A model of multilayer tiered architecture for big data

  • Ordóñez Salinas S
  • Nieto Lemus A
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Abstract

Until recently, the issue of analytical data was related to Data Warehouse, but due to the necessity of analyzing new types of unstructured data, both repetitive and non-repetitive, Big Data arises. Although this subject has been widely studied, there is not available a reference architecture for Big Data systems involved with the processing of large volumes of raw data, aggregated and non-aggregated. There are not complete proposals for managing the lifecycle of data or standardized terminology, even less a methodology supporting the design and development of that architecture. There are architectures in small-scale, industrial and product-oriented, which limit their scope to solutions for a company or group of companies, focused on technology but omitting the functionality. This paper explores the requirements for the formulation of an architectural model that supports the analysis and management of data: structured, repetitive and non-repetitive unstructured; there are some architectural proposals –industrial or technological type– to propose a logical model of multi-layered tiered architecture, which aims to respond to the requirements covering both Data Warehouse and Big Data.

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APA

Ordóñez Salinas, S., & Nieto Lemus, A. C. (2016). A model of multilayer tiered architecture for big data. Sistemas y Telemática, 14(37), 23–44. https://doi.org/10.18046/syt.v14i37.2257

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