System Analysis and Design Report

This report provides an in-depth analysis of system analysis and design, focusing on the integration of cloud computing solutions in healthcare IT. It discusses non-functional requirements, system qualities, interface requirements, and the software development life cycle (SDLC) approaches, including predictive and adaptive methods. The report concludes with recommendations for implementing cloud resources to enhance the management of patient records, emphasizing the benefits and challenges associated with cloud computing.

Running Head: SYSTEM ANALYSIS AND DESIGN
Assessment 3
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SYSTEM ANALYSIS AND DESIGN 2
Table of Contents
Introduction.............................................................................................................3
System’s non-functional requirements..................................................................3
System qualities......................................................................................................4
System interface.....................................................................................................4
UI and system interface requirements.................................................................5
System constraints..................................................................................................5
A review of the cloud solutions...............................................................................5
Strengths of cloud computing................................................................................6
Weaknesses............................................................................................................6
Protecting the project’s data...................................................................................6
Analysis of the SDLC Approach............................................................................7
Predictive approach................................................................................................7
Advantages of the approach................................................................................8
Disadvantages.....................................................................................................8
Adaptive method....................................................................................................8
Advantages of the approach................................................................................9
Disadvantages.....................................................................................................9
Recommendation.....................................................................................................9
Conclusion..............................................................................................................10
References..............................................................................................................11

SYSTEM ANALYSIS AND DESIGN 3
Introduction
As the demands for faster connectivity increases, the application of cloud facilities will also
increase to support the functional requirements of the end users. These facilities among many
other characteristics will offer flexibility benefits owing to their availability across the World
Wide Web. Moreover, they will be resilient because of the redundancy programs of the service
providers who will frequently set up multiple resources in different areas (Stantchev, Colomo-
Palacios, & Niedermayer, 2016). In addition to this, the technology will drastically reduce the
overall cost of operation as the end users (subscribers) will have minimal managerial roles.
These roles in today’s on-premise infrastructure will include the implementation functionalities
as well as the general maintenance operations, which are eliminated after the application of the
cloud facilities. Now, the project at hand requires extensive storage because of the growing
demands made by the patient’s records. Therefore, to meet this objective, the project aims to
integrate cloud resources into the proposed system. This report analyses this requirement where
the various aspects of cloud solutions are outlined.
System’s non-functional requirements
In system design, the non-functional requirements represent the general constraint of the
system’s functionalities. In essence, these requirements restrict the operations of the resources as
defined by the functional requirements (Chung, 2015). Furthermore, they will outline the process
in which the functionalities of a system are achieved i.e. the how of operations and not the
“what” of the system’s operations. In general, there are four main groups of the non-functional
requirements:
 Usability – a group of requirements that require the system to priorities its functionalities
based on the user application patterns i.e. the usage characteristics.

SYSTEM ANALYSIS AND DESIGN 4
 Reliability – the system ability to satisfy the user demands after a long time of operation.
 Performance - the system’s response to the user’s initial specifications and commands.
 Security – the ability to maintain the integrity of the system’s resources (Terzakis, 2012).
System qualities
There are specific minimal services and operations that the system must perform, these services
define the qualities of the system where certain distinctive attributes are highlighted. Moreover,
they specify the characteristics of the system from the end user’s perspective (Lévy & Ramdane-
Cherif, 2003). In this project, the following qualities must form the basis of its functionalities:
 Serviceability – the ease in which the system will be maintained while using a wide range
of monitoring activities.
 Latent capacity – considering the field of application, the system’s ability to handle
unusually high loads will facilitate its performance and usability.
 Availability – finally, the system should have a reasonable service time when the overall
resources are readily available to the end users (Gorton, 2011).
System interface
In the computing industry, an interface represents a general boundary area that separates several
computing components while facilitating the exchange of information. In this project, the main
system interface will be between the Headspace system and the cloud resources. This boundary
as highlighted above will facilitate the exchange of information between the end users and the
cloud storage resources (Mulo, 2007). Moreover, the system at hand will have another additional
interface that will deliver results to the end users (user interface). In both instances, the following
requirements will have to be met:

