About Me

Hello! As a graduate of the Google Data Analytics Certificate program, I have experience guiding data through every step of the analysis process, from cleaning to analysis to visualization. I’m proficient in SQL, Microsoft Excel/Google Sheets, and Tableau, and I’m continually developing my skills in Python.

My undergraduate degree in Psychology and Music also provided many opportunities for me to exercise my analytical muscles, from carrying out my own quantitative research study to finding patterns within the music I performed.

Of course, there’s more to data analysis than statistics and spreadsheets. Numbers and figures are minimally helpful without someone to interpret them and use them to take action. To that end, I am adept at communicating complex concepts in a way that’s easy for others to understand, whether that’s presenting research findings to a broad audience or distilling technical details into plain English for the rest of my team.

I am also persistent in translating the insights I glean from my analyses into concrete action, striving to help my team streamline processes, work more effectively, and continue growing to be the best version of ourselves.

Bianca Aspin

Google Data Analytics Capstone Project:
How Does a Bike-Share Company Navigate Speedy Success?

In this scenario, I was a data analyst working for the marketing analysis team at Cyclistic, a fictional bike-share company based in Chicago. Cyclistic identified an opportunity to increase profits and grow as a company by maximizing its annual membership numbers. To help them realize this opportunity, I analyzed 2021 usage data from Divvy (a similar real-life company) to explore how casual riders and annual members differed in their use of the company’s bike-sharing services.

Project Summary

I used Microsoft Excel, PostgreSQL, and Tableau to process and analyze the anonymized trip data to compare which stations members and casual riders visited, when they started trips, and how long those trips lasted. The results indicated that casual riders preferred different stations from members, that casual ridership surpassed that of members during the summer months and on weekends throughout the whole year, and that casual riders tended to take longer trips than members.

These findings led me to recommend that Cyclistic’s marketing team time its next membership drive strategically to get casual riders' attention when they use its services the most (during the summer months) and include messaging emphasizing the flexibility of membership with longer ride lengths. I also recommended that this campaign target in-person marketing efforts at casual riders’ most popular stations on weekends and afternoons.

Additionally, I encouraged Cyclistic to conduct additional research into the viability of creating a separate, weekends-only membership tier that might appeal more to current casual riders than the existing annual membership.