Information Requirements for Big Data Projects: A Review of State-of-the-Art Approaches

An Iterative Methodology for Defining Big Data Analytics Architectures

“…First, we reviewed some approaches based on requirements modeling techniques [1], [2], [15]. In [2] a bibliographic review of this kind of approaches is conducted. They conclude that the poor taking of requirements in Big Data projects as one of the causes of failure.…”

“…These requirements are used as an input for our proposed algorithm to generate an initial structure of the Big Data Pipeline. Afterwards, this structure is successively refined during the remaining phases (2)(3)(4)(5), where the selection of the most appropriate technologies and techniques is performed based on the analysis of the requirements identified during phase 1. Moreover, as this methodology is envisaged as an iterative methodology, in Section IV we describe the evaluation process that can be performed to refine the design of the Big Data Pipeline by iterating again through the different phases of the methodology.…”

“…I N recent years, the large number of publications on Big Data techniques [1]- [4], technologies [5]- [7] and applications [8]- [10], highlights the importance of the Big Data phenomenon in the field of data processing and analysis. Most researchers [2], [8], [11] define the concept of Big Data using the following features directly or indirectly, also known as the 3 V's of Big Data:…”

Conceptual modeling in the era of Big Data and Artificial Intelligence: Research topics and introduction to the special issue

“…Recently, there have been several methodological proposals [58,41,1,57,21] providing effective solutions that help practitioners to develop Big Data solutions. Most of these proposals are based on the analysis of the requirements derived from the 5V's or characteristics of Big Data, which helps with the definition of the Big Data pipeline.…”

“…Most of these proposals are based on the analysis of the requirements derived from the 5V's or characteristics of Big Data, which helps with the definition of the Big Data pipeline. Requirements modeling approaches [58,41] are based on the premise that one of the most common causes of the failure of Big Data projects is the lack of clear and measurable requirements. There are other approaches that use requirements modeling in combination with Data Warehousing (DW) techniques traditionally used in Business Intelligence (BI) systems [40,48,54].…”