Discussing Relations Between Dynamic Business Environments and Big Data Analytics

Abstract

Big data attracts researchers and practitioners around the globe in their desire to effectively manage the data deluge resulting from the ongoing evolution of the information systems domain. Consequently, many decision makers attempt to harness the potentials arising with the use of those modern technologies in a multitude of application scenarios. As a result, big data has gained an important role for many businesses. However, as of today, the developed solutions are oftentimes perceived as completed products, without considering that the application in highly dynamic environments might benefit from a deviation of this approach. Relevant data sources as well as the questions that are supposed to be answered by their analysis may change rapidly and so do subsequently the requirements regarding the functionalities of the system. To our knowledge, while big data itself is a prominent topic, fields of application that are likely to evolve in a short period of time and the resulting consequences were not specifically investigated until now. Therefore, this research aims to overcome this paucity by clarifying the relation between dynamic business environments and big data analytics (BDA), sensitizing researchers and practitioners for future big data engineering activities. Apart from a thorough literature review, expert interviews are conducted that evaluate the made inferences regarding dynamic and stable influencing factors, the influence of dynamic environments on BDA applications as well as possible countermeasures. The ascertained insights are condensed into a proposal for decision making, facilitating the alignment of BDA and business needs in dynamic business environments.

Business Analytics and Market Adaptation in the E-Commerce Industry in Nigeria

“…The reality of today's business environment, particularly that of e-commerce businesses, has shown a need to re-evaluate their business model based on the impact of the Covid-19 pandemic (Srinivas et al, 2020;Staegemann et al, 2020;Vidgen et al, 2020) including upgrading or re-aligning their digital infrastructure capabilities so they can be better efficient and be more flexible in adapting to the business environment and market changes. (Cirera & Muzi, 2020;Ekka, 2020;Seetharaman, 2020;Tim et al, 2020) in their work conclude that the survival of businesses in an era of global volatility and uncertainty heavily depends on adaptation capabilities and mechanisms that enable them to define appropriate responses to achieve market stability with zero, less, or minimal impact from the changes in the market.…”

Examining the Interplay Between Big Data and Microservices – A Bibliometric Review

“…Furthermore, there are two important research aspects, on the one hand, the use of big data to enhance microservices and, on the other hand, the utilization of microservices to realize big data applications. While both have their merits, especially the latter one could gain higher importance, since its allows to fulfil the rising need for flexibility in analytics solutions [13]. However, in either case, the development of the research should slowly move to more mature endeavors, resulting in a shift from the momentarily extremely predominant conference publications to more journal contributions.…”

“…This is even exacerbated by the circumstance that the business reality, including, for instance, the accessible sources, available algorithms and technologies as well as the type of questions whose answers promise benefit to the organization, might evolve over time, which also requires the BDA to adapt accordingly. As a result, a modular design, in contrast to a monolithic architecture, could be desirable [13]. One potential approach to achieve said modularity is the utilization of microservices as building blocks of the BDA solution as a whole [14]- [16].…”

Towards a Concept for Building a Big Data Architecture with Microservices

“…Contributing to this problem, the newly implemented algorithms and solutions might evolve over time, thus rendering the effort pointless, if the Big Data architecture is not adapted accordingly. This results in a rising demand for designs, which consist of building blocks that can be modified and replaced independently from each other, contrasting isolated implementations and applications [5]. Implementing microservices as the building blocks of Big Data architecture appears to be a feasible solution due to high degree of modularization [6].…”