Technical Field The present invention relates to a system and method for assessing the transitioning of computing components/service categories to a cloud computing environment and more particularly for determining the transition of organization applications to a cloud computing environment. Background Traditional data centers tend to run a single operating system instance and a single business application on one physical server. This "one server, one appliance" model leads to extremely poor resource utilization. For example, it is not uncommon for a significant portion of data center resources to be unused for a majority of the data center's "up" time. Wasted resources include CPU, RAM, Storage, and Network Bandwidth. Additionally, many traditional data centers are typically implemented by combining a heterogeneous mix of different servers, operating systems, applications and data. Consequently, deploying, managing, and reconfiguring software or hardware on physical servers and the data center's network infrastructure is mostly achieved via manual (e.g., human) labor, and it typically very time consuming. Additionally, in such data centers, the upgrading of servers typically involves a relatively slow and costly process. Further, in situations where workloads grow more rapidly than expected and place heavy demands on server resources, such traditional data centers face the problem of over-utilizing their servers, which may result in business continuity being placed at risk. A number of factors have given rise to an increase in the utilization of cloud computing resources. For example, advances in networking technologies have significantly improved resource connectivity while decreasing connectivity costs. Advances in virtualization technologies have increased the efficiency of computing hardware by improving scalability and making it possible to more closely match computing hardware resources to the requirements of a particular computing task. Additionally, virtualization technologies commonly deployed in cloud computing environments have improved application reliability by enabling failover policies and procedures that reduce or all together eliminate disruption due to an application or hardware failure. In general, the concept of "cloud computing" refers to the utilization of a set of shared computing resources (e.g., servers) which are typically consolidated in one or more data center locations. A cloud-based computing resource is thought to execute or reside somewhere on the "cloud", which may be an internal corporate network or the public Internet. From the perspective of an application developer or information technology administrator, cloud computing enables the development and deployment of applications that exhibit scalability (e.g., easily and dynamically increase or decrease resource utilization as needed), performance (e.g., execute efficiently and fast), and reliability (e.g., never, or at least rarely, fail), all without any regard for the nature or location of the underlying infrastructure. A cloud computing implementation of a software application allows an organization to access the application through the Internet without knowledge of, expertise with, or control over the technology infrastructure supporting the application. Cloud computing provides many benefits over traditional infrastructure models where compute equipment is owned or leased and housed in a server room, data center, or collocation site, such as on-demand procurement, reduced cost, increased capability in terms of compute and storage, flexibility and application mobility. For example, applications may be provided that are accessible from a web browser, while the application software and data are centrally stored. Cloud computing may add complexity over traditional infrastructure models in terms of regulation compliance and controllability; organizations may have difficulty determining the trade-off between the benefits and the complexity. There are various systems and methods devised for assessing the transitioning of computing components/service categories to a cloud computing environment as mentioned below. US 2010/0042720 includes a multi-cloud management module having a plurality of cloud adapters. The multi-cloud management module provides a unified administrative interface for provisioning cloud-based resources on any one of several clouds for which a cloud adapter is configured for use with the multi-cloud management module. Each cloud adapter converts non-cloud-specific commands to cloud-specific provisioning commands for the cloud to which the cloud adapter is associated. US 2010/0125473 discloses a system for providing a cloud computing assessment tool. The system may include a memory, an interface, and a processor. The processor may receive a data center configuration from the user. The data center configuration may include a compute and storage capacity. The processor may determine a cloud computing configuration equivalent to the data center configuration. The processor may identify a time period for transitioning from the data center to cloud computing. The processor may identify a plurality of trend values representing changes in the compute capacity and storage capacity over the period of time. The processor may generate a strategy to transition from the data center to cloud computing over the period of time. The strategy may account for the changes in the