JMC

Introduction

Transaction records for Maven Roasters, a fictitious coffee shop operating out of three NYC locations. Dataset includes the transaction date, timestamp and location, along with product-level details.

Recommended Analysis:

1. How have Maven Roasters sales trended over time?
2. Which days of the week tend to be busiest, and why do you think that's the case?
3. Which products are sold most and least often? Which drive the most revenue for the business?

Data Dictionary:

• transaction_id : Unique sequential ID representing an individual transaction
• transaction_date : Date of the transaction (MM/DD/YY)
• transaction_time : Timestamp of the transaction (HH:MM:SS)
• transaction_qty : Quantity of items sold
• store_id : Unique ID of the coffee shop where the transaction took place
• store_location : Location of the coffee shop where the transaction took place
• product_id : Unique ID of the product sold
• unit_price : Retail price of the product sold
• product_category : Description of the product category
• product_type : Description of the product type
• product_detail : Description of the product detail

Dashboard

Note: For better experience, open the dashboard in fullscreen.

Analysis:

1. How have Maven Roasters sales trended over time?
• There was an increase in sales from January to June although there was a drop in sales on February.
2. Which days of the week tend to be busiest, and why do you think that's the case?
• Weekdays were the busiest days of the week because people would buy coffee before going to work.
3. Which products are sold most and least often? Which drive the most revenue for the business?
• According to the list of products displayed on the table, Barista Espresso is the most sold product and Green beans is the least sold product.