Good quality is what makes a system useful. High-quality software is achieved by implementing non-functional requirements such as reliability, security, efficiency, maintainability and modifiability, etc. These attributes are not addressed in the design phase, so they should be reflected in the architecture phase. Therefore, an architecture focused on the implementation of non-functional requirements that leads to the development of effective and high-quality software is needed. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay This article offers a standard process. Their approach is based on the PEAK (Pre-positioned Expeditionary Assistance Kit). They conducted quality attribute workshops where requirements are organized in the form of quality attribute scenarios. Each quality attribute is assigned a BG (Business Goal). The scenarios are then further refined and prioritized. Prioritization has three scales (Low, Medium and High). Once these scenarios have been finalized, we proceed with the design of the Architecture via Attribute-driven Design (ADD). It is stated that non-functional quality is very important for the success of the project. Non-functional requirements (NFRs) are less relevant to customers but are the primary concern for software architects. And these non-functional requirements are very important for the functionality of the system. The study focused on 13 software architects working in a Spanish organization. Several research questions were posed to the architects through interviews. The results of these questions revealed that for functional requirements, the main source of requirements is the users or customers who are actually the domain experts, while for non-functional requirements the architect becomes dominant. Some interviewers believe that software architects see themselves as the real experts in defining non-functional attributes, such as efficiency, reliability, security, etc. Interviewers also stated that non-functional requirements are not often documented and if they are the documentation will not always become accurate. The purpose of their study is to reveal the actual practices used in industries regarding non-functional requirements. As the project grows, it becomes more difficult to estimate the effort required during the development phase. Based on recent past work, the authors use information quality theory to estimate these efforts. The authors implemented the quality model with respect to the four aircraft development programs C-130 AMP, EA-18G, MQ-9 and BAMS. The behavior of the binomial transition probability on three of the four programs indicates that there is an impact on the outcome of architecture reuse. Furthermore, the behavior of the conversion rate metric across the four programs indicates that the metric can capture the “momentum” of the architecture as they gain experience. This study ensures the quality of social media data. They provided a solution to data evaluation by which a user can evaluate the quality attribute with evaluation metrics. Quality evaluation metrics are divided into three categories based on the type of information. These are content-based metrics, context-based metrics, and evaluation-based metrics. Data evaluation is conducted at different data processing stages of big data architecture, passing through the pipeline of a big data system. They use big data architecture from other researchers' work, they added.