Open-Source Big Data Analytics Architecture for Businesses

Unaware of existing big data technologies, organizations fail to develop a big data capability despite its disruptive impact on today's competitive business environment. To determine the shortcomings and strengths of developing a big data architecture with open-source tools from technical and managerial perspectives, this study (1) systematically reviews the available open-source big data technologies to present a comprehensive picture, and (2) proposes an open-source architecture for businesses to take as a reference while developing big data analytics capabilities. Lastly, we discuss technical, domain-specific, and firm-specific soft challenges related to establishing a big data architecture in an organization, and how these challenges are reshaping the big data research domain.


Gökalp, Mert Onuralp; Kayabay, Kerem; Eren, Pekin Erhan; Koçyiğit, Altan (2016-12-17)
Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market, they are underutilized by organizations due to their complexities. Deployment and usage of big data analysis t...
Big data maturity models for the public sector: a review of state and organizational level models
OKUYUCU, ARAS; Yavuz, Nilay (Emerald, 2020-07-01)
Purpose Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level. Design/methodology/approach A literature search is conducted using Web of Science an...
Data Science Roadmapping: Towards an Architectural Framework
KAYABAY, KEREM; Gökalp, Mert Onuralp; Gökalp, Ebru; Eren, Pekin Erhan; Koçyiğit, Altan (2020-11-24)
The availability of big data and related technologies enables businesses to exploit data for competitive advantage. Still, many industries face obstacles while leveraging data science to overcome business problems. This paper explores the development of a roadmapping approach to address data science challenges. Towards this goal, we customize technology roadmapping by synthesizing roadmapping, big data, data science, and data-driven organization literature. The resulting data science roadmapping approach li...
Joint Virtual Machine Embedding and Wireless Data Center Topology Management
Bütün, Beyza; Onur, Ertan; Department of Computer Engineering (2022-5-10)
With emerging technologies such as the Internet of Things and 5G, generated data grows enormously. Hence, Data Center Networks (DCNs) have an important duty to store and process a significant amount of data, which makes them a critical component of the network. To meet the massive amount of traffic demands, wired DCNs need to deploy large numbers of servers and power-hungry switches, and huge lengths of wires. An enormous increase in the usage of cables causes high cabling complexity and cost while deployin...
Secure model for efficient live migration of containers
Mavuş, Zeynep; Angın, Pelin; Department of Computer Engineering (2019)
Cloud services have become increasingly widespread in the past decade due to their ability to reduce the complexity and cost of managing computers and networks. Cloud applications are run in virtualized environments such as virtual machines and containers to be able to allocate resources in an inexpensive manner. Both of these approaches require effective resource utilization, for which an important enabling technology is live migration, which involves moving a service from one host to another with the mini...
Citation Formats
M. O. Gökalp, A. Koçyiğit, and P. E. Eren, “Open-Source Big Data Analytics Architecture for Businesses,” 2020, Accessed: 00, 2021. [Online]. Available: