Open AccessEvaluative Review of Streaming Analytics: Tools and Technologies in Real-Time Data Processing
Author(s) -
Shailaja B. Jadhav,
D. V. Kodavade
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-1262
Subject(s) - analytics , computer science , stream processing , big data , data science , business intelligence , data stream mining , data analysis , field (mathematics) , business analytics , predictive analytics , software analytics , data stream , data mining , distributed computing , business model , telecommunications , software construction , mathematics , software , marketing , software system , pure mathematics , business , business analysis , programming language
Nowadays, big data processing systems are evolving to be more stream-oriented; where each data record is processed as it arrives by distributed and low latency computational frameworks [18]. Data streams have been extensively used in several fields of computational analytics such as data mining, business intelligence etc. [17]. In every field, the data stream can be considered as an ordered sequence of data items, as they continuously arrive over the period. Due to this characteristic, streaming data analytics is a challenging area of research [5, 11]. This paper aims to present data stream processing as a growing research field , along with streaming analytics frameworks as a rich focus area. The paper also contributes to evaluate the efficacy of available stream analytics frameworks. One of the Industry 4.0 use case - predictive maintenance rail transportation - has been illustrated here as a case study design mapped with streaming analytics framework.