compute capacity and the storage capacity. The processor may provide a graphical output and a numerical output of the strategy to the user. US 2009/0276771 discloses on-demand, grid and/or utility computing networks. Examples of at least a portion of the techniques (and/or related features, aspects, and/or benefits) disclosed herein include: techniques for migrating virtual appliances from a first server grid to a second server grid via a communication network; techniques for migrating distributed applications from a first server grid to a second server grid via a communication network; techniques for delivering pre-packaged software in virtual appliances to computing systems for use in operating software applications; techniques for managing use of virtualized computing resources implemented in a computing network; exchange systems for renting or leasing computing resources provided over a computing network; techniques for offering, via a computing network, virtualized computing resources for use in deployment of one or more distributed applications at one or more server grids of a computing network; techniques for offering, via a computing network, distributed application components for use in deployment of one or more distributed applications at one or more server grids of a computing network; techniques for implementing exchange of computing resources between computing resource providers and computing resource subscribers of a computing network; and the like. In at least one embodiment, the computing network may include multiple different data centers and/or server grids which are deployed different geographic locations. In at least one embodiment, at least some of the server grids may be operable to provide on-demand, grid and/or utility computing resources for hosting various types of distributed applications. In at least one embodiment, a distributed application may be characterized as an application made up of distinct components (e.g., virtual appliances, virtual machines, virtual interfaces, virtual volumes, virtual network connections, etc.) in separate runtime environments. In at least one embodiment, different ones of the distinct components of the distributed application may be hosted or deployed on different platforms (e.g., different servers) connected via a network. In some embodiments, a distributed application may be characterized as an application that runs on two or more networked computers. However, above-mentioned systems and methods do not provide a unique, fast, efficient, highly automated and comprehensive framework which provides for very high level of parameterization at each level that are useful in aligning with the organization's imperatives, business needs and business demands. The afore-mentioned problems are solved by the instant invention. Objects and Summary The object of the present invention is to provide a system and method for assessing the transitioning of computing components/service categories to a cloud computing environment. It is an object of the present invention to provide a system and method for determining the transition of organization applications to a cloud computing environment. Another object of the present invention is to determine the cloud computing provider for the organization. Yet another object of the present invention is to provide a very high level of parameterization at each level of transitioning to the cloud computing environment. To achieve the aforementioned objects, the present invention provides a method for determining a transition to a cloud computing environment, said method comprising the steps of: • identifying at least one category of service in an organization to be transitioned to a cloud computing environment; • collecting relevant information about the category from one or more service category owners and/or users; • analyzing the information received based on pre-defined parameters; and • classifying the services into high cloud ready, moderate cloud ready or limited cloud ready based on the analyzed information. The present invention further provides a system for determining a transition to a cloud computing environment, said system comprising: • means for identifying at least one category of service in an organization to be transitioned to a cloud computing environment; • means for collecting relevant information about the category from one or more service category owners and/ or users; • means for analyzing the information received based on pre¬defined parameters; and • means for classifying the services into high cloud ready, moderate cloud ready, or limited cloud ready based on the analyzed information. Brief Description of the Drawings The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and components. Fig. 1 is an exemplary system illustrating the network diagram of the cloud computing assessment tool according to the present invention. Pig. 2 is an illustration of general purpose computer system used in a cloud computing assessment tool according to the present invention. Fig. 3 is an exemplary method indicating the three phases for transitioning to a cloud computing infrastructure according to the present invention. Fig. 4 is an exemplary flowchart illustrating a method of transitioning to a cloud computing environment according to the present invention. Fig. 5 is an exemplary flowchart illustrating analyzing phase of the method according to the present