Business System Development Life Cycle †MyAssignmenthelp.com

Question: Discuss about the Business System Development Life Cycle. Answer: Introduction While information systems manage users data, the modern requirements demand other extended services because of the prevalence of the digital environment. In todays digital system, the demands of information availability and accessibility are higher than ever before because of the various technologies that can support this requirement. Virtualization is one such technology where resources management are delivered to end users using virtual infrastructure i.e. the internet. Moreover, the concepts of virtualization are well exhibited by cloud computing which today is the leading service provider in terms of ICT resources. Now, this outcome is as a result of the benefits it provides including extended resource availability and accessibility, functionalities that are necessary for modern ICT infrastructures(Rackspace, 2017). Similarly, the Headspace project aims to improve its proposed information system by incorporating cloud computing in order to increase the availability of information among its staff and patients. This report analyzes this requirement from a design perspective and offers recommendations on the design structure so as to meet the needs of the user. Lets start by distinguishing these factors with those of the functional requirements, non-functional requirements are elements or factors that are used as the criteria of judging the system performance. In essence, the fulfilment of these requirements enhances the user's operations which improve their interaction with the overall system(Microsoft, 2017). This definition is different from functional requirements that define the functionalities and capabilities of the system. In this section, we highlight these elements based on the FURPS+ reference. These are the factors that affect the systems design so as to influence the experience of the user and the packages run-time behaviour. In this case, they will determine the Headspace projects impact which will enhance the system application in different user platforms(Chung, 2012). The qualities are: Design qualities: conceptual integrity is the key component here where the systems components must be coherently integrated into the implementation process. Supportability: a factor that dictates the overall systems support control features through the elements put in place to resolve operational issues. User qualities i.e. usability: the Headspace system must meet the requirements of the end user, this ability defines the systems usability. Runtime qualities: Performance, reliability and security Performance is the indication of the softwares responsiveness while the reliability is the ability to withstand attacks based on a consistent operation. Finally, the security where the elements of cloud computing will emphasize the need for authorization, authentication and encryption. In essence, security is an element determined by the safety of the data management used as well as its ownership(Lowey, 2017). User interface (UI) and system interface UI is the main component of the GUI (graphical user interface) which generally represents the entire system to the end user. UIs non-functional requirements are only met if the systems interface is designed using a user-centred approach in order to improve its overall impact(Hassan, 2015). This design leads to the following qualities: System accessibility and availability the systems agility and flexibility will improve its overall access as the user will be able to apply it across different platform e.g. different operating systems. Reliability and consistency accessing the Headspace system should be a consistent operation irrespective of the platform used. Aesthetic appeal the system should be appealing to the eye based on the interaction of the different elements of the interface i.e. colour, font and images. Budget - because of the minimal resources available and even the time limitations of implementing the system. Technical integration - because of the different platforms and user preferences needed(Taylor, 2000). Cloud-based solutions Cloud computing is without a doubt the next evolution of the internet which will provide dynamic resources to the end users based on their immediate demands of accessing online services. Now, the Headspace project requires these resources to facilitate the storage of the patients stories and diagnostic information. In essence, the project requires a versatile system that will adjust its functionalities to suit those of the users as they will change from time to time. Moreover, the patients may visit more than one healthcare worker which necessitates an agile system management that can be accessed at all fronts. Cloud computing offers these elements through its functional infrastructure that is based on the internet. Now, considering the system will be deployed online (which is a public environment), the various aspects of cloud computing come into play which influences its strengths and weaknesses(Chappelle, 2008). High accessibility and availability so long as the users (Headspace) have access to the internet the resources (patients records) will be readily available. Moreover, the users can access them from any digital platform. Flexibility and mobility moving the data and user resources from one location to another are easily accomplished as the service provider offers the services in multiple locations. Cost savings finally, the project will minimize the implementation and maintenance cost because the service provider will cater for them all. The user will just perform the end user roles i.e. front-end functionalities(cloud., 2017). Data security a key element of this project due to the sensitive nature of the data which will be mostly patients records. Cloud computing operates within a public domain which makes it difficult to manage because the user is unable to track their resources. As a response, the Headspace project must integrate advanced encryption standards to limit the number of those accessing the system management. Moreover, they should employ authentication features to improve the systems accountability(Alton, 2015). System control and data ownership At the end of the day, the service provider controls the overall system regardless of the service model used. This outcome makes it difficult to manage the resources as the user cannot tag or track their facilities adequately. As a solution, the Headspace project may consider custom SLAs (service agreements) that could stipulate their roles in handling their data so as to understand their legal limitations. Furthermore, extremely sensitive resources should be hosted in the on-premise equipment. System development life cycle (SDLC) There are usually very many variables to consider during the development process of a system. These variables will include elements such as non-functional requirements which have been given above and functional requirements among many others. Now, while system developers may have the necessary expertise to meet the implementation demands, their functionalities depend on design structures and procedures that aid the process(Stoica, Mircea, Micu, 2013). Therefore, SDLC denotes the overall procedure of designing and developing software systems where the roles