Before learning about the advantages of data structure, we should first understand a data structure and a data type and why we need them.
Data types are nothing but the classification or categorization of the data items. Data types represent the kind of value and also tell what operations can be performed on a particular data. Various programming languages and various data types.
Note: The data structures and data types are often used interchangeably. But data structures are used to store the various data types.
Let us now learn about the classification of data structure. The data structure can be classified into two categories namely – primitive data structure and non-primitive data structure.
Refer to the diagram below to see the visual representation of the various data types along with their sizes.
Let us briefly discuss the primitive data structures and non-primitive data structures.
a. Primitive Data Structure
A primitive data structure can store the value of only one data type. For example, a char data structure (a primitive data structure) can store only characters.
Key features of a primitive data structure:
- The size of a primitive data structure is known as it can store can only one data type.
- The primitive data structure will always store some data. It cannot contain the NULL value.
- Examples of the primitive data type are integer, character, boolean, float, double, long, etc.
Learn more about primitive data structures
b. Non-Primitive Data Structure
Unlike the primitive data structure, a non-primitive data structure can store the value of more than one data type. For example, a list in python can store various data types inside it.
Key features of a primitive data structure:
- The size of a primitive data structure depends upon the type of data it stores.
- The primitive data structure will be just initialized without storing any data or value. It can contain the NULL value.
- Examples of the non-primitive data types are linked lists, stacks, queues, dictionaries, etc.
To learn more refer: non-primitive data structures ,or non primitive data types in java.
Advantages of Data Structures
- Data structure is a secure way of storing the data on our system.
- Data structures help us to process the data easily.
- Data structures also help us to store the data on the disks very efficiently so that we can easily retrieve the data.
- Data structures are very important for designing algorithms.
- As we know that data structures are a way to arrange data into a certain form. Now the program execution speed is highly dependent on the type of data structure used.
- Data structures provide us with the reusability of the data. We can create some data in certain formats and store it in libraries so that can be used by different clients.
- Data structures like Graphs help us to visualize, process, and model real-life problems.
- Data structures like Trees help us to visualize, implement and work with hierarchal data sets. For example, if the user has searched a then he/she will search b, so it is widely used in searching related fields.
- Data structures provide us with data abstraction so that the user need not be worried about how the data is being stored on the system.
- Data structures provided by various programming languages come with various built-in functions (or methods) that help us to utilize the particular database more efficiently.
- If a program is working with huge data sets, then the efficient working of such a program depends widely on the type of data structure used. So, an adequate selection of data structure is very important.
- Data structures are also used in the database management system (DBMS) field for creating an index, storing the data using B and B+ trees, etc.
- Data structures have many practical uses such as dynamic memory allocation, process scheduling, file system organization, dictionary, etc.
Now, as we have discussed the advantages of data structure, let us now learn some of the disadvantages of data structure.
What are the Disadvantages of Data Structure?
We have earlier discussed the advantages of a data structure but data structures have some disadvantages as well. Let us now discuss some of the disadvantages of data structures.
- Some of the data structures are complex to handle for a new programmer.
- Some of the data structures provide slower access to data due to the complex structure.
- In case of complex problems or issues, we may require experts to handle the situation.
- The designing of data structures from scratch is quite complex and may require complex algorithms and a lot of time along with tests (quality testing).
- Larger applications require the data structures to be used within one another like the node of a graph is composed of an array or list. So, in such scenarios, the maintenance is quite complex and costlier.
But, we should learn data structures as they are one of the most important concepts of computer science as they help us to manage the data efficiently.
Learn More about the Need & Applications of Data Structure
So far we have discussed the data structure and its relation to the data types. Apart from this, we have also discussed the advantages of data structure and the disadvantages of data structures. Learn more about the data structures
Conclusion
- Data structures are nothing but a meaningful way of arranging, and storing the data in the computer for efficient utilization and processing depending upon the situation.
- Data structures can be classified into two categories namely – primitive data structure and non-primitive data structure.
- Data structure is a secure way of storing the data on our system.
- Data structures help us to process the data easily.
- Data structures provide us with the reusability of the data.
- Data structures also help us to store the data on the disks very efficiently so that we can easily retrieve the data.
- Data structures like Graphs help us to visualize, process, and model real-life problems.
- Data structures like Trees help us to visualize, implement and work with hierarchal data sets.
- Data structures are also used in the field of database management systems (DBMS) for creating an index, storing the data using B and B+ trees, etc.
- Larger applications use nested data structures so the maintenance becomes quite complex and costlier.
- The designing of data structures from scratch is quite complex and may require complex algorithms and a lot of time along with tests.
