The Dataset is about superstore orders in the United States of four different regions east, west, central, and south. The dataset consists of close to 10000 orders spanning from 2014 to 2017. The tabular dataset consists of order details, customer details, product details, categories, subcategories, sales & profit across different regions, states, and cities of the United States.
Analyze the dataset and make a dashboard around it mentioning the factors that affect the sales and profit.
To uncover the hidden insights that would help the stakeholders of the superstore in achieving its business objectives. I have incorporated Data visualization techniques to provide actionable insights.
Tableau
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California has generated the highest amount of profit, comprising a contribution of 26.67%, while Texas has incurred the highest amount of loss, comprising a contribution of -8.98%.
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The most profitable subcategory is the copiers with a 19.42% profit contribution, while the tables are the highest with a -6.19% loss contribution.
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The months of November and December show some kind of seasonality triggering the profit increase.
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The superstore should avoid the sale of machines despite great revenue in this sub-category due to high loss contribution, and instead focus more on the sale of the copiers as in addition to great revenue, these are generating the highest amount of profit.