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Retail
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Supermarket
The data scientists at Big Mart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet.
Using this model, Big Mart will try to understand the properties of products and outlets which play a key role in increasing sales.
Please note that the data may have missing values as some stores might not report all the data due to technical glitches. Hence, it will be required to treat them accordingly.
Visualizing multiple charts of all significant fields from the train set to analyze and report insights of how Outlet Sales is driven by store & product’s attributes at a retail store and on which variables should be focused further
Train and Test sets: https://www.kaggle.com/akashdeepkuila/big-mart-sales?select=Train-Set.csv
ProductID : unique product ID
Weight : weight of products
FatContent : specifies whether the product is low on fat or not
Visibility : percentage of total display area of all products in a store allocated to the particular product
ProductType : the category to which the product belongs
MRP : Maximum Retail Price (listed price) of the products
OutletID : unique store ID
EstablishmentYear : year of establishment of the outlets
OutletSize : the size of the store in terms of ground area covered
LocationType : the type of city in which the store is located
OutletType : specifies whether the outlet is just a grocery store or some sort of supermarket
OutletSales : (target variable) sales of the product in the particular store
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Tableau
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Power BI
The first Establishment Year experience the highest ever-recorded Total Sum of Outlet Sales at over 3.6 million. Other Establishment Years fluctuated around the Average Total Sum of Outlet Sales at 2,065,861. Only the 1998 saw the lowest Total Sales at 188,340. There might be a significant crisis among the Big Mart or an external factor in this year.
Medidum-sized Outlets contributed slightly more than half the Total Sum of Outlet Sales. Low and High-sized outlets gained moderately at 32.16% and 15.09%, respectively. This medium size can be aimed to expand other Big Mart's properties. Other sizes can be maintained or expanded at a low extent to guarantee the market domination.
(Analysis to be continued)
As the 5 groups are duplicated and can be categorized into 2 groups: Regular and Low Fat. I will select the relevant Fate Content and group them together as below.