Data:
Data is a collection of raw facts, such as number, words, measurements, observations or just description of things.
Information:
Information is a classified or organized data which has some meaningful value. Information is processed data in which organization, decision and actions are based.
Example: 20 students are enrolled at Durgalaxmi for the year 2081 in computer engineering.
Knowledge:
Knowledge is a understanding of specific subject through experience or education.
Example: 20 students are enrolled which is very minimum.
Database:
Database is a collection of related data which represents some aspect of real world.
Simply, database is a container of data files in which data are stored in huge amount.
Database Management System
DBMS is a software for storing and retrieving data by considering appropriate safety measures. DBMS allows users to create their own database as per their requirement. DBMS facilitate the creation and maintenance of computerized database.
Example: My SQL, Mongo DB, MS SQL server, etc.
File System
File system is a structural and logical rule that are used to organize the group of data and their name. File system is a traditional way that is easier for physical access.
Limitations of File System:-
i) Data Redundancy:
Redundancy means duplication of same data in different tables. Redundancy leads to excess data storage.
ii) Data Inconsistency
when same data is managed differently in different places, it leads to data inconsistency. Data inconsistency creates unreliable Information because it will be difficult to determine which version of information is correct.
iii) Data Isolation
In file system, because data mapping is not supported. So all the files are created and kept in isolation. It becomes very difficult to keep database in same state after the execution of transaction.
iv) Data Dependency
Data are stored in specific format or structure in a file. If the structure or format is changed, all the exciting application program accessing that files also need to be changed. Otherwise the program may not work correctly.
v) Controlled Data Sharing: It is very difficult to provide access to control data at different level for different users in a file system.
Advantages of DBMS:-
i) Data Redundancy problem can be solved
ii) High Security
iii) Presence of data integrity
iv) Supports multiple users
v) Shared data
vi) Data Backup
Disadvantages of DBMS
i) Size: The functionality of DBMS makes use of large piece of software which occupies huge disk space.
ii) Complexity: DBMS is complex to manage and maintain data.
iii) Higher Impact of Failure: The centralization of resources increase the vulnerabilities of the system because all users application rely on the availability of DBMS. The failure of any component can bring operation to half.
iv) Performance: The performance of DBMS is very slow. It may not run as fast as possible.
v) Cost of DBMS: The cost of DBMS varies significantly depending on the environment and functionality provided.
Applications of DBMS:
i) Security: DBMS provides security features to ensure that data can only recover in case of system failure or data loss.
ii) Healthcare: DBMS is used in healthcare to manage patients data, medical reports, billings and transaction records.
iii) Accounting: Database administrative framework is utilized for putting data about deals, holdings and acquisition of monetary instruments.
Example: Stacks and bond in a data set.
iv) Banking: Database executive framework is used to store the exchange data of the client in the database. Information and details of account holders and workers is also stored in the database.
v) Credits and Exchanges: The DBMS framework is used for buying on change cards and age of month to month proclamations.
vi) Data Retrieval: DBMS provides a way to retrieve data quickly and easily using search queries.
vii) Data manipulation: DBMS provide tools to manipulate data such as sorting, filtering, aggregating, merging, searching and displaying data.
viii) Multiuser Access: DBMS allows multiple users to access and modify data simultaneously.
Types of Database users:
i) Database Administrators
DBA are the most important type of database users. DBA have full control of the database and they are sometimes known as the super-user of database. DBA monitor the backup and recovery of the database records and provides technical support as well.
ii) Naïve Users
Naïve users don’t have any knowledge of DBMS but still frequently use the database applications to get the interface provided by the DBMS applications. Naïve users mostly use database to view level.
iii) Sophisticated Users
They are the type of database users who know DBMS commands and are familiar with the database. Sophisticated users can be data analysts, Engineers, system analysts, etc.
iv) Database Designer
Database designers are the user in DBMS who design and create the structure of the database including triggers , indexes, schemas, entity relationships, tables, constraints, etc which completes the database.
v) Application programmer
They are also known as back-end developers who are computer professional users who are responsible for developing the application programs.
