A review foranalytics requirements processes: from Malaysia public sector perspectives.

Big Data Analytics (BDA) projects in Malaysia's public sector become challenging because it involves complex processes of diverse data sets among agencies, ministries and stakeholders to uncover valuable insights. One of the critical challenges is to ensure the analytics output is meaningful an...

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Bibliographic Details
Main Authors: Ya'Acob, Suraya, Hussein, Surya Sumarni, Abu Bakar, Nur Azaliah, Daud, Zuliana
Format: Article
Language:English
Published: Penerbit UTM Press 2022
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Online Access:http://eprints.utm.my/104576/1/ZulianaDaudSurayaYaacobNurAzaliah2022_AReviewforAnalyticsRequirementsProcess.pdf
http://eprints.utm.my/104576/
https://oiji.utm.my/index.php/oiji/article/view/196/146
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Summary:Big Data Analytics (BDA) projects in Malaysia's public sector become challenging because it involves complex processes of diverse data sets among agencies, ministries and stakeholders to uncover valuable insights. One of the critical challenges is to ensure the analytics output is meaningful and valuable in facilitating business decisions in the public sector. Hence, the clarity for analytics requirements or typically known as Business Requirement Specification (BRS) is essential. Clear analytics requirements can help business and technical persons understand what to expect, deliver, and change during the BDA project development. Furthermore, it is important to understand the requirements of the business and align them to the analytics features. Currently, the level of alignment between business and technology is constantly uncertain and the process of developing analytics requirements mostly relies on current methodologies and processes which are still unsure of their ability to handle the analytics requirements. Hence, this paper intends to investigate further, explore and analyse the current methodologies and their suitability to handle analytics requirements. These findings can be extended to develop more practical processes in guiding the analytics requirements in the future.