- Normalization: Process of organizing data in a database to reduce redundancy and improve data integrity.
State two 2 advantages of Normalization
- Data Integrity: Reduces data redundancy and inconsistencies, leading to improved accuracy and reliability.
- Efficient Database Design: Helps in optimizing storage space, simplifying data updates, and enhancing overall database performance.
State two 2 disadvantages of Normalization
- Increased Joins: Need for frequent joins between normalized tables can lead to performance issues, especially in complex queries.
- Complexity: Over-normalization can result in overly complex database schemas, making it challenging to query and maintain the database.
Explain with examples, the following terms
Polymorphism
Abstraction
Encapsulation
Inheritance
### Polymorphism:
- Definition: Polymorphism allows objects of different classes to be treated as objects of a common superclass through method overriding.
- Example:
```python
class Animal:
def speak(self):
pass
class Dog(Animal):
def speak(self):
print("Woof!")
class Cat(Animal):
def speak(self):
print("Meow!")
def animal_speak(animal):
animal.speak()
dog = Dog()
cat = Cat()
animal_speak(dog) # Output: Woof!
animal_speak(cat) # Output: Meow!
```
### Abstraction:
- Definition: Abstraction allows hiding the complex implementation details and showing only the necessary features to the user.
- Example:
```python
from abc import ABC, abstractmethod
class Shape(ABC):
@abstractmethod
def area(self):
pass
class Rectangle(Shape):
def __init__(self, length, width):
self.length = length
self.width = width
def area(self):
return self.length * self.width
rectangle = Rectangle(5, 3)
print(rectangle.area()) # Output: 15
```
### Encapsulation:
- Definition: Encapsulation involves bundling data (attributes) and methods (behaviors) that operate on the data into a single unit (class) to restrict direct access to data.
- Example:
```python
class Employee:
def __init__(self, name, salary):
self.__name = name # Private attribute
self.__salary = salary # Private attribute
def get_name(self):
return self.__name
def get_salary(self):
return self.__salary
def set_salary(self, new_salary):
self.__salary = new_salary
emp = Employee("Alice", 50000)
print(emp.get_name()) # Output: Alice
print(emp.get_salary()) # Output: 50000
emp.set_salary(55000)
print(emp.get_salary()) # Output: 55000
```
### Inheritance:
- Definition: Inheritance allows a class to inherit attributes and methods from another class, promoting code reusability and establishing an "is-a" relationship.
- Example:
```python
class Vehicle:
def __init__(self, make, model):
self.make = make
self.model = model
def display_info(self):
return f"{self.make} {self.model}"
class Car(Vehicle):
def __init__(self, make, model, color):
super().__init__(make, model)
self.color = color
def display_info(self):
return f"{self.color} {self.make} {self.model}"
car = Car("Toyota", "Corolla", "Red")
print(car.display_info()) # Output: Red Toyota Corolla
```
Define the following terms in DBMS
Attributes
Cardinality
Degree
Tuple
### Attributes:
- Definition: Attributes are the individual data elements that describe an entity. In a database table, attributes correspond to columns that represent specific characteristics or properties of the entity being modeled.
### Cardinality:
- Definition: Cardinality refers to the number of unique values that a column (attribute) can hold in a relational database table. It indicates the relationship between tables in a database by specifying the maximum number of related records that each record in a table can have in another table.
### Degree:
- Definition: Degree, also known as arity, refers to the number of attributes (columns) in a relation (table) within a relational database. It represents the total number of fields or data components in a tuple (row) of the relation.
### Tuple:
- Definition: In a relational database context, a tuple represents a single row or record in a table. It contains a set of attributes (columns) that encapsulate specific data related to an entity. Each tuple in a table represents a distinct instance or occurrence of the entity being modeled.
State and Explain five 5 advantages of Relational Model
### Advantages of Relational Model:
1. Data Integrity:
- Explanation: The relational model enforces data integrity through constraints such as primary keys, foreign keys, and unique constraints. This ensures the accuracy, consistency, and reliability of data stored in the database.
2. Flexibility and Scalability:
- Explanation: The relational model allows for flexible data retrieval and manipulation through SQL queries, enabling users to perform complex operations efficiently. Additionally, relational databases can easily scale to accommodate growing data volumes and evolving business requirements.
3. Normalization:
- Explanation: The relational model promotes data normalization, reducing data redundancy and inconsistencies. By organizing data into related tables and eliminating duplicate information, it enhances data integrity and simplifies database maintenance.
4. Data Consistency:
- Explanation: Relational databases ensure data consistency by enforcing ACID properties (Atomicity, Consistency, Isolation, Durability) during transactions. This guarantees that database operations are executed reliably and that data remains consistent even in concurrent access scenarios.
5. Query Optimization:
- Explanation: Relational databases offer query optimization mechanisms, such as indexing, query plans, and execution plans. These tools enhance query performance by efficiently retrieving data from tables, minimizing processing time, and improving overall database performance.
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