For example, a point-of-sale terminal (POS terminal, a computerized cash register) in a busy supermarket collects huge volumes of raw data each day about customers' purchases. However, this list of grocery items and their prices and the time and date of purchase does not yield much information until it is processed. Once processed and analyzed by a software program or even by a researcher using a pen and paper and a calculator, this raw data may indicate the particular items that each customer buys, when they buy them, and at what price; as well, an analyst or manager could calculate the average total sales per customer or the average expenditure per day of the week by hour. This processed and analyzed data provides information for the manager, that the manager could then use to help her determine, for example, how many cashiers to hire and at what times. Such information could then become data for further processing, for example as part of a predictive marketing campaign. As a result of processing, raw data sometimes ends up being put in a database, which enables the raw data to become accessible for further processing and analysis in any number of different ways.