📉 SQL + Tableau: Covid Data and Dashboard
🚲 R + Tableau: Cyclistic Bike Share Analysis
🏊♀️ R + Tableau: Bellabeat Fitness Data Analysis
📈 R: Regression Models and Data Transformation
- Analyze 12 months of Divvy data to see how we can convert casual riders into annual members.
- Use tidyverse to wrangle data, dplyr to clean data, lubridate to wrangle date attributes, ggplot2 to visualize data, and readr to save csv for further analysis.
- Built a presentation in Tableau with the marketing analytic team and primary skateholder audiences in mind.
- View the project here ✔
- View the presentation here ✔
- Analyze fitness trend for 30 user data to see how we can help guide marketing strategy for the company.
- Use tidyverse to wrangle data, dplyr to clean data, lubridate to wrangle date attributes, ggplot2 to visualize data, and readr to save csv for further analysis.
- Built a presentation in Tableau with the marketing analytic team and primary skateholder audiences in mind.
- View the project here ✔
- View the presentation here ✔
- Examine the predictor and response variable, and the validity of the regression model.
- Check influential, leverage points and outliers.
- Transform the data to improve the model and build a prediction interval table.
- View the project here ✔
- Analyze and clean covid data from January 2020 to September 2021 in SQL using CTW and Temp Table.
- Built a dashboard in Tableau showing global death percentage, death toll per continent, infection rate per country and infection prediction into 2022.
- View the project here ✔
- View visualization here ✔
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