A Guide to Reference Data Types in Computer Science

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Reference data management (RDM) is a classification system for data hierarchies. Types of data include Big Data, research data, reference data, master data (of which reference data is a subset), and more. Data types, on the other hand, are something different. Most data types can fall into two categories: reference types and primitive types. The following list provides a better look at the scope of these categories.

Reference Type

  • What we refer to as reference data types are data types that do not store their value directly, as primitive data types would. Rather, a reference type stores its value in a memory address. Like the memory we’re familiar with as humans, a memory address is a “reference” to a specific memory at a specific location that can be accessed at various levels by both hardware and software.

To sum it up, a reference type cannot store an actual value, such as a simple numeric value. For that, you would need a primitive type.

Primitive Type

A primitive data type is capable of using primitive values directly, even at the lowest levels entered in by a programmer. Seven primitive types are in existence:

String

Number

BigInt

Boolean

Undefined

Symbol

Null

These primitives cannot be changed. They are already predefined within Java but not SQL. A “data type class,” however, can provide for SQL.

Class Type

A class type is a subclass of reference type. It applies to true classes in the JLS sense, but it is not an array type or interface type.

Interface Type

An interface type, sometimes referred to as an abstract type, is also a subclass of reference type. It contains various useful methods, including abstract, default, and static. Class types use the abstract methods of interface types.

Nested Type

A nested type is a subset of an interface type.

General Type

General type data is capable of supporting integers, floating point numbers, Boolean equations, and variables. General type data is supported by most languages, and it defines the manner in which operations can be performed on the data.

String Type

A string type is simply a sequence of characters, usually listed as some type of variable. If it is a local variable, it can have a string value, but it does not need to be a default value.

Numeric Types

Numeric types relate to the way numbers are stored in columns for datasets. Exact numeric types can be divided into the following categories: INTEGER, BIGINT, DECIMAL, NUMERIC, NUMBER, and MONEY.

Compound Types

Compound types, aka composite types, are composed by combining a number of elements and program elements from both reference types and primitive types. They are the Frankensteins, or Frankentypes, of data types. Compound types include the following: lists, pointers, hashes, structures, and object references.

Array Types

Array types are a subset of compound types and a type of data structure. As the name suggests, this data type, most basically, uses a collection of elements known as arrays, array variables, or array values. These values can be one-dimensional or multidimensional in form, and they serve to homogenize data points and store them in a more efficient way.

Conclusion

The truth of the matter is that it can be very challenging to memorize, let alone understand all of these data types. However, in the artificial intelligence world that is the 21st century, data storage and data management, with all of its nuances, is crucial to making sense of data and metadata. When we can make sense of these technological realities, then we can manage the challenges that face the ever-technologically advancing world in which we live.