Bellabeat Data Analysis: Leveraging R for Insightful Exploration
In this project undertaken as part of the Google Data Analytics Specialization, I applied data analysis techniques using the R programming language, specifically leveraging tidyverse and ggplot2 packages. The case study involved working on real-world tasks as data analyst for the fictional company, Bellabeat, a manufacturer of high-tech health products for women. Following the steps of the data analysis process, I addressed key questions posed by the company, emphasizing the importance of asking, preparing, processing, analyzing, sharing, and acting on data.
As a junior data analyst in Bellabeat's marketing analytics team, I focused on a specific product to analyze smart device usage data. The data exploration aimed to uncover insights that could guide the company's marketing strategy. The case study provided a tangible project for my portfolio, showcasing my ability to tackle real-world data challenges and deliver actionable insights. Throughout the analysis, I delved into the personas and products involved, providing context to the data-driven decision-making process within the dynamic setting of Bellabeat.
The project showcased my adeptness in utilizing R programming, along with proficiency in the tidyverse and ggplot2, to conduct comprehensive data analysis and visualization. By presenting my findings to Bellabeat's executive team along with high-level marketing strategy recommendations, I demonstrated my ability to contribute to data-driven decision-making processes.
The dataset utilized for this case study is the FitBit Fitness Tracker Data, which was generated by respondents to a distributed survey via Amazon Mechanical Turk between December 3rd and December 5th, 2016. The dataset contains minute, hourly, and daily information of steps taken, intensity, calories burned, and sleep time.
The code for this case study can be found in my Kaggle profile.
Skills & Tools
Exploratory Data Analysis, Data Visualization, Statistics, R, tidyverse, ggplot2, RMarkdown