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Analysed 541,000+ retail sales time-series data to compute retail metrics (inventory turn, revenue generation, customer retention) using SQL, prescriptive analytics and Tableau for business report action plan

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Retail-Analytics-Evaluating-Business-Performance-with-KPIs

The dataset is of online retail from Machine Learning Repository at UCI. https://archive.ics.uci.edu/ml/datasets/online+retail

It is a trans-national transactions dataset between 01/12/2010 and 09/12/2011 for a registered online retail based in UK. It sells unique gifts for all occasions. The majority of the customers are wholesalers.

Following is the description of the data -

InvoiceNo: Invoice number. Nominal, a 6-digit integral number uniquely assigned to each transaction. If this code starts with letter 'c', it indicates a cancellation.

StockCode: Product (item) code distinct for every product.

Description: Product (item) name.

Quantity: The quantities of each product per transaction. Numeric.

InvoiceDate: Invice Date and time. the day and time when each transaction was generated.

UnitPrice: Unit price of a product. Numeric, Product price per unit in sterling.

CustomerID: Customer number unique to each customer.

Country: The name of the country where each customer resides.

Analysis of the data will be done to

The data will be analyzed to understand retail math and metrics including inventory turn, average price, revenue generation and calculating margin. It will also be used to identify trends in the revenue generation by the number of orders and analyzing when the dips happen.

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Analysed 541,000+ retail sales time-series data to compute retail metrics (inventory turn, revenue generation, customer retention) using SQL, prescriptive analytics and Tableau for business report action plan

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