The Final Project

Learning Objectives

By completing this final project, students will be able to:

  1. Independent Dataset Selection and Research: Identify, evaluate, and select appropriate datasets from public sources (Kaggle, government databases, etc.) based on licensing, usability, and relevance to personal or professional interests.

  2. Comprehensive Exploratory Data Analysis: Conduct thorough EDA on self-selected datasets, documenting findings, patterns, and insights using Jupyter notebooks with clear analysis narratives.

  3. Data Cleaning and Preprocessing: Apply systematic data cleaning techniques to prepare raw datasets for analysis, handling missing values, duplicates, and data quality issues while documenting all decisions and transformations.

  4. Advanced Data Visualization and Storytelling: Create compelling Tableau stories that effectively communicate data insights through well-designed visualizations, filters, calculations, and narrative captions that guide stakeholder understanding.

  5. Professional Portfolio Development: Produce a complete, professional-quality data analysis project suitable for portfolio presentation, demonstrating the full data analysis lifecycle from business question formulation to actionable insights and recommendations.

The final project is an opportunity to showcase your analysis skills from EDA to visualization and produce a project for your professional portfolio. The project is broken into five checkpoints and a final presentation.

  1. Selecting your business issue and dataset
  2. EDA
  3. Cleaning data
  4. Manipulate, interpret, and visualize data

Examples of final project repositories to help you understand the requirements and complete your own:

  1. Carly’s Final Project: Microbiome Analysis .
  2. Courtney’s Final Project: Dungeons and Dragons Encounter Creator .
  3. Kimberly’s Final Project: Chocolate Bar Analysis .
  4. Sally’s Final Project: Sephora Analysis .