Data Structures are very much important, as we can use these data structure techniques in solving different problems in programming which can benefit us or anyone using these applications.

The techniques which we will learn in this article will help us in future in many different aspects to sort data and we will learn some new skills to sort data in programming.

NEEDS FOR A DATA STRUCTURE:

First Of all let’s see what are the needs of a data structure?

• Data Structures are used to organize data to make a program more efficient.
• More powerful computers have more complex applications.
• And more complex applications demands more calculations.

So to make if short if I have a very much powerful computer system then that computer system will have more some complex applications installed in it, and if an application is very much complex it demands more calculations sorting and capturing data, here the data structure comes into play, we have to make sure that these complex calculation can be done very smoothly, and that is only possible if we use the correct data structure techniques to sort data.

For Example: if I have a telephone directory with 8 million records saved in database, and now I am given the task to filter out 1 specific record from that database of telephone directory, then I must use the correct data structure technique to filter out that record which can get the results for me quickly, but let’s suppose I don’t use the correct data structure technique than that filtration process of 1 record from 8 million records can take day’s but if I will use the correct the data structure technique then the same result can be filtered out in few seconds or minutes.

ORGANIZING DATA:

This Data organization is very much important or any company or software program,

• Any organization for a collection of records that can be searched, processed in any order, or modified.
• The choice of data structure and algorithm can make the difference between a program running in a few seconds or many days.

The same example mentioned above is the best way to understand the importance of Data Organization, we that example we can clearly understand the importance of using correct data structures, if we don’t use the correct data structures that if may cause us or the company for which we are working very badly.

Because if we are filtering, modifying or calculating any data from a database having millions of records, we need to make sure that these calculation and data filtering should be done quickly with accurate results, and that is only possible if we use the correct data structures and algorithms.

EFFICIENCY:

Now let’s see which solutions are considered to be efficient,

• A solution is said to be efficient if it solves the problem within its resource constraints.
  • Space
  • Time
• The cost of a solution is the amount of resources that the solution consumes.

What we understand from the above explanation is that a solution is considered to efficient only if it can provide us accurate results within its resources, and these resources are,

• Space: Which means the amount of space our solution takes to provide accurate results.
• Time: How much time our solution takes to provide accurate results.

We have to make sure that our solution take minimum disk space and time to provide accurate results. If the solution is taking too much disk space and time to provide accurate results that means our solution cannot be called efficient. And the amount out disk space used and time consumed also decides the cost of our solution, because if our solution is taking too much time then we then the cost of electricity will be increased, and if our solution is taking too much disk space then we would need to upgrade the disk space of our system and that will also increase the cost of our solution and our solution in such cases cannot be considered as efficient and cost effective.

SELECTING A DATA STRUCTURE:

In order to select the correct data structures we have to follow the below steps,

1. Analyze The Problem And Determine Resources Accordingly:

This means that we have to first the analyze the problem provided to us, we have to check either the problem can be solved through a data structure or not,

For Example: If have a computer system having 200 (MB) of Hard Disk, and we are asked to store 1 (GB) data in that that computer, in this scenario we cannot use any data structure technique and the only available option will be to upgrade our Hard Disk from 200 (MB) to 1 (GB) to solve this problem.

2. Determine The Constraints And Quantify The Resources Accordingly:

Sometimes we might be provided a problem in which we would need to identify the correct data sources to solve those problems.

For Example: We need to filter out 1 record from 40 million records, In this scenario we have to identify the correct data structure technique which can help us in solving our problem quickly.

3. Selecting the Data Structures That Best Meet Our Requirements:

This is something which can only be gained from experience, because sometimes we might be assigned any problems which have already been solved by someone before us in this can we can use the internet and do some research that how people have solved similar problems before, then we can implement those methods accordingly and we might get our desired results such techniques of researching and solving problems gain our experience and next time we will be able to solve similar problems on our own.

Conclusion:

Data Structures can play vital role in our daily life programming, if you learn this technique of sorting and playing around with huge data, then you are someone to keep an eye on because it is skill very much in demand in today’s programming market, As many companies have huge/big data and they need some who can play around that data according to their requirements and give them their desired results, Today there are thousands of data analyst jobs in market offering high salaries to people who have mastered this technique and these data analyst are ranked very high in the market.

After learning this skill you can also work as freelancer and make some handsome amount of money on many freelancing website available on the internet.

So if you want to become a professional data analyst expert then you need to master all these techniques and it can only be achieved by practice and continues research in the data structures department.

Hopefully you will find this article very much informative and you can benefit from it, don’t forget to share it with your data loving partners as well.