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3 Examples of Data Abstraction

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Data abstraction is the design of data based on abstract concepts as opposed to physical realities. The term is associated with intuitive and easy to understand representations of complex data. The following are illustrative examples.

Calculations

A weather forecast offers intuitive data based on concepts such as "probability of precipitation" that are based on weather algorithms that process data collected from weather stations and satellites. The concept drops details such as confidence intervals and margin of error.

Data Collection

A metric such as customer satisfaction rate is based on quantification of an abstract question such as "How would you rate our service?" Although the concept of "satisfaction" is abstract it may be taken as seriously as concrete numbers such as revenue.

Data Structures

Programming languages and APIs typically offer abstract data types that provide an intuitive way to store and access data. For example, a List data type allows data to be stored as an ordered sequence. A List offers programmers intuitive methods to access data without the need to understand how data is actually structured and managed.
Overview: Data Abstraction
Area
Definition (1)
Data based on abstract concepts.
Definition (2)
Data based on an intuitive concept.
Definition (3)
Data that is collected, calculated or structured based on a concept that differs from concrete physical realities.
Related Concepts
Next: Abstract Concepts

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