Data Model II: Types of Data Modelling – SS2 Data Processing Lesson Note (First Term)

Types of data modelling

1. Flat Model: The flat Model (or Table) model consists of a single, two-dimensional array of data elements, where all members of a given column are assumed to be similar in values, and all members of a row are assumed to be related to one another.
2. Hierarchical Model: In a hierarchical database, data is organized into an upside-down tree-like structure, implying a single upward link in each record to describe the nesting, and a sort field to keep the records in a particular order in each same-level list. Hierarchical structures were widely used in the early mainframe database management systems.

3. Network Model: This model organizes data using two fundamental constructs, called records and sets. Records contain fields, and sets define one-to-many relationships between records: one owner, and many members.

4. Relational Model: The relational model or relational database model is based on first-order predicate logic. Its core idea is to describe a database as a collection of predicates over a finite set of predicate variables, describing constraints on the possible values and combinations of values.

5. Object-relational Model: The object-relational model is similar to the relational database model, but objects, classes and inheritance are directly supported in database schemas and the query language. An object-relational database can be said to provide a middle ground between relational databases and object-oriented databases (OODBMS).

6. Star Schema: The star schema is the simplest style of data warehouse schema. The star schema consists of a few “fact tables” (possibly only one, justifying the name) referencing any number of dimension tables”. The star schema is considered an important special case of the snowflake schema.