In this example, consider global sales transactions being logged by thousands of servers, all day, and every day, twenty-four hours a day. These transaction records contain typical sales information, such as the date the transaction took place (transaction date), a product identifier (product name), the price of the product (SKU price), the total charged (price), the payment type (payment type), and so on.
In addition, the transaction also captures some interesting fields, such as when the user's online account was created, when they last logged on, and so on.
Many times there is a desire to view transactional data within a particular context--a context that is based on a secondary data source. For example, suppose that there is data available to us that contains promotional marketing information: a file extracted from a database containing the sales and marketing efforts for the products in our sales transactional file.
This information may...