An entity can be concrete, such as a person or a book, or abstract, such as a loan, a vacation, or a notion. Entities are the fundamental units of objects that can exist in the physical world or represent ideas or concepts. A set of entities of the same type that share the same features or attributes is referred to as an entity set.
A set of attributes represents an entity. An attribute is also known as a data item, data element, data field, and so on. Attributes are descriptive properties that each member of an entity collection possesses. A grouping of related entities is referred to as an entity set.
📌 Example: In a library environment:
- Entity Set: Catalogue
- Entity: Books, Journals, AV-Materials, etc.
- Attributes: Author, Title, Imprint, Accn. No., ISBN, etc.
The term 'DATA' refers to a fact or, more specifically, the value of an entity's attribute. In general, an entity can be an item, a thought, an event, a condition, or a scenario. An entity is described by a set of attributes. Data is information in a form that can be processed by a raw computer. Data are the building blocks of information.
The phrase 'BASE' refers to a thing's support, foundation, or vital constituent. As a result, base supports data.
A 'DATABASE' is a system whose foundation, or main concept, is essentially a particular method of handling data. In other words, a database is simply a computer-based record keeping system. The goal of a database is to record and store information. The fundamental function of a database is to provide service and support for an information system at a low cost.
In short:
"A database is an organized collection of related information stored with minimum redundancy, in a manner that makes them accessible for multiple application."
Definitions
- Prakash Naveen: "Database is a mechanized shared formally defined and central collection of data used in an organization."
- J.M. Martin: "Database is a collection of inter-related data stored together without harmful or unnecessary redundancy to serve multiple application."
- Mac-Millan Dictionary of Information Technology: Defines a database as "a collection of inter-related data stored so that it may be accessed by authorized users with simple user-friendly dialogues."
Functions of Database
The overarching goal of a database is to manage information as a whole. The goal is to make information access simple, rapid, affordable, and adaptable for the user.
Key functions include:
- Controlled Redundancy: Redundant data takes up space and is thus inefficient. System performance is increased by controlled redundancy.
- User-Friendly: Ease of learning and use of database software is a key characteristic.
- Data Independence: Allows for changes at one level of the database without influencing other levels (e.g., changing hardware or adding new data without rewriting applications).
- Economy: Use, store, and modify data at a low cost.
- Accuracy and Integrity: Centralized database control ensures data quality and consistency. Integrity controls detect errors at their source.
- Recovery from Failure: Ensures the system recovers promptly without losing transactions.
- Privacy and Security: Security measures prevent unwanted access. Centralized DBMS control ensures sufficient protection.
- Performance: Response time to queries suitable for data use.
- Database Retrieval, Analysis, and Storage: Makes retrieval, analysis, and storage easier.
- Compatibility: Hardware/software ability to work with different systems.
- Concurrency Control: Allows multiple users to access a database simultaneously while maintaining data integrity.
- Support: Handles complex file structures and access paths (e.g., MARC).
- Data Sharing: Allows any number of users to share data under supervision.
- Standards Enforcement: Standardizes stored data formats for easier exchange between systems.
Types of Databases
A database is considered a central pool of data which can be shared by a community of users. There are three yardsticks to determine the nature of data:
- Whether data is free of format or formatted.
- Whether the definition of data is the same size as data itself.
- Whether the data is active or passive.
Based on these, databases can be classified into four kinds:
- Bibliographic Databases
- Knowledge Databases
- Graphic-Oriented Databases
- Decision-Making Databases
Bibliographic Databases
- Contain format-free (unformatted) data.
- Made up of textual material with little or no format.
- Frequently used in libraries and information systems.
- Example: Book and document abstracts with key terms and phrases, including titles, authors, journal name, volume/issue, date, keywords, abstract, etc.
Knowledge Databases
- Used in Artificial Intelligence applications.
- Contain structured, separate information.
- Usually contain many different types of data with few occurrences each.
- Data size can be as vast as the specification of the data.
Graphic-Oriented Databases
- Used in Computer-Aided Design (CAD), Computer-Aided Learning (CAL), Computer-Aided Instruction (CAI).
- Data is active, meaning it can be executed or acted upon.
- Allows modifications that cannot be executed in bibliographic or knowledge databases.
Decision-Making Databases
- Used in corporate management and administrative tasks.
- Help handle resource planning and sales forecasting.
- Characteristics: ➯ Formatted ➯ Longer than description ➯ Passive
- Often referred to simply as databases.
Concept of Data Structure
Data are structured according to the data model. A group of data elements handled as a unit is called a data structure.
📌 Example: Book details consist of data elements like Author name, Title, Publisher’s name, ISBN, and Quantity.
Different approaches exist to analyze the logical structure of data in complex databases. While all DBMS share a common data management approach, they differ in data structure.
Types of Data Structures
- List Structure➯ A linear data record structure. ➯ Nth record is related to (N-1) and (N-2) simply due to position. ➯ Represents a one-to-one relationship.
- Tree / Hierarchical Structure➯ Non-linear, multilevel hierarchical structure. ➯ Each node connects to multiple nodes below but only one above. ➯ Parent-child relationship used to store data. ➯ Root: Top node, Node: Data at levels, Leaf: Final node. ➯ Represents a one-to-many relationship.
- Network Structure➯ Another hierarchical structure but more general. ➯ Data represented by records and links. ➯ Supports many-to-many relationships. ➯ Users see database as a collection of individual record occurrences.
