Data structure & Algorithm

1. What is Data Structure?

2. Definition of Data Structure
Data Structure can be defined as the
group of data elements which provides an
efficient way of storing and organizing data in
the computer.

3. Student Mark Sheet

4. Dictionary

5. Google Maps

6. Latitude & Longitude

8. Data Structure Example

9. Data Structures are the main part of many
computer science algorithms as they enable the
programmers to handle the data in an efficient
way.
Data Structure uses in Computer
Science

10. 1. Operating System

11. 2. Artificial intelligence

12. 3. Computer Graphics

13. As applications are getting complexes and
amount of data is increasing day by day, there may
arise the following problems:
1. Processor speed :-
To handle very large amount of data, high speed
processing is required, but as the data is growing day
by day to the billions of files per entity, processor
may fail to deal with that much amount of data.
Need of Data Structures

14. 2. Data Search:-
Consider an inventory size of 106 items in a
store, If our application needs to search for a
particular item, it needs to traverse 106 items every
time, results in slowing down the search process.
Need of Data Structures

15. 3. Multiple requests:-
If thousands of users are searching the data
simultaneously on a web server, then there are the
chances that a very large server can be failed during
that process
in order to solve the above problems, data
structures are used. Data is organized to form a data
structure in such a way that all items are not required
to be searched and required data can be searched
instantly.
Need of Data Structures

16. 1. Efficiency: Efficiency of a program depends upon
the choice of data structures.
 For example: suppose, we have some data and we
need to perform the search for a particular record.
Advantages of Data Structures

17. 2. Reusability: Data structures are reusable, i.e. once
we have implemented a particular data structure, we
can use it at any other place.
3. Abstraction: Data structure is specified by the ADT
which provides a level of abstraction. The client
program uses the data structure through interface only,
without getting into the implementation details.
Advantages of Data Structures

19. Definition of Algorithm
Dictionary Definition:
A process or Set of Rules to be followed in
calculations or problem-solving operation,
especially by a computer.
Formal Definition:
An algorithm is a finite set of instructions that
are in a specific order to perform specific task.

20. Characteristics of an Algorithm
1. Input: An algorithm has some input values. We can
pass 0 or some input value to an algorithm.
2. Output: We will get 1 or more output at the end of an
algorithm.

21. Characteristics of an Algorithm
3. Unambiguity: An algorithm should be unambiguous
which means that the instructions in an algorithm should
be clear and simple.
4. Finiteness: An algorithm should have finiteness. Here,
finiteness means that the algorithm should contain a
limited number of instructions, i.e., the instructions
should be countable.

22. Characteristics of an Algorithm
5. Effectiveness: An algorithm should be effective as
each instruction in an algorithm affects the overall
process.
6. Language independent: An algorithm must be
language-independent so that the instructions in an
algorithm can be implemented in any of the languages
with the same output.

23. Dataflow of an Algorithm
1. Problem: A problem can be a real-world
problem or any instance from the real-world
problem for which we need to create a program or
the set of instructions.
2. Algorithm: An algorithm will be designed for a
problem which is a step by step procedure.

24. Dataflow of an Algorithm
3. Input: After designing an algorithm, the
required and the desired inputs are provided to the
algorithm.
4. Processing unit: The input will be given to the
processing unit, and the processing unit will
produce the desired output.
5. Output: The output is the outcome or the result
of the program.