invention. Detailed Description System and method for assessing the transitioning of computing components/service categories to a cloud computing environment is described. The system and method is not intended to be restricted to any particular form or arrangement, or any specific embodiment, or any specific use, disclosed herein, since the same may be modified in various particulars or relations without departing from the spirit or scope of the claimed invention herein shown and described. The system and/or method shown is intended only for illustration and disclosure of an operative embodiment and not to show all of the various forms or modifications in which this invention might be embodied or operated. The instant invention provides a system and method for assessing the transitioning of computing components/service categories in an organization to a cloud computing environment. The service categories can be infrastructure, applications or software. The cloud computing environment can be based on IaaS (Infrastructure as a service), PaaS (Application or Platform as a service), SaaS (Software as a Service). The instant invention provides for very high degree of parameterization at each level of the system for transitioning to cloud computing environment. There are many factors such as CRI (cloud readiness score) score, risk scores and value scores of the computing components based on which the method determines the most suitable cloud computing type, cloud provider and cloud scenario for the organization. The method also determines the capability of the computing components to be moved to the cloud type, provider and scenario. The techniques described herein may be used in many different operating environments and systems. An exemplary environment that is suitable for practicing various implementations is discussed in the following section with respect to the accompanying figures. EXEMPLARY SYSTEM Fig. 1 is an exemplary system illustrating the network diagram of the cloud computing assessment tool according to the present invention. According to a preferred embodiment of the instant invention, the system and method provides a technique for transitioning the organization applications to the cloud computing environment by implementing IaaS, PaaS or SaaS as a cloud model. The network environment 100 can include a server 102 comprising a database 110, network 104, service categories 106 in an organization which can be transitioned to either of cloud computing model as mentioned in the diagram, one or more users and/or service category owners 108A-N of the organization. The server 102 can interact with the users and/or service category owners 108A-N of the organization 106 through the network 104 for devising a transition strategy for the organization to the cloud computing environment. It provides a questionnaire to the users and/or owners as front end applications through the network 104. The server 102 can include application server, an infrastructure or data center server and software server depending upon the type of service to be deployed in the organization. The server 102 can be a general purpose computer system as illustrated in Fig. 2. The network 104 can include wide area network such as internet, local area network, wireless network or any other network that can allow data communication. The networks can be public or private network connection and can deploy any of the security features such as firewall, encryption etc. The database 110 can be any relational, hierarchical or network database. The users 108A-N workstations can be a general purpose computer system as depicted in Fig. 2. Fig. 2 is an illustration of general purpose computer system used in a cloud computing assessment tool according to the present invention. The computer system 200 can operate as a standalone device or may be connected, e.g., using a network, to other computer systems or peripheral devices. In a networked deployment, the computer system can operate in the capacity of a server or as a client user computer in a server-client user network environment, or as a peer computer system in a peer-to-peer (or distributed) network environment. The computer system 200 can also be implemented as or incorporated into various devices, such as a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile device, a palmtop computer, a laptop computer, a desktop computer, a communications device. It can also be implemented using electronic devices that provide voice, video or data communication. The computer system 200 can include a processor 202, such as, a central processing unit (CPU), a graphics processing unit (GPU), or both. The processor 200 can be one or more general processors, digital signal processors, application specific integrated circuits, field programmable gate arrays, servers, networks, digital circuits, analog circuits, combinations thereof, or other now known or later developed devices for analyzing and processing data. The computer system 200 can include a memory 210 that can communicate via a bus 208. The memory 210 can be a main memory, a static memory, or a dynamic memory. The memory 210 can include various types of volatile and non-volatile storage media, including but not limited to random access memory, read-only memory, programmable read-only memory, electrically programmable read-only memory, electrically erasable read-only memory, flash memory, magnetic tape or disk, optical