Introduction
The multistep process of developing and implementing an information system is referred to as the System Development Life Cycle. There are various SDLC models with each consisting of a series of defined phases or steps. This paper discusses two types of System Life Cycle Models: Seven steps model and the spiral model.

Seven step model
Planning
The objectives and requirements of the project are determined at the planning step. An estimation of resources including costs and personnel is also made in relation to the proposed project. The available information is analyzed, and alternative solutions are considered. When the most viable alternative is arrived at, the information is put together into a project plan. (Jeremy, 2008)

System Analysis
The end user requirements are determined at this phase. The project team determines the end-user requirements with the assistance of customer focus groups, which present their needs and expectations on the system and how it will perform. The needs and requirements are documented in this phase. (Jeremy, 2008)

System design
The design step is the architectural phase of system development. Charts are used to show the flow of data processing, and the project team establishes the most logical design. The operations and functions of the system under development are described in detail during this phase. Reviews on the design are also conducted to ensure the design addresses efficiency, practicality, cost, security, and flexibility. (Jeremy, 2008)

System development
During the system development phase, the system developers execute the requirements of the design step. Actual user interface screens and database are designed by the developers, the code for the data flow process are also generated in this phase. The system development phase entails the conversion of the detailed design into a finished product. (Jeremy, 2008)

Testing phase
The testing phase involves the testing of all aspects of the system for performance and functionality. The whole system is tested for integration with other products and other previous versions with which it requires interacting. Fundamentally, the main purpose of the testing step is to validate that the system includes all the end user requirements reflected in the analysis step. Additionally, the testing phase also ensures that all the functions are accurately functioning; that the system is aligned to the standards of the business and the end users and that the system works with all other systems including the previous systems. (Jeremy, 2008)

Implementation Phase
The implementation phase entails the deployment and installation of the system in end user’s premises, ready to become running. End user training may be required to ensure that they can effectively use the system. The length of implementation is dependent on the complexity of the system.

Maintenance Phase
The maintenance phase is carried out on a periodic basis to ensure that the system does not become obsolete. Maintenance involves continuous evaluation of system’s performance. It also entails providing latest updates for particular system components to ensure that it meets the right standards. (Jeremy, 2008)

Spiral model
The Spiral Lifecycle model is comparable to the Incremental model except that it incorporates a risk analysis process. A project passes through four phases repeatedly in sequence in spirals. Critical requirements are identified for the first spiral at the start of the process while the Subsequent spirals add functionality to the baseline spiral. (University of Maryland, 2007)

Planning Phase
The business clearly defines its high-level requirements and project goals during this phase. The need and purpose of the system are also established and documented during this step. Key rules are also identified here in the initiation phase. The planning phase entails defining timelines, resources and other project related information. Interviews are conducted to help in developing a comprehensive system that fits users’ requirements. (University of Maryland, 2007)

Risk Analysis
The risk analysis step is fundamental to assess both management and technical risks associated with the project. Risks are identified, and alternative solutions are developed to address factors that may deter the successful completion of the system. (Shelly & Harry, 2009)

Engineering step
A representation of the system is built at this phase. A prototype is tested against the risk evaluated based on the expectations of the end users. The prototype is refined and rectified until end user expectations are achieved.

Evaluation
The final system is thoroughly evaluated during this step. End user feedback is required on which to base the evaluation.

The figure shows spiral model representing four phases; planning, risk analysis, engineering, and evaluation. The radius component represents the project cost while the angular component represents the progress in the current spiral.

Comparing the two models
Spiral Life Cycle Model represents a very flexible system lifecycle model. The seven step model is a rigid life cycle model system on the other hand. The project manager in a spiral model can determine the development phases according to the complexity of the project. The spiral model is transparent as Project monitoring is very effective and easy given that each phase and each loop is reviewed by concerned people. The seven step model does not allow much interaction with the end users during its development. This makes it less transparent. Gary (Shelly & Harry, 2009)

The spiral model is more attractive compared to the seven step model as Risk Management is an inbuilt feature of the model. In a spiral model, alterations can easily be introduced later in the life cycle. Coping with such changes isn’t a difficult task for a spiral model project manager. The introduction of changes in the seven step model presents a difficulty.

Spiral models are appropriate for high-risk projects, where business requirements may be unstable. They are not suitable for low-risk projects. Seven step models suit low-risk projects where projects are not exposed to high risks to warrant detailed risk analysis.

Spiral Model usually involves high cost compared to the seven step model. Seven step models are cheaper since risk analysis is not fundamental to the development process. They do not also require expertise to carry out these steps. (Valacich et al, 2015)

Protocols and Rules need to be followed properly to successfully implement the spiral model. The factor makes it tough as they should be followed throughout the span of the project. Seven step model is easy to develop rules, and protocols are not detailed or complex. In the spiral model, using the same prototype in future presents a difficulty as a result of various customizations allowed from the client.

It is necessary for researchers to ensure that they avoid research bias. Biases are likely to occur when a researcher is evaluating the results of the data collected. Bias normally results from the systematic alteration of the truth. However, a researcher may avoid biases when evaluating the results of data collected through ensuring that they use the collect statistical techniques. The researcher may be able to avoid biases through ensuring that they clearly understand all the statistical techniques that they are planning to use when collecting data. According to Gerhard (2008), researchers can avoid bias through multivariate analysis. The multivariate analysis normally applies mathematical models in assessing the association of multiple predictors of an outcome. In this case, the estimate for every variable reflects the individual association of the variable with the outcome. The use of the regression model during analysis tends to produce unbiased results for the variable of interest when all the confounders adequately measured and the model correctly specified. In this way, the research will be able to avoid biases when they are evaluating the results. Triangulation is also another strategy for avoiding bias in research (Liu & Fellows 2009). The research may verify the results using other data sources. A research can find other data sources that support the results of the data collected. In this way, it is possible to ensure confidence and avoid bias.