SYSTEM ANALYSIS AND DESIGN 5
UI and system interface requirements:
 Responsiveness and consistency – there are two factors that will determine these
requirements; first the response speed to user’s requests and secondly, the speed of giving
a functional feedback. Now, this responsiveness will also maintain the consistency of the
output functions.
 Familiarity – to improve the system’s intuitive outcomes, the interface should have
familiar structures and designs.
 Attractive (aesthetic appeal) – finally, the interfaces must be appealing to the eye to
continuously engage the user (Yoder & Wirfs-Brock, 2013).
System constraints
System constraints will occur in two main formats; the technical limitations and the business
restrictions. In the technical limitations, the functionalities of the system will be limited by
implementation elements and procedures such as new technologies and deployment platforms.
On the other hand, business restrictions will include items such as the cost and development
timelines (Terzakis, 2012).
A review of the cloud solutions
In this project, the cloud technology is being sorted out to increase the availability of resources.
Now, cloud computing will improve the delivery of IT resources through its defining
technologies that form part of wider service concept. In essence, the general technology will
have several foundational elements that will include IT resources such as hardware, software and
networks (Telkom, 2016). Therefore, their interoperability with the user’s system will dictate the

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benefits and weaknesses of the proposed solution. In this case, the following strengths and
weaknesses will be experienced as a result of the cloud facilities.
Strengths of cloud computing
i. Cost flexibility – the cost of using cloud solutions will vary from one application to
another depending on the user’s requirements. Therefore, the Headspace project will be
able to commission and thus pay for services they need.
ii. Increased mobility – first, the data of the Headspace system will be readily available after
being hosted online. Furthermore, the will also be able to move with their resources once
they are linked with the cloud servers.
iii. Enhanced collaboration – with cloud applications, the users (in this case the medical
practitioners) will collaborate their activities to generate better diagnosis and treatment
results (CTR, 2017).
Weaknesses
i. System downtime – when the online infrastructure is disrupted the overall service of the
cloud facilities are halted
ii. Security and privacy – the resources face many threats because of the nature of the cyber
environment where many threats are exhibited. Moreover, the resources are stored in
unknown locations which exposes them to unknown vulnerabilities (Tsagklis, 2013).
Protecting the project’s data
Patient’s records including their detailed stories will be hosted online which necessitates the need
to implement advanced security features. Furthermore, unlike the physical data, the virtualized
information will not abide by the legal stipulations of the land. Therefore, to protect the data
being used, the organization must first implement a standard security plan that will detail the
system’s authentication and encryption standards (Telkom, 2016). Moreover, the same plan will

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outline the access policies for the users who will have unique access parameters. In addition to
this, the organization must consult and enact legal agreements that spell out the responsibilities
of data processes which will include the ownership of the data.
Analysis of the SDLC Approach
System or software development life cycle is a procedure of designing, developing and
deploying software solutions. The overall aim of this procedure is usually to improve the quality
of the systems having met the user’s requirements and expectations. Now, to meet this objective,
the SDLC procedure follows a detailed plan that describes all the implementation stages of
software development (RBT, 2010). In this case, development phases such as planning, testing,
building and solution deployment are given. Furthermore, based on the defining user
requirements, the SDLC process can adopt several distinctive procedures which in the end
defines the types of SDLC i.e. the approaches/methods. This section highlights some of these
methods, the predictive and adaptive SDLC approach.
Predictive approach
This method can be defined as a classical approach to system design as it uses conventional
procedures to implement solutions. In essence, the approach will follow a logical and sequential
plan that will have minimal operation deviations. Furthermore, it will have pre-defined elements
for the system’s implementation which will include the user requirements and assumptions. In
all, the following features will generally characterize the method:
 First, it uses a predictable process to design systems where all the parameters are pre-
defined.
 Secondly, it is associated with a consistent implementation plan that will never change
after its documented (Okoli & Carillo, 2012).

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 Thirdly, the implementation phases are executed sequentially with minimal overlap
incidences.
Advantages of the approach
i. The method follows a logical pattern which makes it easy and simple to understand.
ii. Furthermore, its logical structure enhances the rigidity of the implementation procedure
which improves the management process.
iii. Finally, the approach is favourable for small projects which are easily managed and
implemented in a short period of time.
Disadvantages
i. First, it's very inflexible lacking the ability to adapt to changes such as those of system
requirements.
ii. Moreover, it contains a lot of risks and uncertainties because unknown variables easily
disrupt the entire process.
iii. Finally, it is not suitable for long-term projects as they tend to have many changes (GU,
2017).
Adaptive method
Now, this approach evolved from the classical methods in an attempt to fulfil the limitation of
their functionalities. In essence, the desire to have an agile and adaptable procedure led to its
development as it was able to accommodate any system changes. Furthermore, unlike the
predictive method, it does not predict and pre-define all the requirements of the system at a
single instance. Instead, it defines a logical development process while considering the
possibility of system variations (Okoli & Carillo, 2012). Moreover, it divides the development
process into several stages that are then executed simultaneously. In all, it has the following
features:

