Introduction to DBMS (Database using MS ACCESS PGDCA/DCA)
Introduction to DBMS
 |
| Introduction to DBMS |
What is Data
Data refers to raw facts, figures, or information that is collected, stored, and processed for various purposes. Data comprises a collection of homogenous or heterogeneous units of information. This "data" encompasses various forms such as text, numbers, media, and more, and can be stored in physical or electronic formats. The term 'Data' is derived from 'datum,' which refers to a single piece of information and becomes plural when used.
Data plays a critical role in various fields, including business, science, healthcare, finance, education, and government, where it is used for purposes such as research, analysis, planning, forecasting, and reporting.
In the context of computing and technology, data serves as the foundation for generating insights, making decisions, and solving problems. It can be analyzed, transformed, and visualized to extract meaningful patterns, trends, and correlations that inform decision-making and drive actions.
What is Database
A database is a structured collection of data organized in a way that enables efficient storage, retrieval, manipulation, and management of information. It is designed to store large volumes of data in a systematic and organized manner, making it easy to access and utilize for various purposes.
In a database, data is typically organized into tables, each consisting of rows and columns. Each row represents a single record or entry, while each column represents a specific attribute or field of the data. By structuring data in this way, databases facilitate efficient querying, sorting, filtering, and analysis of information.
Databases can be categorized into different types based on their architecture, functionality, and usage
Type of Database
Relational Databases:
Relational databases are designed to organize data into tables with established relationships between them. Some common examples of relational databases are MySQL, PostgreSQL, Oracle Database, and Microsoft SQL Server.
NoSQL Databases:
NoSQL databases are designed to handle unstructured or semi-structured data and offer flexible data models. They are suitable for handling large volumes of data with high scalability and performance. Some examples are MongoDB, Cassandra, Couchbase, and Redis.
Object-Oriented Databases:
Object-oriented databases store data as objects, allowing for complex data structures and relationships to be represented. Examples include db4o and ObjectDB.
Graph Databases:
Graph databases store data in a graph structure consisting of nodes, edges, and properties. Examples include Neo4j, Amazon Neptune, and ArangoDB.
Components of a database
components of a database system categorized into hardware, software, and logical components:
Hardware Components:
Server: The server is the physical machine or computer system that hosts the database management system (DBMS) software and stores the database files.
Storage Devices: Storage devices such as hard disk drives (HDDs), solid-state drives (SSDs), or network-attached storage (NAS) systems are used to store the database files and data.
Memory (RAM): Random access memory (RAM) is used by the DBMS software to cache frequently accessed data and perform database operations efficiently.
Software Components:
Database Management System (DBMS): The DBMS is the software application or system responsible for managing the database. It provides tools and interfaces for creating, organizing, manipulating, and accessing data stored in the database.
Data Access Language: Data access languages such as Structured Query Language (SQL) are used to interact with the database, allowing users to perform operations such as querying, inserting, updating, and deleting data.
Procedures and Functions: Procedures and functions are sets of precompiled SQL statements that perform specific tasks or calculations within the database.
Logical Components:
Data: Data is the raw facts, figures, or information stored in the database.
Tables: Tables are the logical structures used to organize and store data in the database. Each table consists of rows and columns, where each row represents a record and each column represents an attribute of the data.
Indexes: Indexes are data structures that improve the performance of data retrieval operations by providing quick access to specific rows or subsets of data within a table.
What is DBMS
DBMS stands for Database Management System. It is a software application or system that facilitates the creation, organization, manipulation, and management of databases.
A DBMS provides an interface for users and applications to interact with the database, allowing them to perform tasks such as querying, inserting, updating, and deleting data. It also handles various administrative functions, including data security, concurrency control, backup and recovery, and data integrity enforcement.
Key features(Advantages) of a DBMS include:
1. Data Definition: A DBMS allows users to define the structure of the database, including the types of data that can be stored, the relationships between different data elements, and the constraints and rules that govern the data.
2. Data Manipulation: DBMS enables users to perform operations on the data stored in the database, such as adding new records, modifying existing records, and deleting unwanted records. This is typically done using query languages like SQL (Structured Query Language).
3. Data Retrieval: DBMS provides mechanisms for users to retrieve specific data from the database based on predefined criteria. This includes querying the database using SQL queries or other search mechanisms.
4. Concurrency Control: DBMS ensures that multiple users or applications can access and modify the database simultaneously without interfering with each other's operations. It manages concurrency control through locking mechanisms and transaction management.
5. Data Security: DBMS includes features to protect the confidentiality, integrity, and availability of data stored in the database. This includes authentication, authorization, and encryption mechanisms to control access to sensitive data.
