Universiti Teknologi Malaysia Institutional Repository

ADiBA big data adoption framework: accelerating Big Data Revolution 5.0

Daut, Norhayati and Salim, Naomie and Chan, Weng Howe and Zainal, Anazida and Huspi, Sharin Hazlin and Ghazali, Masitah and Ahmad, Fatimah Shafinaz (2022) ADiBA big data adoption framework: accelerating Big Data Revolution 5.0. In: 11th International Conference on Data Science, Technology and Applications (DATA), 11 July 2022 - 13 July 2022, Lisbon, Portugal.

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Official URL: http://dx.doi.org/10.5220/0011351700003269

Abstract

Researchers have formulated the revolution of Big Data into several stages, from stage 1 using raw data until stage 5 using operational intelligence and advanced analytics is used to provide wisdom. However, for organisations to reap the values from big data adoption and implementation, they must embrace Big Data Revolution 5.0: digital acceleration. At this stage, Big Data Analytics (BDA) becomes an asset from which, businesses can get new insights and aid value creation, resulting in increased profits. BDA will play a large part in extending an organisation's presence, which will lead to enticing possible investors and hasten global growth. In this paper, we proposed a framework that aid organisations toward big data adoption and implementation that can create the best value for the organisations. It covers the whole value chain of big data adoption and implementation from the enculturation of big data in the organisation, to business understanding, to data management and governance, to big data project planning, to data understanding, to data preparation, to procurement, to analytics modeling, data product development, evaluation of model and data product deployment, maintenance, and upgrades and inculturation of data analytics into business. The framework has been successfully used in several Malaysian organisations, government, semi-government, and private sectors.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:big data, data analytics, big data adoption, digital transformation, data-driven organisation
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:101442
Deposited By: Yanti Mohd Shah
Deposited On:14 Jun 2023 10:26
Last Modified:14 Jun 2023 10:26

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