Deta analytics

[KarthikaRajendhran]

The growth of supermarkets in most populated cities is increasing and market competitions are
also high. The dataset is one of the historical sales of supermarket company which has
recorded in 3 different branches for 3 months data. Predictive data analytics methods are easy
to apply to this dataset.
Attribute information
Invoice id: Computer-generated sales slip invoice identification number
Branch: Branch of supercenter (3 branches are available identified by A, B and C).
City: Location of supercenters
Customer type: Type of customers, recorded by Members for customers using member
cards and Normal for those without member cards.
Gender: Gender type of customer
Product line: General item categorization groups - Electronic accessories, Fashion
accessories, Food and beverages, Health and beauty, Home and lifestyle, Sports and
travel
Unit price: The price of each product in $
Quantity: Number of products purchased by the customer
Tax: 5% tax fee for customers buying
Total: Total price including tax
Date: Date of purchase (Record available from January 2019 to March 2019)
Time: Purchase time (10 am to 9 pm)
Payment: Payment used by the customer for the purchase (3 methods are available –
Cash, Credit card and Ewallet)
COGS: Cost of goods sold
Gross margin percentage: Gross margin percentage
Gross income: Gross income
Rating: Customer stratification rating on their overall shopping experience (On a scale of
1 to 10)
Dataset Link: Dataset
Challenge:
Upload the dataset to Cognos Analytics, delete the unnecessary columns, create a data