6. Backup and Recovery: DBMS allows users to create backups of the database to prevent data loss in the event of hardware failure, software errors, or other disasters. It also provides tools for restoring the database to a previous state if necessary.
7. Data Integrity: DBMS enforces data integrity constraints to ensure that the data stored in the database remains accurate, consistent, and valid. This includes enforcing constraints such as primary keys, foreign keys, and domain constraints.
Overall, DBMS plays a critical role in modern data management by providing a centralized and efficient way to store, organize, and access data, thereby enabling organizations to make informed decisions and streamline business processes.
Disadvantages of Database Management Systems (DBMS):
1. Cost: Implementing and maintaining a DBMS can be costly, including expenses related to software licenses, hardware infrastructure, and personnel training.
2. Complexity: DBMS systems can be complex and require specialized knowledge and skills to set up, configure, and administer effectively.
3. Potential for Data Loss: While DBMS includes features for data backup and recovery, there is still a risk of data loss in the event of system failures, human errors, or other unforeseen circumstances.
4. Performance Overhead: DBMS introduces overhead in terms of processing and resource consumption, which can impact the performance of database operations.
5. Vendor Lock-in: Organizations that choose to use proprietary DBMS solutions may become dependent on a single vendor for support and updates. This can limit flexibility and freedom of choice, as migrating to a different DBMS may require significant effort and resources.
6. Scalability Limitations: Some DBMS systems may have limitations in terms of scalability, particularly with respect to handling large volumes of data or supporting a growing number of users and transactions. Organizations may need to invest in additional hardware or software upgrades to address scalability issues over time.
Relational Database
A relational database is a type of database management system (DBMS) that organizes data into tables, where each table represents a collection of related data entities. In a relational database, data is structured in a tabular format consisting of rows and columns, with each row representing a record or tuple, and each column representing a specific attribute or field of the data.
The key concept in a relational database is the notion of relationships between tables. Relationships are established using common attributes, known as keys, which are used to link rows in different tables. The most common type of relationship in a relational database is the foreign key, which references a primary key in another table.
Characteristics of relational databases:
1. Data Integrity: Relational databases enforce data integrity constraints to ensure the accuracy and consistency of data. This includes enforcing primary key and foreign key constraints, as well as other integrity rules specified by the database schema.
2. Flexibility: Relational databases offer flexibility in data retrieval and manipulation, allowing users to perform complex queries, joins, and aggregations to extract meaningful insights from the data.
3. Scalability: Relational databases can scale to accommodate large volumes of data and support a high number of concurrent users. They offer features such as indexing, partitioning, and clustering to optimize performance and scalability.
4. ACID Properties: Relational databases adhere to the principles of ACID (Atomicity, Consistency, Isolation, Durability), which ensure that database transactions are processed reliably and consistently, even in the event of system failures or errors.
5. Normalization: Relational databases use normalization techniques to reduce data redundancy and improve data integrity. Normalization involves breaking down tables into smaller, more manageable entities and organizing them to minimize data duplication.
Relational databases are widely used in various industries and applications, including e-commerce, finance, healthcare, and more, due to their flexibility, reliability, and ease of use. Examples of relational database management systems (RDBMS) include MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server, and SQLite.
Integrity constraints
Integrity constraints in a database are rules or conditions that are enforced to ensure the accuracy, consistency, and validity of the data stored in the database. These constraints help maintain the integrity of the data and prevent errors, inconsistencies, or data quality issues. Here's how integrity constraints relate to different types of keys:
Primary Key Constraint:
A primary key constraint ensures that each row in a table has a unique identifier, known as the primary key.
It enforces entity integrity by preventing duplicate records in the table.
The primary key constraint also ensures that the primary key column(s) cannot contain null values, as null values are not allowed in primary key columns.
Unique Key Constraint:
A unique key constraint ensures that the values in one or more columns are unique across all rows in the table.
It allows for the enforcement of uniqueness without requiring the column(s) to serve as the primary key.
Like the primary key constraint, a unique key constraint also disallows null values in the specified column(s).
Not Null Constraint:
A not null constraint ensures that a column does not accept null values.
It enforces domain integrity by requiring that every row in the table must have a value for the specified column(s).
This constraint is typically applied to columns that are essential for the integrity and functionality of the data model.
Foreign Key Constraint:
A foreign key constraint establishes a relationship between two tables by linking a column in one table (the child table) to a column in another table (the parent table).
It enforces referential integrity by ensuring that values in the foreign key column(s) of the child table correspond to values in the primary key column(s) of the parent table.
The foreign key constraint helps maintain consistency between related tables and prevents orphaned records.
