-To analyze customer traffic trends and identify peak hours in order to optimize staffing and improve operational efficiency.
-To identify the average number of pizzas in an order, as well as the top-selling pizzas, in order to inform inventory management and marketing strategies.
-To determine the total revenue generated by pizza sales throughout the year and identify any seasonal trends in order to inform forecasting and budgeting decisions.
-To assess the popularity of various pizzas on the menu and identify any underperforming items or opportunities for promotion in order to optimize the menu and increase sales.
This dataset contains 4 tables in CSV format
-The Orders table contains the date & time that all table orders were placed
-The Order Details table contains the different pizzas served with each order in the Orders table, and their quantities
-The Pizzas table contains the size and price for each distinct pizza in the Order Details table, as well as its broader pizza type
-The Pizza Types table contains details on the pizza types in the Pizzas table, including their name as it appears on the menu, the category it falls under, and its list of ingredients
-Connected and transformed raw data from Excel files and designed interactive reports and dashboards to complete the task.
-Re-modelled the data relationship.
-Created an executive KPI dashboard containing dynamic filtering options, high-level trending metrics, sales performance, order distribution, and trendings month over month, quarter over quarter. PIZZA DASH
