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These days, Big Data (BD) and Big Data Analytics (BDA) applications have increased intensively among public and private organisations. Most organisations are aware that BDA has an enormous potential in aiding them to better understand their business environments and their customers’ needs. Nevertheless, many organisations have yet to implement BD as they are concerned that poor quality of data will have an adverse impact on establishing worthful insight, and leading to severe mistakes during their decision-making process. In addition, the different BD characteristics or traits could affect data quality. Therefore, to determine the value of data generated from BD, the collected data must be analysed for accuracy and quality. This paper aims to present findings to better understand quality requirements for BDA implementation in the public sector, specifically in Malaysia. This study explored the influence of Data Quality Dimensions (DQD) on BDA application, identified the influence of Big Data Traits (BDT) on DQD, and evaluated the integration of BDT and DQD in BDA applications using expert validation approach. A conceptual model that incorporates DQD and BDT for BDA application in the public sector was proposed as the study outcome. The conceptual model was developed based on eight BDT (variety, velocity, veracity, validity, volume, value, volatility, and variability) and four data quality categories (intrinsic, contextual, representational, and accessibility). The expert validation results showed that five out of eight BDT are important. The outcomes from this study would deliver important knowledge to the current body of studies that may prove useful for potential use in the future.

ESTABLISHMENT OF BIG DATA ANALYTICS APPLICATION MODEL FOR MALAYSIAN PUBLIC SECTOR: AN EXPERT VALIDATION