Created Using MsEXCEL

This project uses data-driven insights to optimize business operations and customer experiences at our coffee shop. Using various analytical tools, we'll uncover trends in sales, popular products, peak times, and customer behavior.

• Increase Sales: Identify high-selling products, effective promotions, and optimal pricing strategies.
• Improve Customer Experience: Understand customer preferences, buying patterns, and peak traffic times for better staffing and inventory management.
• Enhance Marketing: Target marketing campaigns based on customer demographics and product popularity.
• Optimize Operations: Identify potential areas to streamline processes and reduce costs.

• Sales Transactions: Includes product details (type, size, roast), purchase date/time, price, customer ID.
• Customer Demographics: Optional data like age, gender, location.
• Inventory Records: Tracks stock levels and popular items.
• Social Media Data: Sentiment analysis of social media mentions and reviews for qualitative insights.

• MsExcel: Data cleaning, manipulation, and analysis.
• PowerQuery Editor: Database querying and data management.
• Excel/Google Sheets: Data manipulation and additional analysis if needed.
• Excel Power Pivot: Data visualization and interactive dashboard creation.

• Sales Trends: Daily, weekly, monthly, and seasonal fluctuations.
• Product Popularity: Best-selling coffee types, sizes, roasts, and other items.
• Customer Behavior: Purchase frequency, average order value, peak traffic hours.
• Geographic Analysis: Sales distribution by location (if customer data is available).

• data/: Contains raw data files (.csv, .xlsx, .json, etc.)
• scripts/: Contains Python scripts for data cleaning, analysis, and modeling.
• notebooks/: Jupyter Notebooks or similar for exploratory analysis.
• visualizations/: Stores charts, graphs, and visualizations.
• dashboard.twb (Tableau) or dashboard.pbix (Power BI): Interactive dashboard file.

1. Data Collection: Ensure necessary data is collected and stored in the 'data' folder.
2. Environment Setup: Install required MsExcel Version.
3. Exploratory Analysis: Load data into a Excel Tables and begin exploring trends.
4. Data Cleaning: Address missing values, inconsistencies, and outliers.
5. Data Analysis and Modeling: Perform in-depth analysis to answer key business questions.
6. Visualizations: Create compelling visualizations to clearly communicate findings.
7. Dashboard Development: Design an interactive dashboard in MsExcel using Charts.

For questions or collaboration: [[email protected] ]

Let's get brewing with data! ☕️