In my AirBnB 2016 project, I took on the challenge of analyzing a large dataset from the Washington, America area to gain a deeper understanding of the Airbnb market. The goal was to identify key trends and patterns that could inform the strategies of individuals and businesses in the industry.

To accomplish this task, I used a combination of Tableau and Excel to explore and visualize the data. In Tableau, I created an interactive dashboard that allowed me to quickly filter and drill down into different aspects of the data. I was able to see the distribution of bedroom types across different zip codes, analyze the average price of a bedroom, and track the revenue generated over the course of a year. I also used Excel to clean and prepare the data for analysis, ensuring that it was accurate and reliable.

Through my analysis, I discovered a number of key insights that shed light on the Airbnb market in Washington. For example, I found that the most commonly booked bedroom type was a private room, followed by an entire home or apartment. I also identified certain zip codes where the average price of a bedroom was higher than others, indicating potential opportunities for higher earnings.

One of the most valuable aspects of this project was the opportunity to hone my skills in data analysis, visualization, and storytelling. By presenting my findings in a clear and compelling way, I was able to help others better understand the market and make more informed decisions.