Database design procedure
Database design involves a series of processes that facilitate the designing, development, implementation, and maintenance of data for enterprises. A well-designed database is easy to maintain, enhances data consistency, and is cost-effective in terms of disk storage space. The database designer determines how data elements are related and what data needs to be stored. The fundamental purposes of database design in DBMS consist of establishing logical and physical design models for the planned database system. The logical model focuses on data requirements and the data to be stored independently of physical considerations, while the physical data design model involves translating the logical database design onto physical media using hardware resources and software systems like database management systems (DBMS).
The database design process involves the following steps:
1. Determine the purpose of your database:
- Understand the intended use and objectives of the database. This step prepares you for subsequent design decisions.
2. Find and organize the required information:
- Gather all types of information you need to store in the database, such as product names and order numbers.
- Organize this information into categories or entities, such as Products or Orders.
3. Divide the information into tables:
- Divide the organized information into distinct tables, with each table representing a major entity or subject, such as Products or Orders.
4. Turn information items into columns:
- Determine the specific pieces of information (fields) you want to store in each table.
- Each field becomes a column in the table, representing a specific attribute, such as Last Name or Hire Date in an Employees table.
5. Specify primary keys:
- Choose a primary key for each table, which uniquely identifies each row in the table.
- Common examples of primary keys include Product ID or Order ID.
6. Set up table relationships:
- Determine how the data in one table relates to the data in other tables.
- Establish relationships between tables by adding fields or creating new tables to clarify these relationships.
7. Refine your design:
- Analyze your database design for any errors or inconsistencies.
- Create the tables and add sample data to ensure the design meets your requirements.
- Make adjustments to the design as necessary based on your testing and evaluation.
8. Apply normalization rules:
- Apply normalization rules to ensure that your database tables are structured correctly and efficiently.
- Normalize the data to eliminate redundancy and minimize data anomalies.
- Make any adjustments to the tables as needed to comply with normalization principles.
By following these steps, you can create a well-organized and efficient database design that accurately represents your data and meets your business needs.
Data normalization
Data normalization is a process used in database design to organize data into tables and ensure data integrity by eliminating redundancy and dependency. The main goal of normalization is to minimize data duplication and inconsistencies while optimizing database performance.
Normalization typically involves applying a series of rules, known as normalization forms, to ensure that data is structured efficiently. The most commonly used normalization forms are:
1. First Normal Form (1NF):
- Ensures that each column in a table contains atomic (indivisible) values and that there are no repeating groups of columns.
- Each field must contain a single value, and each row must be uniquely identifiable.
For example we have the following database
StudentID | StudentName | Course1 | Course2 | Course3
--------------------------------------------------------------
101 | John Doe | Math | Science | English
102 | Jane Smith | History | Math | Biology
After 1st Normal Form
StudentID | StudentName
-------------------------
101 | John Doe
102 | Jane Smith
StudentID | Course
-----------------
101 | Math
101 | Science
101 | English
102 | History
102 | Math
102 | Biology
2. Second Normal Form (2NF):
- Builds on 1NF and ensures that each non-key attribute is fully functionally dependent on the primary key.
- Eliminates partial dependencies, where non-key attributes depend on only part of the primary key.
Now using the above example we can modify the design
StudentID | StudentName
-------------------------
101 | John Doe
102 | Jane Smith
CourseID | CourseName
---------------------
1 | Math
2 | Science
3 | English
4 | History
5 | Biology
3. Third Normal Form (3NF):
- Builds on 2NF and ensures that there are no transitive dependencies between non-key attributes.
- Eliminates dependencies where a non-key attribute depends on another non-key attribute, rather than directly on the primary key.
Example of 3rd NF
EmployeeID | EmployeeName | DepartmentID | DepartmentName | ManagerID
---------------------------------------------------------------------
1001 | John Doe | 101 | Sales | 2001
1002 | Jane Smith | 102 | Marketing | 2002
Benefits of data normalization :
- Reducing data redundancy and minimizing storage space.
- Improving data integrity by minimizing the risk of anomalies, such as update anomalies, insertion anomalies, and deletion anomalies.
- Simplifying database maintenance and modification, as changes to the database structure are less likely to cause data inconsistencies.
Overall, data normalization is a crucial aspect of database design that helps create efficient, maintainable, and reliable databases that accurately represent the underlying data.
Conclusion
Frequently Asked Question(FAQ)
What is Data ?
Data refers to raw facts, figures, or information that is collected, stored, and processed for various purposes.
What is Database ?
A database is a structured collection of data organized in a way that enables efficient storage, retrieval, manipulation, and management of information.
What is DBMS ?
DBMS stands for Database Management System. It is a software application or system that facilitates the creation, organization, manipulation, and management of databases.
What is Relational Database ?
A relational database is a type of database management system (DBMS) that organizes data into tables, where each table represents a collection of related data entities.
Post a Comment