media and the like. In one case, the memory 210 may include a cache or random access memory for the processor 202. The memory 210 can be an external storage device 214 or database for storing data and can include a hard drive, compact disc ("CD"), digital video disc ("DVD"), memory card, memory stick, floppy disc, universal serial bus ("USB") memory device, or any other device operative to store data. The memory 210 can be operable to store instructions executable by the processor 202. The processing strategies can include multiprocessing, multitasking, parallel processing and the like. The computer system 200 can further include a display 212, such as a liquid crystal display (LCD), an organic light emitting diode (OLED), a flat panel display, a solid state display, a cathode ray tube (CRT), a projector, a printer or other now known or later developed display device for outputting determined information. Additionally, the computer system 200 can include an input/output device 206 configured to allow a user to interact with any of the components of system. The input device 206 may be a number pad, a keyboard, or a cursor control device, such as a mouse, or a joystick, touch screen display, remote control or any other device operative to interact with the system. The computer system 200 can include a communication interface 216 for transmitting or receiving the instructions over the network 218. The communication interface 216 can be a part of the processor 202 or can be a separate component. The communication interface can be created in software or may be a physical connection in hardware. The communication interface 216 can be configured to connect with a network 218, external media, the display 212, or any other components in system 200, or combinations thereof. The connection with the network 218 can be a physical connection, such as a wired Ethernet connection or may be established wirelessly. In the case of a server 102, the server can communicate with users 108A-N through the communication interface 216. EXEMPLARY METHOD Fig. 3 is an exemplary method indicating the three phases for transitioning to a cloud computing infrastructure according to the present invention. The first phase is explore phase which involves collection of Data/Information about the category of service from the one or more users and service category owners of the organization. The information can be organization's business imperatives, people, processes, technologies, tools, risks, compliance, application's inventory, support characteristics, infrastructure such as servers, network, data storage and connectivity. The collection of data depends upon the cloud computing environment to be implemented as explained above. The second phase is analyze phase which can be based on parameters like Business Criticality of Application, Application/Platform Complexity, Demand Elasticity, Technology etc. The user or service category owner is provided with a questionnaire by the server. The questionnaire comprises of questions based on the characteristics of the computing components, for example, application characteristics. The questions can be used to determine the environment of the computing component, the operating system used by the computing component etc. The assessment is done by the server 102 in a mathematical manner as defined below. 1. Let A be a set of application characteristics, thus A = {A1,A2> -tAn} 2. Let E be a target cloud environment characteristics, thus E = {El,Ez,...,En} 3. Then, Scores (CRI, Risk and Value) Jl(A,Ey of an Application A for a target cloud environment E is defined as equation (i) Where a. wiPj is equal to non-linear function returning 0 or 1 b. wi^) is defined as 1. w(^) = 0 => v(J>i) = 0 or 10 depending on E 2. w(P() = 1 => vM = 0 c. wt is the weight of a parameter d. yt is defined as ... equation (ii) e. Wj is the weight of a question having the value of Vj f. t- = vJb + /U) + f(E) + /U,E) ... equation (iii) g. i^- is baseline benchmark for the given organization for application characteristic A, 4. Let 1(E) be the lower threshold for the given set of applications. 5. £(£) = 3l(A£,E} ... equation (iv) a. where A£ represents ideal application to be kept in house for the organization 6. Let 11(E) be the upper threshold for the given set of applications. 7. lf(F) = MAUfE) ... equation (v) a. where A-a represents ideal application to be moved to cloud for the organization 8. An application's readiness can thus be compared to lower threshold £(£)and upper threshold ll(E'} for the given set of applications. 9. Let C be the set of applications in an organization, then a. CH is the set of applications with high CRI Scores, high Value scores and low Risk score. CRI Score and Value score defined as CH = ¥ Q EC : U(E} < 3l(AQ,E) < 10 ... equation (vi) Risk score defined as CH = V Ci e C : 0.5 < M(AQIE) < L(E) equation (vii) b. CM is the set of applications with moderate CRI Scores, moderate Value scores and moderate Risk scores CRI score, Risk Score and Value Score defined as CM = V Ci eC : £(£) < n(ACi, E) < U(E") ... equation (viii) c. CL is the set of applications with limited CRI Scores, limited Value scores and high Risk Score CRI Score and Value score defined as CL = V Ci€C : 0.5 <3?.(AQ,£) < £(E) ... equation (ix) Risk score defined as CL = V CiEC : U(E) < R(AQ,E) < 10 ... equation (x) d. And C = { Cv, CH, CM, CL, CZ} ... equation (xi) 10. 3i(ACi,E) U(E)