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A Framework to Evaluate Big Data Fabric Tools

A Framework to Evaluate Big Data Fabric Tools
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Author(s): Ângela Alpoim (University of Minho, Portugal), João Lopes (University of Minho, Portugal), Tiago André Saraiva Guimarães (University of Minho, Portugal), Carlos Filipe Portela (University of Minho, Portugal) and Manuel Filipe Santos (University of Minho, Portugal)
Copyright: 2021
Pages: 12
Source title: Integration Challenges for Analytics, Business Intelligence, and Data Mining
Source Author(s)/Editor(s): Ana Azevedo (CEOS.PP, ISCAP, Polytechnic of Porto, Portugal) and Manuel Filipe Santos (Algoritmi Centre, University of Minho, Guimarães, Portugal)
DOI: 10.4018/978-1-7998-5781-5.ch009

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Abstract

A huge growth in data and information needs has led organizations to search for the most appropriate data integration tools for different types of business. The management of a large dataset requires the exploitation of appropriate resources, new methods, as well as the possession of powerful technologies. That led the surge of numerous ideas, technologies, and tools offered by different suppliers. For this reason, it is important to understand the key factors that determine the need to invest in a big data project and then categorize these technologies to simplify the choice that best fits the context of their problem. The objective of this study is to create a model that will serve as a basis for evaluating the different alternatives and solutions capable of overcoming the major challenges of data integration. Finally, a brief analysis of three major data fabric solutions available on the market is also carried out, including Talend Data Fabric, IBM Infosphere, and Informatica Platform.

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