Bellabeat - Google Data Analytics Capstone Case Study

Table of Contents

• Introduction
• Dataset Overview
• Objective
• Data Analysis Process
• Technologies Used
• Files
• Usage
• Conclusion
• Author
• License

Introduction

This README provides an overview of the Bellabeat Google Data Analytics Capstone Case Study. Bellabeat is a fictional company that designs and manufactures health-focused smart devices for women. They offer a range of products, including activity trackers and wellness-oriented smart jewelry. The case study focuses on analyzing customer data to gain insights into user behavior, preferences, and trends, with the goal of informing Bellabeat's marketing strategy.

Dataset Overview

The dataset used in this case study includes anonymized data from Bellabeat's fitness tracker, called the "FitBit". The dataset contains information about daily activity, sleep patterns, and stress levels recorded by FitBit devices worn by Bellabeat users. It also includes demographic data, such as age, gender, and location. The dataset is provided in the form of a CSV file.

Objective

The objective of this case study is to analyze the Bellabeat user data and provide data-driven recommendations to improve the company's marketing strategy. By understanding user behavior, activity patterns, and preferences, we aim to identify opportunities for product improvement and targeted marketing campaigns.

Data Analysis Process

The data analysis process for this case study involves the following steps:

1. Data Gathering: Collect the FitBit dataset provided by Bellabeat, which includes daily activity, sleep, and stress data, as well as demographic information.
2. Data Cleaning: Clean the dataset by handling missing values, removing duplicates, and addressing any formatting issues or inconsistencies.
3. Data Exploration: Explore the dataset to understand the variables, identify patterns, and uncover insights about user behavior and preferences.
4. Data Analysis: Perform statistical analysis and data visualization techniques to derive meaningful insights from the dataset.
5. Recommendations: Based on the analysis findings, provide data-driven recommendations to Bellabeat, including potential improvements to product features and marketing strategies.

Technologies Used

The following technologies were used in this case study:

• R: R programming language was used for data analysis, cleaning, and visualization.
• RMarkdown: RMarkdown was used as the tool to create dynamic and reproducible reports.
• tidyverse: The tidyverse package, including dplyr and ggplot2, was used for data manipulation and visualization.

Files

The case study includes the following files:

1. README.md: The file you are currently reading, providing an overview of the case study.
2. Data: The dataset folder containing FitBit user data for analysis.
3. docs: A folder that contains the RMarkdown used for analysis.
4. index.Rmd: RMarkdown file containing the R code and analysis for the case study.
5. index.html: The HTML report generated from the RMarkdown file, summarizing the analysis findings and recommendations.

Usage

To run the analysis and explore the case study, follow these steps:

1. Ensure R and RStudio are installed on your system.
2. Clone the repository or download the files to your local machine.
3. Open RStudio and set the working directory to the location of the case study files.
4. Open the index.Rmd file in RStudio to view and run the analysis code.
5. Knit the RMarkdown file to generate the HTML report (index.html) summarizing the analysis findings and recommendations.

Conclusion

Through this case study, we aim to provide valuable insights and recommendations to Bellabeat based on the analysis of user data. By leveraging data-driven strategies, Bellabeat can enhance their product offerings and marketing efforts to better cater to their target audience, ultimately leading to improved customer satisfaction and business growth.

Author

This case study was conducted and documented by Arjit Bhardwaj.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Visit the Bellabeat Case Study for detailed analysis and insights.