Background: Our project is centered around a pizza establishment that seeks to deepen its understanding of key performance indicators (KPIs) related to pizza sales. 

Objective: By analyzing sales data, we aim to unveil patterns and trends that will inform strategic decisions, optimize operations, and enhance customer satisfaction. This final product will be an interactive dashboard for our client

Challenge:

1. Mastery of DAX for Data Modeling

• Transitioning from Python to using Data Analysis Expressions (DAX) in Power BI for data modeling and analysis presents a learning curve. The challenge lies in achieving comfort and proficiency with DAX to create complex measures, calculated columns, and data transformations that are crucial for insightful analysis within the dashboard.

2.  Balancing Functionality with Aesthetic Appeal

• Designing the dashboard to be both informative and visually engaging is essential. The challenge involves using colors strategically to highlight key information and improve understanding, without compromising the dashboard’s clarity and usability. This requires a thoughtful approach to visual design principles, ensuring that the use of color enhances data presentation and user experience.

This is the data set: Here 

Jupiter file with SQL code for validation: Here 

1. Daily Trend for Total Orders: This chart will help us identify any patterns or fluctuations in order volumes on a daily basis.

2. Monthly Trend for Total Orders: This chart will allow us to identify peak hours or periods of high order activity on a monthly basis.

3. Percentage of Sales by Pizza Category: This chart will provide insights into the popularity of various pizza categories and their contribution to overall sales.

4. Percentage of Sales by Pizza Size: This chart will help us understand customer preferences for pizza sizes and their impact on sales.

5. Total Pizzas Sold by Pizza Category: This chart will allow us to compare the sales performance of different pizza categories.

1. Top 5 Best Sellers by Revenue, Total Quantity and Total Orders

2. Bottom 5 Worst Sellers by Revenue, Total Quantity and Total Orders