https://github.com/lisashei/analytics_pet-projects
Data analysis and visualization projects
https://github.com/lisashei/analytics_pet-projects
analytics business-analytics data-analysis data-visualization powerbi product-analytics python r sql tableau
Last synced: 9 months ago
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Data analysis and visualization projects
- Host: GitHub
- URL: https://github.com/lisashei/analytics_pet-projects
- Owner: lisashei
- Created: 2025-09-24T14:47:28.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-09-24T17:00:14.000Z (9 months ago)
- Last Synced: 2025-09-24T17:23:28.637Z (9 months ago)
- Topics: analytics, business-analytics, data-analysis, data-visualization, powerbi, product-analytics, python, r, sql, tableau
- Language: Jupyter Notebook
- Homepage:
- Size: 4.7 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Analytics Pet-projects
This repository contains data analysis and visualization projects using Python, R, SQL, Tableau, and Power BI.
## Projects
### [Power BI Company Performance](https://github.com/lisashei/analytics_pet-projects/tree/main/Power%20BI%20Company%20Performance)
This dashboard provides an overview of company performance by tracking key metrics like gross profit, sales, and quantity. It enables detailed analysis of trends, identifies underperforming regions and products, and offers client segmentation to guide strategic decisions for improving profitability.
**Tools**: Power BI
### [Power BI Sales and Customer](https://github.com/lisashei/analytics_pet-projects/tree/main/Power%20BI%20Sales%20and%20Customer)
This project consists of two complementary dashboards that analyze sales performance and customer behavior to drive business strategy. The Sales Report tracks regional and product performance, while the Customer Report provides insights into demographics and purchasing patterns to enable targeted marketing.
**Tools**: Power BI
### [Tableau HBO Movies and Shows](https://github.com/lisashei/analytics_pet-projects/tree/main/Tableau%20HBO%20Movies%20and%20Shows)
This dashboard analyzes HBO's content library by providing insights into release trends, genre popularity, and production patterns across movies and shows.
**Tools**: Tableau
### [Tableau Product Sales](https://github.com/lisashei/analytics_pet-projects/tree/main/Tableau%20Product%20Sales)
This dashboard provides an analysis of product sales performance by tracking key metrics, profit trends, and product categorization to identify profit drivers and optimize product strategy.
**Tools**: Tableau
### [Python Customer Analysis](https://github.com/lisashei/analytics_pet-projects/tree/main/Python%20Customer%20Analysis)
This customer analysis project employs statistical testing to uncover key behavioral patterns, spending patterns, and payment preferences across different customer segments. It provides data-driven recommendations for optimizing customer retention strategies, discount campaigns, and payment system improvements to enhance business performance.
**Tools**: Python (numpy, pandas, matplotlib, seaborn, scipy)
### [Python HBO Analysis](https://github.com/lisashei/analytics_pet-projects/tree/main/Python%20HBO%20Analysis)
This statistical analysis uses regression modeling to identify key factors influencing IMDB ratings for HBO's movies and shows, providing insights for content strategy and rating prediction.
**Tools**: Python (numpy, pandas, matplotlib, seaborn, scipy, statsmodels, sklearn)
### [SQL Customer Report](https://github.com/lisashei/analytics_pet-projects/tree/main/SQL%20Customer%20Report)
This customer report analyzes purchasing behavior, segments customers into categories, and calculates performance metrics. It serves as a foundation for predictive modeling to improve customer retention and engagement.
**Tools**: SQL Server Management Studio
### [SQL Window Functions](https://github.com/lisashei/analytics_pet-projects/tree/main/SQL%20Window%20Functions)
This project utilizes advanced window functions to analyze sales trends and product performance through cumulative totals, moving averages, yearly sales comparisons, and product rankings.
**Tools**: SQL Server Management Studio
### [R City Recommendation App](https://github.com/lisashei/analytics_pet-projects/tree/main/R%20City%20Recommendation%20App)
This application provides personalized European city recommendations by clustering destinations based on similarity features and matching them to users' budget constraints and travel preferences. It helps travelers discover optimal destinations through intelligent filtering, while suggesting alternative cities from the same cluster to expand their options.
**Tools**: R (dplyr, shiny, caret)