The popularity of big data analytics (BDA) has boosted the interest of organisations into exploiting their large scale data. This technology can become a strategic stimulation for organisations to achieve competitive advantage and sustainable growth. Previous BDA research, however, has focused more on introducing more traits, known as Vs for big data traits, while ignoring the quality of data when examining the application of BDA. Therefore, this study aims to explore the effect of big data traits and data quality dimensions on BDA application. This study has formulated 10 hypotheses that comprised of the relationships of big data traits, accuracy, believability, completeness, timeliness, ease of operation, and BDA application constructs. This study conducted a survey using a questionnaire as a data collection instrument. Then, the partial least squares structural equation modelling technique was used to analyse the hypothesised relationships between the constructs. The findings revealed that big data traits can significantly affect all constructs for data quality dimensions and that the ease of operation construct has a significant effect on BDA application. This study contributes to the literature by bringing new insights to the field of BDA and may serve as a guideline for future researchers and practitioners when studying BDA application.

大数据分析（BDA）的普及激发了组织对利用其大规模数据的兴趣。这项技术可以成为组织实现竞争优势和可持续增长的战略刺激。但是，先前的BDA研究更多地集中于引入更多的特性，即大数据特性的Vs，而在检查BDA的应用时却忽略了数据的质量。因此，本研究旨在探讨大数据特征和数据质量维度对BDA应用的影响。这项研究提出了10个假设，其中包括大数据特征，准确性，可信度，完整性，及时性，易操作性和BDA应用程序结构之间的关系。这项研究使用问卷作为数据收集工具进行了调查。然后，使用偏最小二乘结构方程建模技术来分析构造之间的假设关系。研究结果表明，大数据特征可以显着影响所有数据质量维度的构造，并且易于操作的构造对BDA应用具有重大影响。这项研究为BDA领域带来了新的见解，从而为文献做出了贡献，并且可以作为将来研究BDA应用的研究人员和从业人员的指南。