/Restaurant-Sales-Analysis

A data project to analyse and visualise business performance to allow informed operational decision making.

Primary LanguageJupyter Notebook

Restaurant Sales Analysis & Dashboard

A data project to analyse and visualise business performance to allow informed operational decision making. The aim of this project was to further enhance skills working with data utilising SQL, Python, and visualisation tools.

Project steps

  1. Generating Sales Data: Creating initial data for a restaurant menu, then generating realistic (dummy) sales data for a restaurant chain with Python scripts.
  2. Preparing the Data for a Data Warehouse: Data manipulation in Python.
  3. Data Staging: Importing data into a PostgreSQL data base and staging it to create final dimension and fact tables. Adding tables to data warehouse and adding table constraints.
  4. Visualisations in Tableau Public: Importing data into Tableau, creating reports and dashboards to allow tracking organisation's and restaurant's performance on annual and monthly basis.

Visualisations

Try both of the dashboards through this link.

Organisation's Annual Performance Dashboard

Allows users to track the restaurant organisation's performance based on number of orders, sales, cost, and profit. Also gives the user the possibility to easily identify which product bring in the most sales. Organisation's Annual Performance Dashboard

Restaurants' Monthly Performance Dashboard

For the purposes of the operational managers in restarants to track their monthly performance and allow improved planning of staffing and ingredients in stock/purchasing needs. Restaurants' Monthly Performance Dashboard

Data warehouse

dwh_design

Future iterations

  • Generating additional data for the project to allow more realistic analysis of organisation's performance: e.g. employee data, working hours, spoilage data, etc.
  • Adding dashboards to analyse the demand for ingredients to allow restaurants to keep accurate levels of ingredients in stock