Relational Databases
In this lesson, we will explore the concept of relational databases and their components. Understanding how data is organized and related in a relational database is fundamental to effectively using SQL for data manipulation.
Introduction to Relational Databases
Relational databases are a type of database management system (DBMS) that organizes and stores data in a tabular format with predefined relationships between tables. The relational model was introduced by Edgar F. Codd in the 1970s and has since become the most widely used approach for managing structured data.
Components of Relational Databases
Relational databases consist of the following components:
a. Tables: A table is a collection of related data organized in rows and columns. Each table represents an entity or concept within the database. For example, a database for a school might have tables for students, courses, and grades.
b. Rows: Also known as records or tuples, rows represent individual instances of data in a table. Each row contains values that correspond to the columns or fields of the table.
c. Columns: Columns, also known as attributes or fields, represent specific properties or characteristics of the data. Each column has a name and a data type that defines the kind of data it can store (e.g., text, numeric, date).
d. Primary Key: A primary key is a unique identifier for each row in a table. It ensures that each row can be uniquely identified and provides a way to establish relationships between tables.
e. Foreign Key: A foreign key is a column or set of columns in a table that refers to the primary key of another table. It establishes relationships between tables, enabling data integrity and enforcing referential integrity.
f. Relationships: Relationships define how tables are related to each other. The most common types of relationships are one-to-one, one-to-many, and many-to-many. These relationships help to structure and organize data across multiple tables.
Normalization and Data Integrity
Normalization is a process used to eliminate data redundancy and improve data integrity in a relational database. It involves organizing data into multiple tables and establishing relationships between them. Normalization follows a set of rules called normal forms. They are as follows:
- First Normal Form (1NF): The first normal form ensures that each column in a table contains atomic values and there are no repeating groups or arrays within the columns. To achieve 1NF, a table must have a primary key, and each column should contain only single values. Repeating groups should be separated into distinct tables. This eliminates data redundancy and makes it easier to update and manipulate the data.
- Second Normal Form (2NF): The second normal form builds upon the first normal form and eliminates partial dependencies. It states that each non-key column in a table must depend on the entire primary key, rather than just a part of it. In other words, if a table has a composite primary key consisting of multiple columns, each non-key column should depend on the entire composite key, not just a subset. If a non-key column depends on only part of the primary key, it should be moved to a separate table.
- Third Normal Form (3NF): The third normal form further refines the table structure by eliminating transitive dependencies. It states that each non-key column should depend only on the primary key, not on other non-key columns. If a non-key column depends on another non-key column, it should be moved to a separate table. This reduces data duplication and ensures that each piece of information is stored in only one place.
- Fourth Normal Form (4NF): The fourth normal form addresses multi-valued dependencies. It states that a table should not have non-key dependencies between non-key columns. If there are non-key dependencies, they should be separated into their own tables. This helps maintain data integrity and avoids unnecessary data duplication.
- Fifth Normal Form (5NF) or Boyce-Codd Normal Form (BCNF): The fifth normal form deals with join dependencies. It states that a table should not have any non-trivial join dependencies on candidate keys. In simpler terms, it ensures that there are no unnecessary or redundant relationships between tables. If there are such dependencies, they should be resolved by splitting tables or redefining relationships.
By normalizing data, we can reduce data duplication, ensure consistency, and make the database more efficient and manageable.
Querying Data in Relational Databases
SQL allows us to query data in relational databases using SELECT statements. We can retrieve specific columns, filter rows based on conditions, sort data, and perform various operations to retrieve meaningful information from the database.
Understanding the components and structure of relational databases is essential for designing efficient database schemas and effectively using SQL to manipulate data. In the next lesson, we will explore popular database management systems (DBMS) and their role in working with SQL.