Sample size
During a research, using the correct sample size is normally crucial. A sample that is too big can lead to a waste of precious research resources such as money and time, and a sample that is too small may not allow the research to gain reliable insights. Scholars should determine the sample size of for their research by determining how they want their study results to match that of the entire population (Parket & Rea 2014). The sample size must be representative in that it will allow the research to generalize the study findings to the wider population. So as to determine how large or small the sample size of the study, the research should do the margin of error and confidence level. In the margin of error, there is no sample that is perfect; however, one must decide how much error to allow (LeBlanc, 2004). The margin of error determines how much lower or higher than the population mean a research is willing to let the sample mean fall. The researcher also uses the confidence level in determining how often the population percentage lies within the boundaries of the margin of error.

Limitations
Limitations normally affect almost all research projects, and they are the potential weaknesses that are mostly out of the researcher’s control (Gerhard, 2008). It is necessary to know that limitations of a dissertation are normally not something that the researcher can resolve. Thus, even with the obvious limitations, it is acceptable to consider the study and the results of the study authentic. When conducting a study, it is necessary to remember that whatever limits you also limit other researchers. A research study might have limitations such as having access to just one certain people in the organization, certain data, and certain documents. These are some obvious limitations in a research study; however, that does not mean that the study results are not authentic. There will always be some limitations when one is conducting the study; however, those limitations do not make it unacceptable to use the study results (Wiersma, 2000). In this case, the researcher can use the study results and apply to that particular group of people despite that the study focused.

Evaluating data
Data evaluation usually helps the researcher to gain an understanding of the collected data. When evaluating data that is contrary to the results of other studies on the topic, the researcher must consider several factors. In this case, it is significant to consider, what the researcher was trying to learn, whether the study collected the relevant information if data is sensible, and if the right things were measured. During evaluation of the data, the researcher must ensure that he considers the variables included in the study when evaluating the data (Grinnell & Unrau 2010). The data that the researcher garnered from the research participants is what will help the researcher to understand the data collected. When evaluating data that is contrary to the results of other findings on the topic, the researcher can also consider determining some of the factors that would have caused the different. It might be the environment, the time span, or even the people involved in the study (Gerhard, 2008). Hence, putting these factors into consideration when evaluating data will help one to understand the data and also know why the findings may differ despite the topic being the same. The time span can be a major reason for the difference; thus, when evaluating data, the researcher should consider the time difference in the study. Maybe the studies done on the topic were several years ago and because of the current changes it may be the cause of the difference.

Preparing for the Project Management Professional (PMP) exam can be a daunting task for many individuals. The sheer volume of material to cover, coupled with the pressure to pass, often leads to high levels of stress and anxiety. However, it is possible to approach the PMP exam in a way that minimizes stress and even makes the process enjoyable. By implementing effective study strategies, managing time wisely, and maintaining a positive mindset, individuals can navigate the PMP exam preparation journey with ease.

Effective Study Strategies
One of the keys to making the PMP exam enjoyable is to develop and implement effective study strategies. Rather than trying to memorize large amounts of information all at once, it is beneficial to break the material down into smaller, more manageable chunks. Creating a study schedule that allows for regular review sessions over an extended period of time can help reinforce key concepts and prevent cramming, which often leads to increased stress. Additionally, considering the best PMP certification in Pune can provide valuable insights and resources for exam preparation.

Additionally, utilizing a variety of study resources can make the learning process more engaging and enjoyable. This may include textbooks, online courses, practice exams, and study groups. Experimenting with different study methods, such as flashcards, mind maps, or mnemonic devices, can also help individuals find what works best for them and keep the material interesting.

Time Management
Managing time effectively is essential when preparing for the PMP exam. Setting aside dedicated study sessions each day or week and sticking to a predetermined schedule can help ensure that progress is made consistently over time. Breaking down the material into smaller, more manageable tasks and setting specific goals for each study session can also help individuals stay focused and motivated.

It is important to prioritize studying but also to allow time for rest and relaxation. Taking regular breaks during study sessions and scheduling time for leisure activities can help prevent burnout and maintain a healthy work-life balance. By managing time wisely and maintaining a realistic study schedule, individuals can reduce stress and approach the PMP exam with confidence.

Positive Mindset
Maintaining a positive mindset is crucial when preparing for the PMP exam. Rather than focusing on the challenges or potential obstacles, individuals should try to adopt a growth mindset and view the exam as an opportunity for personal and professional growth. Recognizing and celebrating small victories along the way can help build confidence and keep motivation levels high. Additionally, seeking out the best PMP course in Bangalore can provide structured guidance and support throughout the preparation journey.

It is also important to practice self-care and prioritize mental and emotional well-being during the exam preparation process. Engaging in activities that promote relaxation and stress relief, such as exercise, meditation, or spending time with loved ones, can help individuals stay centered and resilient in the face of challenges.

Preparing for the PMP exam does not have to be a stressful or unpleasant experience. By implementing effective study strategies, managing time wisely, and maintaining a positive mindset, individuals can approach the exam with confidence and even find enjoyment in the process. By breaking down the material into smaller, more manageable chunks, utilizing a variety of study resources, and setting aside dedicated time for study and relaxation, individuals can navigate the exam preparation journey with ease. Ultimately, with the right approach and mindset, success on the PMP exam is achievable without unnecessary stress or anxiety.