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Sales Performance Report

  • Topic: Importing Data, Data Manipulation
  • Programming language: SQL
  • Packages: -
  • Algorithms Used: -
  • Project URL: Medium

Data

The dataset used contains transactions from 2009 to 2012 with a total of raw data is 5500, including order status which is divided into order finished, order returned and order cancelled. The dataset that will be used in this project contains the following data:

  • OrderID
  • Order Status
  • Customer
  • Order Date
  • Order Quantity
  • Sales
  • Discount %
  • Discount
  • Product Category
  • Product Sub-Category

    • Task

    DQLab store management wants to know:

    1. Overall performance from DQLab Store

  • Overall performance from DQLab Store for the number of orders and total sales orders finished
  • Overall performance from DQLab Store by product subcategory to compare between 2011 and 2012

    • 2. Promotion Effectiveness and Efficiency

  • Calculate the burn rate of promotions by year
  • Calculate the burn rate of promotions by product subcategory

    • 3. Customer Analyst

  • Analyze the number of customers who make transactions by year
  • Analyze the number of new customers who make transactions by year

    • Summary

    DQLab store during 2009 to 2012 had performance that increased every year but not too significantly. Overall, promotion activities are quite good but still not effective and efficient based on product subcategories. In addition, there are more existing customers who make transactions than new customers, so store performance tends to be stagnant.