SYSTEM ANALYSIS AND DESIGN 9
 First, a logical plan having independent development phases is used.
 These phases then run concurrently based on the developers’ expertise.
 Finally, following their completion, the stage is assembled using several iterative
procedures.
Advantages of the approach
i. Risks and uncertainties are drastically reduced because the method accommodates any
variations or changes.
ii. Secondly, the method is time efficient as multiple stages can be implemented at the same
time.
iii. Its iterative procedures also improve the quality of the final systems as they are based on
the user’s immediate requirements.
Disadvantages
i. There is always the risk of failing to meet the implementation budget because of the
continuous accommodations made to the unknown system changes.
ii. It is also difficult to establish the exact timelines of implementation (Jamsheer, 2017).
Recommendation
In the analysis done above, the predictive approach has been identified as a method for
implementing short-term projects. This conclusion is based on its limitations that prevent it
adapting to system changes, a feature that characterize long-term projects. Furthermore, with its
well laid out plan, it cannot accommodate the features of the long-term project. Now, by any
definition, the Headspace system is a long-term project. For one its defining attributes are very
extensive and secondly, it has many user requirements. Moreover, the system requires the
integration of cloud facilities. Therefore, because of the limitations of the predictive method, the
adaptive approach is the best solution for the proposed project. Also, do remember that with an

SYSTEM ANALYSIS AND DESIGN 10
adaptive approach the developer risks of system uncertainties are drastically reduced which
based on the nature of the exiting project will characterize the development process (Okoli &
Carillo, 2012).
Conclusion
To the Headspace project, cloud resources offer the best solution to its existing problems of
managing patient’s records. These resources also extend the services of the organization by
delivering computing resources to all the users i.e. the members of the medical staff.
Furthermore, they drastically lower the expenditures of the organization by eliminating the
implementation and maintenance costs of the computing resources. Finally, they improve the
scalability of the storage facilities which based on the patient’s stories will regularly change.

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References
Chung, L. (2015). Non-Functional Requirements. Practices and Recommendations, Retrieved 03
October, 2017, from: https://www.utdallas.edu/~chung/SYSM6309/NFR-18-4-on-1.pdf.
CTR. (2017). Advantages and Disadvantages of Cloud ERP. Retrieved 03 October, 2017, from:
http://www.ctrworld.com/advantages-and-disadvantages-of-cloud-erp/.
Gorton, I. (2011). Quality Attributes; Software Quality Attributes. Essential Software
Architecture, Retrieved 03 October, 2017, from:
http://www.springer.com/cda/content/document/cda_downloaddocument/
9783642191756-c3.pdf?SGWID=0-0-45-1137943-p174111059.
GU. (2017). Pros and Cons of Predictive Analysis. Online programs, Retrieved 03 October,
2017, from: http://scsonline.georgetown.edu/programs/masters-technology-management/
resources/pros-cons-predictive-analysis.
Jamsheer, K. (2017). 12 Best Software Development Methodologies with Pros and Cons.
Acodez, Retrieved 03 October, 2017, from: http://acodez.in/12-best-software-
development-methodologies-pros-cons/.
Lévy, N., & Ramdane-Cherif, A. (2003). Quality Characteristics for Software Architecture.
JOURNAL OF OBJECT TECHNOLOGY, Retrieved 03 October, 2017, from:
http://www.jot.fm/issues/issue_2003_03/article2.pdf.
Mulo, E. (2007). Design for Testability in Software systems. Retrieved 03 October, 2017, from:
http://www.infosys.tuwien.ac.at/staff/emulo/pdfs/emmanuel_mulo_thesis.pdf.
Okoli, C., & Carillo, K. (2012). The best of adaptive and predictive methodologies: Open source
software development, a balance between agility and discipline. Research gate, Retrieved
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https://www.researchgate.net/publication/220490309_The_best_of_adaptive_and_predict
ive_methodologies_Open_source_software_development_a_balance_between_agility_an
d_discipline.
RBT, B. (2010). Systems Development Life Cycle: Objectives and Requirements. Retrieved 03
October, 2017, from: http://www.benderrbt.com/Bender-SDLC.pdf.
Stantchev, V., Colomo-Palacios, R., & Niedermayer, N. (2016). Cloud Computing Based
Systems for Healthcare. The Scientific World Journal, Retrieved 03 October, 2017, from:
http://downloads.hindawi.com/journals/specialissues/848162.pdf..
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df.

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Terzakis, J. (2012). Specifying Effective Non-Functional Requirements. Intel, Retrieved 03
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%20Specifying%20Effective%20Non-func.pdf.
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and cons. Retrieved 03 October, 2017, from:
https://www.javacodegeeks.com/2013/04/advantages-and-disadvantages-of-cloud-
computing-cloud-computing-pros-and-cons.html.
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