Example: C, C++, Java, PHP, Python, etc.
DBMS Architecture
The design of DBMS depends upon its architecture. The basic client server architecture is used to deal with large number of computers, web servers, database servers and other components that are connected with network.
Types of DBMS Architecture:
i) 1 Tier Architecture
In this architecture database is directly available to the user. This architecture is used for development of local application where programmers can directly communicate with the database for quick response.
ii) 2 Tier Architecture
In this architecture, application in the client end can directly communicate with the database at the server side. For this interaction API’s like ODBC, JDBC are used. The server side is responsible for providing functionalities like query processing, and Transaction management.
Example: 2 Tier Architecture
iii) 3 Tier Architecture
The 3-tier architecture contains another layer between the client and server. In this architecture client can’t directly communicate with the server. The 3 tier architecture is used in case of large web application.
Example: 3 Tier Architecture
Database Model
A database model is a conceptual representation of how data is organized and structured within a database. It defines the logical structure of the database and how data is stored, organized, and accessed.
Some Types of Database Model are:
i) Hierarchical Model: In this model, data is organized in a tree-like structure where each record has one parent record and multiple child records. It’s like an inverted tree where data flows downward from parent to child. This model was popular in early database systems but has largely been replaced by more flexible models.
ii) Network Model: The network model extends the hierarchical model by allowing each record to have multiple parent and child records, creating a more flexible structure. It uses pointers to represent relationships between records. This model was also used in early database systems but has been largely supplanted by more modern models.
iii) Relational Model: The relational model organizes data into tables (relations) consisting of rows (tuples) and columns (attributes). Relationships between tables are established using keys. It’s based on set theory and provides a powerful and flexible way to represent data and relationships . SQL (Structured Query Language) is commonly used to query and manipulate data in relational databases.
iv) Object-Oriented Model: This model stores data as objects, similar to how they’re represented in object-oriented programming languages. Objects contain data fields and methods/functions to operate on that data. It’s well-suited for applications where data and behavior are closely related, such as in object-oriented programming.
Database Schema
A database schema is a blueprint or logical structure that defines the organization, structure, and relationships of data
within a database. It provides a framework for how data is stored, accessed, and managed. The schema defines the tables, fields, keys, constraints, and relationships that make up the database.
There are different levels of Database schema:
They are:
i) Physical Schema: The physical schema describes how data is stored on the physical storage devices such as hard drives or solid-state drives. It includes details such as file organization, indexing methods, data storage formats, and access paths. This level of schema is concerned with optimizing storage and access for efficient data retrieval and manipulation. Examples of physical schema elements include data block size; file placement, and indexing structures.
ii) Logical Schema: The logical schema describes the structure of the database without considering how the data is physically stored. It defines the tables, columns, relationships, constraints, and other logical structures. This level of schema is concerned with representing the data model and ensuring data integrity and consistency .Examples of logical schema elements includes tables, views, indexes, primary keys, foreign keys, and relationships between tables.
iii) Conceptual Schema: The conceptual schema provides a high-level view of the entire database without going into the details of table structures or implementation specifics. It represents the overall logical structure of the database, including entities, attributes, and relationships. This level of schema is often used for database design and conceptual modeling, providing a clear understanding of the data model. Examples of conceptual schema elements include entity-relationship diagrams (ER diagrams), which depict entities, attributes, and relationships between them.
iv) External Schema (View Schema): The external schema represents specific views or subsets of the database that are tailored to the needs of individual users or applications. it defines how different user groups or applications interact with the database and what data they can access. This level of schema provides a customized view of the database to meet the requirements of different users or applications. Examples of external schema elements include views, which are virtual tables derived from one or more base tables, presenting a subset of the data.