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What are different types of data model?

The basic purpose of a data model is the business model integration which can also be called as the overview of the data modeling context. The details regarding the information or data that is to be stored is provided by the data model. The data model is required in the code generation phase of the development of a product and also during the preparation of functional specifications.

Three perspectives have been defined by the ANSI for the data models namely:
1. External Level: It gives a description of the semantics according to the data manipulation technology. It is concerned with the following:
a) Tables and columns
b) Object oriented classes
c) XML tags and so on.

2. Conceptual Level: It describes the domain’s semantics, thus stating the scope of the model.
3. Physical Level: It gives a description of the physical means for storing the data consisting the following things among the some other:
a) Partitions
b) Table spaces
c) CPUs etc.
With the data models these three perspectives can be implemented independently. Changes can be made in the storage technology without affecting both the conceptual as well as logical model.

Different Types of Data Models

1. Data Base Models
These are actually specifications regarding how a data base is to be structured and used. Many models of this type have been suggested like:
a) Flat model: This model cannot be strictly considered to be a data model since it consists of a single, 2 – D array of the elements having similar values and all the row members are somewhat related to each other.

b) Hierarchical model: The organization of this data model resembles to the tree – like structure having a single upward link for describing the nesting of each record and also a sort field for keeping records in a particular order and in the same level list.

c) Network Model: This data model makes use of 2 fundamental constructs for organizing the data namely sets and records where the sets are used to define the various relationships existing between the records and records consist of the fields.

d) Relational Model: This data model makes use of the first order predicate logic whose core idea is about describing a data base as the collection of predicates. Those predicates are defined over a finite set containing predicate values.

e) Object relational Model: This data model shares similarity with the relational data base model but enjoys a direct support.

f) Star Schema: It is the simplest kind of data model and consists of just the fact tables.

2. Data structure diagram:
This is both a data model and a diagram which gives a description of the conceptual data models by means of the graphical notations. The following are basic graphical elements that are used by a data structure diagram:
a) Boxes: Represents the entities.
b) Arrows: Represents the relationships.
These prove to be quite useful for producing the documentation of the complex data entities.

3. Entity relationship model:
This model (ERM) can be considered to be an abstract form of the semantic data model or the conceptual data model and is used for the representation of the structured data. Makes use of several notations.

4. Geographic Data Model:
This data model is rather like a mathematical construct developed for the representation of the geographic surfaces and objects as data. Some types are:
a) The vector data model
b) The raster data model
c) The triangulated irregular method

5. Generic data model:
The conventional data models when generalized form the generic data models and are used for defining the general relation types which have been standardized.

6. Semantic data model:
This is actually a technique which is aimed at defining the meaning of the data under the context of the inter relationships. It works as an abstraction which states the relation of the stored symbols with the real world.

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