Unit 6 - Team Project: Airbnb business analysis using a data science approach

This unit focused on analyzing Airbnb’s NYC dataset to address a business question, applying data science techniques, and preparing an analytical report. The project was completed as part of a collaborative team effort, emphasizing technical skills, critical thinking, and professional communication.

Team Dynamics

• The team displayed strong communication and collaboration, facilitated by a WhatsApp group for seamless coordination.
• Each member contributed meaningfully, with one member proactively completing significant portions of the report based on team input, which streamlined the final submission process.
• I took the initiative to create the WhatsApp group for better communication and ensured all team members were actively involved in discussions and task updates.
• My role included critically analyzing the data preprocessing and contributing ideas for the exploratory data analysis (EDA), ensuring that the findings addressed the posed business question effectively.

Learning Outcomes

1. Applicability of Machine Learning and Data Science

• Explored the challenges and opportunities presented by real-world datasets, such as handling missing data, identifying relevant features, and choosing the right analysis methods.
• Addressed a business-relevant question using exploratory data analysis (EDA) and unsupervised machine learning techniques (e.g., clustering).

2. Teamwork and Collaboration in a Professional Setting

• Demonstrated effective teamwork by setting clear goals, dividing responsibilities, and maintaining active communication.
• I actively participated in brainstorming sessions, helping the team refine the business question and methodology.
• Reflected on the importance of pre-assigning tasks and setting clear deadlines for improved efficiency in future collaborations.

Key Artefacts

• Business Question: Investigated how booking patterns vary across NYC neighborhoods and factors influencing them.
• Methodology: Conducted EDA, data cleaning, and clustering to derive actionable insights. Visualized results through compelling charts.
• Analytical Report: Delivered a concise 1,000-word report highlighting the analysis, insights, and recommendations for Airbnb, complemented by an appendix with Python code.
• My Contribution: Played a key role in ensuring high-quality data preprocessing and contributed to creating visualizations that effectively communicated key findings.

Self-Reflection

• Strengths: Strong communication and critical thinking ensured cohesive team efforts.
• Improvement Areas: Improved time management and task scheduling for future projects.