Hmmm, let take it this way :D

I mean, take any kind of programming area and eventually you will go as low as you can get, and you will come into some "data" environment, where everything else is gone and pure data and data structures still stand.

So if u strip all user requirements from one system (no mater what kind of system is ) ... you will eventually come to system roots and its data that will need to be either persisted, forwarded or manipulated by your software :)

Any system in information technology is somehow manipulating some sort of data so in its own roots of any system is actually working with data (on some sort of abstraction).

And if you try to work with raw data without any meanings it will be like you started programming and developing some system from a 19th century, so data need to be organized and structured in some pretty way ... and it's a next best thing it happen in a IT .. people start thinking in a way that data has meaning something to some user of a system (one of ways you can eventually structure your data).

So basically beside some of plain simple data types (structures) like int, floats, bool's, char's ant other primitive types we came to programming and organizing data within classes and objects :)

We also started to structure complex types of data into some structured 'patterns' so we now have even more complex data with design patterns like abstract factories, builders, prototypes etc ...

Conclusion, :) no matter what system you are going to provide, it will be based on a data and data structures as a its own base layer ... so its one of the most important thingies you can (and must) spend most of a time ... because if you have problems and bad design on such low as a data layer ... its not gonna work :D

It is not only important for software. It is for the field of computer science in general. Software ,in an abstract level, consist of (set of) data structures interacting with each other . Almost everything you deal with is related to data structures in one way or another.. Data structure is a representation for the information flow in your algorithm/software/application/system.. Thus, it is crucial to choose the right structure for your data. This includes ,for instance, finding cheap complexity representations for your data (if there is any).

how are we using the concepts of data structures in IT projects. from research point of view i can understand it

when you have bug in the software. it might be because of the misuse of the data structure. For instance, allowing null values in the keys. When you are into scalability/high performance issues you need to look for the data structure fits your application. multithread is another important thing: does your software going to be multithreaded? IF yes you need to lock mechanism for the item (data structure component)

for example , in programming if you want to use an array , then you must know the operations that can be performed on arrays(nothing but the data structure),To use different data structures,whether linear or nonlinear , like tree, graph etc you must know the operations that can be performed on it.e.g. how to add an item , or what happens if an item being added etc.

try to implement the theoritical concepts in any one language. Am sure you will not repeat the question to any one.

Because its all about structuring the data to process it as information that serves as knowledge base for whosoever needs it.

If u want to develop Real world projects u must need DS, bcz without using DS u may hv to develop those real world scenario logic's very much exclusively and that logic's may degrade the performance..

Bcz, DS are the pre-difined Design patterns suggested by the sr. Designers or Architectures those DS are best solutions re-occurring the problems of Application develeopment..

@ prasadu mungala please tell me in more detail

Building strong Base mattam week

Data are bases for getting information, and information is basis for making decisions - it can be considered as an axiom in data analysis. Only an appropriate structure of data can enable us to get information hidden in the data. Especially, data structures are relevant in situation of longitudinally collected data, e.g. in health care, where one patient can visit his/her doctor ones, twices or many times (or never). In such cases you have at least two entities you should consider: patient and visit (one patient, more visits, 1:n relationship). The database is then the appropriate data structure. In case you have only one entity (e.g. status of somthing (or someone) in a moment) the appropriate data structure is just a file, or table (e.g. made by using Excel). Data structuring is the crucial question in probvlem solving, in data analysis, for results which could be get by using either statistics or artificial intelligence methods.

Let us take a scenario in our Java based Distributed project internally used "Mark And Sweep" Algorithm, this Alg implemented by java s/w itself for "Automatic Memory Management" in the form of built in Data structure called "Garbage Collector". When java application is running low memory then "Java Virtual Machine" runs the Garbage Collector, then Garbage Collector finds the unused/idle object from "Heap Memory" and makes that idle objects null objects by nullifying it.

Hence, by using this Automatic Memory Management called "Garbage Collector" improves the application performance with efficient memory management and reduce the memory leakages.

Every data has to presented in some structure

It actually used to represent our data. So when we have different type of arrangement, we can have different algorithm models. So we will get different time complexity. Now we have a choice to select our algorithm with less time

We have a option to select best data structure to represent the given set of dtata

If data are simple can be used any predefined data types, but if they are structured should be used DS because they have the ability to fetch and store data in memory, specified by an address.

Data structures helps describe the analysis problem and make it easier to write lean and efficient code to obtain maximum utility from the data we have. Having a good understanding of the concepts in data structures, you are halfway done in coming up with software for whichever task you intend to subject it to.

Knowingly or unknowingly every one use any of the data structure for their program. If they know the DS then they can write the program effectively and efficiently.

Efficient data structures are a key to designing efficient algorithms and software. Some formal design methods and programming languages emphasize data structures, rather than algorithms, as the key organizing factor in software design.

The performance of algorithm usually depends on DS that is used to store and retrieve information.