of planning, creating and even deploying are outlined to fit the immediate needs of the proposed system. A similar approach will be used in the Headspace project, where a wide range of methods may be used to develop it. In essence, these methods will define the projects SDLC and may include the two proposed approaches i.e. predictive and adaptive SDLC. A traditional method that uses conventional concepts to implement systems that have minimal functional and non-functional requirements. The predictive method was the initial approach developed by systems developers to aid their functionalities. Now, at the time of its development, there were minimal system requirements which made it easier to predict the different elements of the software systems(business, 2011). To date, the same guidelines are still in existence as a predictable approach generally defines the modern predictive SDLC method. In essence, the approach will start by defining all the parameters of the system, from functional requirements to user preferences. Moreover, these elements are never changed after being identified and stipulated. From the pre-defined elements, a sequential procedure having logical implementation stages is used to develop the system. Now, this procedure does not deviate from the sequential flow of events as its structure depends on the logical outcomes of each stage. Therefore, overlaps are prohibited which limits the flexibility and diversity of the overall system. Due to this pre-defined structure, the following advantages and disadvantages are experienced(Okoli Carillo, 2010). Pros of the predictive approach It's an accountable approach because it uses a stringent documentation process. Secondly, it's simple and easy to use as all requirements are given before the start of the implementation process. Thirdly, its predictable approach enhances collaboration because all the implementation stages are known(Peru, 2014). An inflexible approach that does not respond to changes. Furthermore, all the development stages run sequentially without overlap which consumes a lot of time. A modern approach that follows dynamic procedures to implement systems based on the immediate demands of the users. Unlike the predictive method, the development procedures are not limited to a single track and may deviate depending on any changes given. Nevertheless, the approach will define a proper design structure consisting of different implementation stages. These stages will outline the different requirements of the system including the functional and non-functional elements. Furthermore, the approach will facilitate the concurrent execution of these stages without following a sequential flow of events(business, 2011). Thereafter, the implementation stages will then be assembled to yield the final system consisting of all the user requirements. Now, the approach will use iteration techniques to assemble the different stages, an outcome that improves the final system. Pros of adaptive approach Its a flexible design method that is able to adapt to any changes. Secondly, it's time efficient as developers can share responsibilities and execute different implementation stages concurrently. Moreover, it offers a user-centred approach that caters for every users needs thus improving the overall system performance and usability. A predictive approach offers the benefit of accountability because the stages of system development are critically given depending on the user's needs. However, its benefits generally end there having extensive limitations more so, with regard to modern systems. On the other hand, the adaptive approach encapsulates all the features of a modern system having the necessary agility and flexibility to adapt to changes(Stoica, Mircea, Micu, 2013). Therefore, during the development stages, the project at hand can introduce new features and requirements without affecting the systems functionalities. Furthermore, its agility would improve the integration outcomes of the system with the cloud resources. Therefore, the adaptive approach is the best SDLC method to use in the Headspace project. Conclusion In this report, the differences between the functional requirements and non-functional requirements have been given. In essence, the functional requirements dictate the capability and functionality of the system. However, the non-functional requirements determine the users judgment with regard to the systems operations. Therefore, factors such as performance, usability, security and reliability must be fulfilled to facilitate a positive user judgment. Furthermore, the systems integration with the cloud facilities is necessary owing to the requirements given by the project. However, this integration should adhere to the guidelines given to protect the data and resource used. References Alton, L. (2015). Cloud computing Pros. IT business edge, Retrieved 28 September, 2017, from: https://www.smallbusinesscomputing.com/biztools/the-pros-and-cons-of-cloud-computing.html. business, M. s. (2011). The System Development Life Cycle. Retrieved 29 September, 2017, from: https://utexas.instructure.com/courses/1166782/files/38198507/download. Chappelle, D. (2008). A SHORT INTRODUCTION TO CLOUD PLATFORMS. AN ENTERPRISE-ORIENTED VIEW, Retrieved 28 September, 2017, from: https://www.davidchappell.com/CloudPlatforms--Chappell.pdf. Chung, L. (2012). Non-Functional Requirements. Retrieved 28 September, 2017, from: https://www.utdallas.edu/~chung/SYSM6309/NFR-18-4-on-1.pdf. cloud., L. (2017). Advantages and Disadvantages of Cloud Computing. Retrieved 29 September, 2017, from: https://www.levelcloud.net/why-levelcloud/cloud-education-center/advantages-and-disadvantages-of-cloud-computing/. Hassan, A. (2015). Software Architecture. CISC 322, Retrieved 28 September, 2017, from: https://research.cs.queensu.ca/~ahmed/home/teaching/CISC322/F09/slides/CISC322_02_Requirements.pdf. Lowey, R. (2017). Non-functional requirements. Scaled agile framework, Retrieved 29 September, 2017, from: https://www.scaledagileframework.com/nonfunctional-requirements. Microsoft. (2017). Chapter 16: Quality Attributes. Retrieved 29 September, 2017, from: https://msdn.microsoft.com/en-us/library/ee658094.aspx. Okoli, C., Carillo, K. (2010). The best of adaptive and predictive methodologies: Open source software development, a balance between agility and discipline. Retrieved 28 September, 2017, from: https://chitu.okoli.org/media/pro/research/pubs/OkoliCarillo2010IJAESD.pdf. Peru, G. (2014). Software Development Life Cycle. GSL Peru , Retrieved 28 September, 2017, from: https://gsl.mit.edu/media/programs/peru-summer-2014/materials/t04-_software_development_life_cycle.pdf. Rackspace. (2017). Understanding the Cloud Computing Stack: SaaS, PaaS, IaaS. Support networking, Retrieved 29 September, 2017, from: https://support.rackspace.com/white-paper/understanding-the-cloud-computing-stack-saas-paas-iaas/. Stoica, M., Mircea, M., Micu, G. (2013). Software Development: Agile vs. Traditional. Informatica Economic?, Retrieved 29 September, 2017, from: https://www.revistaie.ase.ro/content/68/06%20-%20Stoica,%20Mircea,%20Ghilic.pdf. Taylor, A. (2000). Constraints and Limitations. Introduction, Retrieved 29 September, 2017, from: https://www.cse.msu.edu/~cse470/F97/Projects/F00/F00-Cheng/diagnostics/diagnostics2/web/documents/designdoc/document/node5.html.