Quality assurance in big data analytics: An IoT perspective
subject: Big data; Data quality; Data testing; Internet of things (IoT); IoT data validation; Quality of service (QoS)
description: Emergence of IoT as one of the key data contributors in a big data application has presented new data quality challenges and has necessitated for an IoT inclusive data validation ecosystem. Standardized data quality approaches and frameworks are available for data obtained for a variety of sources like data warehouses, webblogs, social media, etc. in a big data application. Since IoT data differs significantly from other data, challenges in ensuring the quality of this data are also different and thus a specially designed IoT data testing layer paves its way in. In this paper, we present a detailed review of existing data quality assurance practices used in big data applications. We highlight the requirement for IoT data quality assurance in the existing framework and propose an additional data testing layer for IoT. The data quality aspects and possible implementation models for quality assurance contained in the proposed layer can be used to construct a concrete set of guidelines for IoT data quality assurance. 2019 Telecommunications Society and Academic Mind.
creator: Fernandes N.A.; Wagh R.
source: Telfor Journal, Vol-11, No. 2, pp. 114-118.
publisher: Telecommunications Society and Academic Mind
date: 2019-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 18213251
format: Online
language: English
type: Article
coverage: Fernandes N.A., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Wagh R., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India