Big Data Security Issues and Challenges

Kareem, Shahab Wahhab; Hasan, Aesha; Hawezi, Roojwan; Muheden, Karwan; Khoshaba, Farah S.

doi:10.4316/jacsm.202102004

Cited by 1 publication

(2 citation statements)

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“…Big data can be in the form of structured, unstructured, as well as semi-structured data accumulating in data stores from a variety of sources (Kareem et al, 2021;Saleh et al, 2018). Bekker (2017) is of the opinion that there are two sources of big data: internal sources (e.g.…”

Section: Sources Of Big Datamentioning

confidence: 99%

“…data on location, product price, transaction time, products purchased, payment methods etc.). According to Kareem et al (2021), big data sources include online sales transaction data, user feedback, social media posts, email messages, marketing data, and a variety of other log data which are related -directly and indirectly -to an organisation's business processes. Supporting this view, Bhadani and Jothimani (2016) commented that social media and video surveillance are also viable sources of big data due to technological advancements that have resulted in a high rate of data generation.…”

Section: Sources Of Big Datamentioning

confidence: 99%

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Estate Surveyors and Valuers’ Perception of the Role of Big Data in Property Marketing in Lagos, Nigeria

Oluwunmi

Role

Umeh

2022

INTREST

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Property marketing in Nigeria has frequently been characterised by unique challenges due to inadequate and unreliable data. In recent times, big data has presented a wide range of solutions to contemporary issues in different industries, including real estate. Notwithstanding, there is a paucity of practical studies on the role of big data in property marketing of many developing nations, including Nigeria. Hence, there is a need to investigate the role of big data in transforming property marketing in Nigeria. The aim of this study is therefore to investigate Estate Surveyors and Valuers’ (ESVs) perception of the role of big data in property marketing in Lagos, Nigeria. 82 questionnaires were administered to ESVs in the study area and 55 (67%) of them were found useful for analysis. The data were analysed using frequency, percentage, mean and relative importance index. The results revealed that out of 9 possible roles of big data in property marketing, the 2 most notable ones are that real estate firms can execute laser-focused marketing strategies; and they can match demand with supply. These outcomes distinctly disclosed the merits of adopting big data in marketing properties. The implication of these findings is that big data has the potential of reducing fraud due to the presence of sufficient and reliable data in the property market. This study concludes that big data is a worthy addition to the toolset of real estate practitioners, particularly with respect to property marketing, and wholly recommends its adoption.

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Section: Sources Of Big Datamentioning

confidence: 99%

Section: Sources Of Big Datamentioning

confidence: 99%