The best way to understand this is to envision database tables as grids, like MS Excel. Each column in the grid contains a particular piece of information. In a customer table, for example, one column contains the customer number, another contains the customer name, and the address, city, state, and ZIP Code are all stored in their own columns.
Breaking Up Data It is extremely important to break data into multiple columns correctly. For example, city, state, and ZIP Code should always be separate columns. By breaking these out, it becomes possible to sort or filter data by specific columns (for example, to find all customers in a particular state or in a particular city). If city and state are combined into one column, it would be extremely difficult to sort or filter by state.
Datatype is a type of allowed data. Every table column has an associated datatype that allows specific data in that column.
A datatype defines what type of data the column can contain. For example, if the column is to contain a number, the datatype would be a numeric datatype. If the column were to contain dates, text, notes, currency amounts, and so on, the appropriate datatype would be used to specify this.
Datatypes restrict the type of data that can be stored in a column (for example, preventing the entry of alphabetical characters into a numeric field). Datatypes also help sort data correctly, and play an important role in optimizing disk usage. As such, special attention must be given to picking the right datatype when tables are created.