Measurement Metric Proposed For Big Data Analytics System

Samosir, Ridha Sefina; Hendric, Harco Leslie; Gaol, Ford Lumban; Abdurachman, Edi; Soewito, Benfano

doi:10.1145/3168390.3168425

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The trade-off between costs and potential benefits is essential to select the best path and decide whether to continue with traditional schemes or to transform into the new one. Without proper organizational evaluation and preparedness, neither strategy is likely to succeed [70]. The big data approach is more appropriate to address or resolve business problems that meet one or more of the following criteria as depicted in the Fig.…”

Section: Preliminary Assessmentsmentioning

confidence: 99%

Big Data: Analytical Solutions, Research Challenges and Trends

Ali¹,

Novikov²

2020

Proceedings of ISP RAS

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The term Big Data refers to an extensive collections of digital data generating every second. Produced datasets come in structured, semi-structured, and unstructured formats throughout the world, which is difficult for the traditional database management systems to analyze. Recently, big data analytics emerges as an essential research area due to the popularity of the Internet and the advent of new Web technologies. This growing area of research represents a multidisciplinary that attracts researchers from various research fields. Interested researchers are invited to design, develop, and implement several tools, technologies, architecture, and platforms for analyzing these large volumes of data. This paper begins with a brief introduction to big data and related concepts, including the main characteristics of big data, followed by discussions of the most significant open research challenges and emerging trends. Next, we review a study of big data analytics, the advantages of using big data solutions, and the preliminary assessments required before migrating from traditional solutions. Finally, we present a review of the recent main applications to obtain a broad perspective of big data analytics.

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Section: Preliminary Assessmentsmentioning

confidence: 99%

Big Data: Analytical Solutions, Research Challenges and Trends

Ali¹,

Novikov²

2020

Proceedings of ISP RAS

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“…Reference [10] proposes the use of dynamic and static metrics for quantifying the behaviour related to the entity attributes in the Big Data environment. As a difference, our data stream strategy uses a formal measurement and evaluation framework, which includes an underlying ontology jointly with the process view for a detailed way in which the measurement process should be defined.…”

Section: Related Workmentioning

confidence: 99%

Extending the Data Stream Processing Strategy to Scenario Analysis

Diván¹

2019

IJATCSE

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The real-time data processing is continuously demanded by their implications in the real-time decision-making process. The data stream processing strategy implements an automatization of the measurement process based on a measurement and evaluation (M&E) framework for supporting real-time decision making. The decision making is based on the indicators, which have a set of decision criteria established by the experts in the domain in the initial M&E project definition. However, the decision criteria are not isolated from the context in which the decision should be made. This work introduces an extension for the data stream processing strategy, incorporating the scenarios as an interpretation related to the possible states of a context. The transition between scenarios is incorporated through the transition model, obtaining feedback from the processed data for adjusting the decision criteria and their interpretation in terms of the current context. A new complementary schema to the project definition is incorporated for supporting the extensions. In this way, the data stream processing strategy now is able to support the scenario definitions, transition analysis jointly with the possibility of fitting each indicator's decision criteria to each particular scenario. Finally, a scenario analysis based on the monitoring of outpatients is outlined.

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Articulating heterogeneous data streams with the attribute-relation file format

Diván

Reynoso

2019

ADVANCES IN ELECTRICAL AND ELECTRONIC ENGINEERING: FROM THEORY TO APPLICATIONS (SERIES 2): Proceedings of the International Con

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Measurement Metric Proposed For Big Data Analytics System

Cited by 3 publications

References 14 publications

Big Data: Analytical Solutions, Research Challenges and Trends

Big Data: Analytical Solutions, Research Challenges and Trends

Extending the Data Stream Processing Strategy to Scenario Analysis

Articulating heterogeneous data streams with the attribute-relation file format

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