Database Concepts and Structures

Database Concepts and Structures

DATABASE SCHEMA
A database schema is the skeleton structure that represents the logical view of the entire database. It defines how the data is organized and how the relations among them are associated. It formulates all the constraints that are to be applied on the data.

A database schema defines its entities and the relationship among them. It contains a descriptive detail of the database, which can be depicted by means of schema diagrams. It’s the database designers who design the schema to help programmers understand the database and make it useful.

A database schema can be divided broadly into two categories:

• Physical Database Schema: This schema pertains to the actual storage of data and its form of storage like files, indices, etc. It defines how the data will be stored in a secondary storage.
• Logical Database Schema: This schema defines all the logical constraints that need to be applied on the data stored. It defines tables, views, and integrity constraints.

E-R MODEL: BASIC CONCEPTS                                    

The ER model defines the conceptual view of a database. It works around real-world entities and the associations among them. At view level, the ER model is considered a good option for designing databases.

Entity: An entity can be a real-world object, either animate or inanimate, that can be easily identifiable. For example, in a school database, students, teachers, classes, and courses offered can be considered as entities. All these entities have some attributes or properties that give them their identity.

An entity set is a collection of similar types of entities. An entity set may contain entities with attribute sharing similar values. For example, a Students set may contain all the students of a school; likewise a Teachers set may contain all the teachers of a school from all faculties. Entity sets need not be disjoint.

Attributes: Entities are represented by means of their properties called attributes. All attributes have values. For example, a student entity may have name, class, and age as attributes.

There exists a domain or range of values that can be assigned to attributes. For example, a student’s name cannot be a numeric value. It has to be alphabetic. A student’s age cannot be negative, etc.

Types of Attributes

• Simple attribute: Simple attributes are atomic values, which cannot be divided further. For example, a student’s phone number is an atomic value of 10 digits.
• Composite attribute: Composite attributes are made of more than one simple attribute. For example, a student’s complete name may have first name and last-named.
• Derived attribute: Derived attributes are the attributes that do not exist in the physical database, but their values are derived from other attributes present in the database. For example, average salary in a department should not be saved directly in the database, instead it can be derived. For another example, age can be derived from date of birth.
• Single-value attribute: Single-value attributes contain single value. For example: Social Security Number.
• Multi-value attribute: Multi-value attributes may contain more than one values. For example, a person can have more than one phone number, email address, etc.

These attribute types can come together in a way like:

• simple single-valued attributes
• simple multi-valued attributes
• composite single-valued attributes
• composite multi-valued attributes

Entity-Set and Keys

Key is an attribute or collection of attributes that uniquely identifies an entity among entity set.

For example, the roll number of a student makes him/her identifiable among students.

• Super Key: A set of attributes (one or more) that collectively identifies an entity in an entity set.
• Candidate Key: A minimal super key is called a candidate key. An entity set may have more than one candidate key.
• Primary Key: A primary key is one of the candidate keys chosen by the database designer to uniquely identify the entity set.

Generalization & Specialization

The ER Model has the power of expressing database entities in a conceptual hierarchical manner. As the hierarchy goes up, it generalizes the view of entities, and as we go deep in the hierarchy, it gives us the detail of every entity included.

Going up in this structure is called generalization, where entities are clubbed together to represent a more generalized view. For example, a particular student named Mira can be generalized along with all the students. The entity shall be a student, and further, the student is a person. The reverse is called specialization where a person is a student, and that student is Mira.