Data mining is the process of analyzing hidden patterns of data according to different perspectives for categorization into useful information, which is collected and assembled in common areas, such as data warehouses, for efficient analysis, data mining algorithms, facilitating business decision making and other information requirements to...
In relational databases, a row is a data record within a table. Each row, which represents a complete record of specific item data, holds different data within the same structure.
A row is occasionally referred to as a tuple.
I've you've used Excel or any other spreadsheet, you have some idea what a table might look like. Relational tables have a very similar but more complex structure, as each table column represents a certain table property.
Let's use an example of a table called CUSTOMER_MASTER that stores basic customer data. It might contain a CUSTOMER_LASTNAME column, which, as the name implies is used to store the last name of customers. This column may have certain parameters, e.g., each surname must be 30 characters or less and only comprised of alphabetical characters. Thus, each customer surname added to the CUSTOMER_MASTER table must meet these parameters.
However, each complete customer row or record also includes other items (e.g., first name, physical address, e-mail address, date of birth and gender, etc). Like Excel, each item is neatly slotted into designated corresponding columns. Thus, each customer row or record is one horizontal line of data that holds a collection of items.
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