Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams

Dubuc, Timothee; Stahl, Frederic; Roesch, Etienne B.

doi:10.1109/access.2020.3046132

Cited by 16 publications

(6 citation statements)

References 78 publications

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“…Nevertheless, as the Internet of things develops, big data processing increases, while scholarly analytics help to evaluate the role of big data in technical processes. Researchers [15] have warned that the growth of the collection of technical network data and a rapid increase in the number of IoT devices can create difficulties for computer networks. To solve this problem, it is necessary to increase the maintenance service capacities for data processing infrastructure.…”

Section: Resultsmentioning

confidence: 99%

How Patents Influence Market Value of Industrial Enterprises' Assets?

Dementev¹

2021

КФ

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Scientists and engineers are continuously patenting innovative ideas such as inventions, industrial designs, and utility models. It is therefore relevant to pose the question of the influence of intellectual property in the field of innovative technologies on the market value of the assets of industrial enterprises. We analyse the dependence of the results of intellectual activity in the field of advanced technologies on the capitalization of innovative industrial production after the adoption of the developed technologies. We consider patent landscapes, analyse research publications, and study the dependence of financial indicators on the results of intellectual activity at enterprises producing computers, optics and electronic equipment. Our research methodology is based on the statistical analysis of the dependence of the financial results of industrial enterprises on the actual application of the results of intellectual activity to the technological process. We define the object of analysis by citing research articles and surveys from the WoS database. The patent landscape is assessed using data from commercial information systems such as Orbit Intelligence (Questel) and Amadeus (Bureau van Dijk, Moody’s Analytics) that make it possible to visually show the links between patent activity and technological trends in the computer and electronic technology industries. The research results shall be useful for assessing the effectiveness of employing patents in manufacturing and the prospects of improving production technologies for the formation of corporate innovative technological policy. We conclude that the use of information on patent trends is an effective tool for increasing the competitiveness of enterprises producing electronic equipment. The priority financing of innovative technologies ensures the sustainable development of the manufacturing industry and have a positive impact on the profitability of enterprise assets.

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Section: Resultsmentioning

confidence: 99%

How Patents Influence Market Value of Industrial Enterprises' Assets?

Dementev¹

2021

КФ

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“…This capability is essential in time-sensitive applications where rapid response is critical, such as in autonomous vehicles, industrial automation, and smart infrastructure. Real-time predictive analytics at the edge involves forecasting future events or trends based on current data streams (Dubuc et al, 2020). By leveraging historical data and ML algorithms, edge devices can predict potential outcomes and take preemptive actions to mitigate risks or optimize operations.…”

Section: Integration Of Analytics Into Edge Devicesmentioning

confidence: 99%

Reviewing the Transformational Impact of Edge Computing on Real-Time Data Processing and Analytics

Oluwole Temidayo Modupe,

Aanuoluwapo Ayodeji Otitoola,

Oluwatayo Jacob Oladapo

et al. 2024

Comput. sci. IT res. j.

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Edge computing has emerged as a pivotal paradigm shift in the realm of data processing and analytics, revolutionizing the way organizations handle real-time data. This review presents a comprehensive review of the transformational impact of edge computing on real-time data processing and analytics. Firstly, the review delves into the fundamental concepts of edge computing, elucidating its architectural framework and highlighting its distinct advantages over traditional cloud-centric approaches. By distributing computational resources closer to data sources, edge computing mitigates latency issues and enhances responsiveness, thereby enabling real-time data processing at the edge. Furthermore, this review explores how edge computing facilitates the seamless integration of analytics capabilities into edge devices, empowering organizations to derive actionable insights at the source of data generation. Leveraging advanced analytics algorithms, such as machine learning and artificial intelligence, edge computing enables autonomous decision-making and predictive analytics in real time, fostering innovation across diverse industry verticals. Moreover, the review examines the transformative implications of edge computing on various sectors, including healthcare, manufacturing, transportation, and smart cities. By enabling localized data processing and analytics, edge computing enhances operational efficiency, ensures data privacy and security, and unlocks new opportunities for business optimization and value creation. This review underscores the profound impact of edge computing on real-time data processing and analytics, revolutionizing the way organizations harness data to drive informed decision-making and gain competitive advantage in today's dynamic business landscape. As edge computing continues to evolve, its transformative potential is poised to redefine the future of data-driven innovation and digital transformation. Keywords: Edge, Computing, Analytics, Data, Impact, Review.

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“…This paper delves into the diverse array of analytical tools that define the Big Data landscape, ranging from traditional reporting to advanced analytics and machine learning algorithms. Traditional reporting and querying remain foundational components of analytical tools in the Big Data landscape (Dubuc et al,2020). These tools are characterized by their ability to generate historical reports and answer specific questions based on structured data.…”

Section: Analytical Tools In the Big Data Landscapementioning

confidence: 99%

Business Intelligence in the Era of Big Data: A Review of Analytical Tools and Competitive Advantage

Adebunmi Okechukwu Adewusi,

Ugochukwu Ikechukwu Okoli,

Ejuma Adaga

et al. 2024

Comput. sci. IT res. j.

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In the contemporary business landscape, the proliferation of Big Data has revolutionized the way organizations gather, process, and utilize information for strategic decision-making. This paper provides a comprehensive overview of the evolving role of Business Intelligence (BI) in harnessing the potential of Big Data and the subsequent impact on gaining a competitive advantage. The review delves into the arsenal of analytical tools that have emerged to handle the vast volumes of data generated in the digital age. From traditional reporting and querying to advanced analytics, machine learning, and predictive modeling, organizations now have a myriad of options to extract valuable insights from their data reservoirs. This paper investigates the efficiency, scalability, and adaptability of these tools in the context of Big Data, emphasizing their role in transforming raw data into actionable intelligence. Furthermore, the paper explores how the integration of BI and Big Data analytics contributes to the development of a competitive edge for businesses. The ability to harness insights from diverse data sources provides organizations with a holistic view of market trends, consumer behavior, and operational efficiency. This, in turn, empowers decision-makers to make informed and timely choices, enhancing overall organizational agility and responsiveness to market dynamics. The study also highlights the challenges associated with implementing BI in the era of Big Data, including issues related to data quality, security, and the need for skilled professionals. Effective solutions to these challenges are discussed, emphasizing the importance of a robust data governance framework and continuous investment in talent development. This paper underscores the pivotal role of Business Intelligence in leveraging the potential of Big Data for gaining a competitive advantage. As organizations navigate the complexities of the modern business landscape, the judicious use of analytical tools and the integration of BI with Big Data analytics stand as key drivers for informed decision-making and sustainable success. Keywords: Business Intelligence, Big Data, Analytical Tool, Business, AI, Review.

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Mapping the Big Data Landscape: Technologies, Platforms and Paradigms for Real-Time Analytics of Data Streams

Cited by 16 publications

References 78 publications

How Patents Influence Market Value of Industrial Enterprises' Assets?

How Patents Influence Market Value of Industrial Enterprises' Assets?

Reviewing the Transformational Impact of Edge Computing on Real-Time Data Processing and Analytics

Business Intelligence in the Era of Big Data: A Review of Analytical Tools and Competitive Advantage

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