The Impact of big data on software design. Research Paper

Impact of Big Data on Software Design
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Impact of Big Data on Software Design
Abstract
Each software/application is designed for a particular purpose. The developer has to find the optimal design to ensure the software achieves its intended purpose. However, in the age of big data, developers have been forced to find new approaches to strike a balance in providing a product that can meet its utility objectives to the user and allow data collection and processing into a more meaningful form. This article has explored how big data has impacted software development to achieve the aforementioned objective. It also details secondary methodology design which has reviewed existing literature to find out the impact of big data on software development. Additionally, the article has further analyzed the secondary data and drew conclusions.
Background Information
The tech industry is increasingly mining data for varied reasons. It has sparked heated debates on the data utility. Many tech firms cite that big data projects are to enable them to develop more intuitive products and experiences for users. The opposers of big data cite that data mining has become very lucrative and tech firms are selling the information to third party companies to develop targeted ads to the users. However, as data mining has brought a new set of opportunities to the tech industry. Thus, big data has birthed a new form of software design in which the user’s end is simply packaged to collect the data and avail utility of the software over the internet. Thus, the software is largely hosted by the tech firms in their data repository and the continued utility of the software hooks the user to their system to enable them to continually collect data. The tech firms then develop algorithms and complex analytical software to enable them to sift, sort and process the data for their intended purpose. Thus, one of the primary ways in which data has impacted software development is through necessitating creating client-side applications which can simply be summarized as Software as a Service (SAAS) CITATION Anj17 \l 1033 (Anjum & Budgen, 2017). The client has little control over the abstracted information flow between the software/application and the servers which whilst milking data allow the user to continue using the software. It has presented a new set of challenges to software designers and developers. Software designers and developers now have to design products which can mine data and address the privacy concerns pertinent to big data. Software has to be designed to seamlessly relay that data securely and quickly to the storage centers. The client-side stubs are now hugely hinged on the internet for an operation which enables the tech companies to ensure the users are mostly on the internet to enjoy the utility of the software.
Statement of the problem
Developers have to build products which can collect a variety of information including textual, multimedia among others. The big data application has to be designed to ensure it collects a variety of data. The main tool for collecting user’s information is portable devices mainly smartphones. The software developers also have to ensure they build their application in such a way that it can run multiple smartphone operating system platforms. The application has to be custom designed for a smartphone considering it is limited by storage space, processing power among other limitations of the smartphone devices. The information collected has to be processed and analyzed on servers which run different operating systems. Thus, big data has complicated software development and has necessitated developers to learn how a single system meant to be deployed on multiple fronts to facilitate collection processing and analysis of the data.
Literature review
As the tech industry intensifies data collection, there is a compelling need to collect the data within the provisions of the law whilst protecting the user’s privacy. The world today is data-driven and it needs special processes to be processed for improving and diversifying utility and experience. Big data also requires multiple collection tools on the client-side and this has prompted user interface designers and developers to find the compromise between usability and utility. They have to ensure their product is usable and still serves to collect the data intended by the tech firm.
Big data requires developers to learn several programming languages to be able to develop for big data applications CITATION Pat16 \l 1033 (Hung, 2016). If it is a team, it has to bring on board several experts in several programming languages to successfully build a big data application. This is because big data applications are often meant to run on several platforms that need different programming languages to develop. For example, a team may need to have an android and iOS programmers to develop mobile phone application capable of collecting information from smartphones running those mobile phone operating systems. The application also needs a server-side which is supposed to process and analyze the data could be built using python programming language whilst the server’s operating system is Linux. Thus, to develop the application the developers ought to be proficient in all these programming languages.
Developers also need to learn how to feature ‘must-have’ features either in the interest of user’s privacy or to conform to data regulation policies on users’ data CITATION Kor12 \l 1033 (Davis, 2012). Many countries today have some form of regulation on data management and the developers must reflect these regulations in their products. Most of these regulations require encryption of the data on transit. Encryption is necessary to ensure the developer protects the user and their application from hackers. Other features that are necessary for inclusion is compression which allows the developers to reduce the size of the data before transit to save space on their servers and to ensure less resources are required to store and transport the information. The tech forms also may wish to protect their clients from mass surveillance by the government and thus they introduce features to ensure their client’s data is safe. These requirements have to be reflected in the application and they must be implemented by the software developer.
The future of technology is mainly predicted to be artificial intelligence and the internet of things. Tech firms and developers have to develop products that are aligned with the future of technology. Therefore, most big data developers have to design and develop products that allow some degree of artificial intelligence and or applications that can harness the opportunities of IoT CITATION Pra17 \l 1033 (Krishna, 2017). IoT is mainly to increase the data collection pool to encom...