Assessment of Data Quality Dimensions Influencing Big Data Analytics Role in Sustainable Development Growth Performance - Muhammad, Nur Khairiah; Osman, Nor Hasni; Salleh, Nurul Azita (Global Business and Social Entrepreneurship Resources, 2024)
Many nations are increasingly interested in the value of massive amounts of data, driven by the growing importance of Big Data Analytics (BDA) in today's competitive landscape. The adoption of Big Data Analytics enables organizations to strategically enhance their operations efficiencies, gain a competitive edge, and sustain long-term growth. In the context of Sustainable Development Growth (SDG), ensuring high data quality becomes even more critical, as decisions based on inaccurate or incomplete data can lead to suboptimal outcomes and potentially adverse environmental or social impacts. Prior research on Big Data Analytics has ignored data quality in favor of adding more big data attributes – referred to as Vs (volume, variety, velocity, etc.) Poor quality, outdated, and incomplete data can result in inadequate decision-making. Therefore, the primary aim of this study is to explore the importance of Data Quality Dimensions (DQD) and Big Data Analytics adoption can influence the effective impact measurement and data collection for the success of SDGs. Key variables from research literature reviews were incorporated into the research framework for this study. This study used quantitative method of cross-sectional survey to data professional practitioners and management board (senior and middle managers) that involved in Big Data Strategies within Malaysia. By introducing novel insights in the realm of Big Data Analytics, this study contributes to the body of literature and serves as a valuable resource for future scholars and industry practitioners who wish to investigate BDA solutions associated to performance of SDGs