A data structure is a way of organizing and storing data in a computer so that it can be accessed and manipulated efficiently. It defines the layout, relationships, and the operations that can be performed on the data, making it easier to work with large amounts of data in an optimized manner.

Key Characteristics of Data Structures:

1. Organization: Determines how the data is arranged and related to each other.

2. Efficient Operations: Specifies operations such as insertion, deletion, searching, and updating.

3. Storage: How and where the data is stored (memory, disk, etc.).

Types of Data Structures:

1. Primitive Data Structures: These are the most basic data structures, which directly represent the data.

Examples: Integers, Floats, Characters, Strings, etc.

2. Non-Primitive Data Structures: These are more complex data structures that are built using primitive data types. They are categorized into:

Linear Data Structures: Data elements are arranged in a linear sequence.

Examples: Arrays, Stacks, Queues, Linked Lists

Non-Linear Data Structures: Data elements are not stored in a linear sequence.

Examples: Trees, Graphs

Importance of Data Structures:

1. Efficient Data Manipulation: Helps in performing operations like searching, sorting, and modifying data efficiently.

2. Memory Management: Ensures that data is stored in a way that minimizes memory usage and improves access speed.

3. Optimal Algorithm Design: Certain data structures support specific algorithms that run more efficiently.

Example:

Array: A collection of elements stored in contiguous memory locations. It allows efficient access to elements but has a fixed size.

Linked List: A collection of nodes where each node points to the next. It allows dynamic memory usage but slower access compared to an array.