Scenario: Mattresses and More sells bedding essentials from their e-commerce store. Their purchase funnel is:

  1. The user browses products and adds them to their cart
  2. The user proceeds to the checkout page
  3. The user enters credit card information and makes a purchase

Three steps! Simple and easy.

As a sales analyst, you want to examine data from the shopping days before Christmas. As Christmas approaches, you suspect that customers become more likely to purchase items in their cart (i.e., they move from window shopping to buying presents).

The data for Mattresses and More is spread across several tables:

  • browse - each row in this table represents an item that a user has added to his shopping cart
  • checkout - each row in this table represents an item in a cart that has been checked out
  • purchase - each row in this table represents an item that has been purchased



Let’s examine each table. Note that each user has multiple rows representing the different items that she has placed in her cart.

SELECT * FROM browse LIMIT 5; SELECT * FROM checkout LIMIT 5; SELECT * FROM purchase LIMIT 5;

What are the column names in each table?

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