Frequently Asked Questions (FAQ’s)

Q. What are data types of attributes?

Data types of attributes refer to the categories that describe the nature of the values they can take on within a dataset, including qualitative types such as nominal and ordinal, and quantitative types such as discrete and continuous.

Q. What is the difference between nominal and ordinal attributes?

Nominal attributes represent categories without any inherent order or ranking, while ordinal attributes have a meaningful sequence or ranking between values, but the magnitude between values is not precisely known.

Q. How do discrete and continuous attributes differ?

Discrete attributes represent countable values or whole numbers, while continuous attributes can take on any value within a range and are typically associated with measurements.

Q. What are attributes in warehouse?

In a data warehouse, attributes typically refer to the descriptive characteristics or properties of data entities, such as dimensions or features, which are used for analysis, reporting, and decision-making.

When we talk about data mining, we usually discuss knowledge discovery from data. To learn about the data, it is necessary to discuss data objects, data attributes, and types of data attributes. Mining data includes knowing about data, finding relations between data. And for this, we need to discuss data objects and attributes. 

Data objects are the essential part of a database. A data object represents the entity. Data Objects are like a group of attributes of an entity. For example, a sales data object may represent customers, sales, or purchases. When a data object is listed in a database they are called data tuples.