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Performed the data exploration and cleaning using SQL for a dataset about an e-commerce store to provide answers for smart business questions.

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Global Superstore Data Analysis

Introduction

Since the COVID-19 pandemic the e-commerce has become very important, thus generating a large data traffic. This project covers the exploration and cleaning of a large set of fictitious data corresponding to an online store to provide answers to key questions about the business.

Scenario

The CEO believes that the future success of the company depends on:

• An improvement in inventory management focused on products that generate higher profits for the company.

• Design a special promotional campaign for the best customers with the intention of strengthening business relationships.

• Minimize delivery times for countries with higher frequency.

Therefore, it is necessary to carry out an analysis of the data reported in the last 4 years to make decisions based on them.

Business Questions

Product Analysis

• Which are the top 10 profit-making product types on a yearly basis?

• How is the product price varying with sales – is there any increase in sales with the decrease in price at a day level?

Customer Analysis

• Profile the customers based on their frequency of purchase – calculate frequency of purchase for each customer.

• Do the high frequent customers are contributing more revenue?

• Which customer segment is most profitable in each year?

Country and Delivery Analysis

• How the customers are distributed across the countries?

• What is the average delivery time across the countries.

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Performed the data exploration and cleaning using SQL for a dataset about an e-commerce store to provide answers for smart business questions.

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