Relational Data Structure

Table:
A table is a fundamental concept in a relational database. It represents a collection of related data organized in rows and columns. Tables are used to store and represent entities or objects in the real world. Each table has a name and consists of rows and columns.

Column:
A column, also known as an attribute or field, represents a specific piece of data within a table. Columns define the structure of the data stored in the table and provide a name and data type for each data element. For example, in a table representing employees, you might have columns such as "EmployeeID," "FirstName," "LastName," "Age," etc.

Row:
A row, also referred to as a record or tuple, represents a single data instance in a table. Each row contains data corresponding to each column in the table. In the employee table example, each row would contain information about a specific employee, such as their ID, name, age, etc.

Data Type:
A data type defines the type of data that can be stored in a column of a table. It specifies the kind of data that the column can hold, and it also determines the operations that can be performed on the data. Common data types include integers (e.g., whole numbers), strings (e.g., text), floating-point numbers (e.g., decimals), dates, and more. The choice of data type for a column depends on the nature of the data it will store and the constraints required for that data.

For example, if you have a column for ages, you might use the data type "integer" to ensure only whole numbers are allowed. If you have a column for dates of birth, you might use the data type "date" to ensure proper date format and date-related operations can be performed on that data.