customer Segmentation and Spending Patterns
Employed statistical analysis, forecasting, clustering, and control chart techniques to extract insights and monitor data variation effectively, showcasing Tableau's advanced capabilities for informed decision-making.
This project investigates ChatGPT adoption among CSU East Bay postgraduates, exploring usage patterns and future aspirations through surveys and interviews. The team's commitment ensures collaborative efforts for timely project completion.
The goal of this competition is to use various factors to predict obesity risk in individuals, which is related to cardiovascular disease.
The objective was to optimize the profit of Derma Glow's facial product line through strategic pricing decisions using non-linear programming and demand analysis.
This project focuses on Cognizant Technology Solutions, analyzing the importance of HRM within the company and conducting statistical tests to benefit organizational strategies and employee management.
The objective is to forecast Procter & Gamble's stock performance using time series analysis to provide valuable insights for investors and stakeholders.