A Novel Rigorous Measurement Model for Big Data Quality Characteristics

Satisfiable data quality is the basic guarantee for data-based research, decision-making, and service. Today, new trends in the creation, collection, and utilization of data are constantly emerging. With the usage of massive data, the problem of data quality is highlighted. Several studies on the measurement, evaluation, and management of big data quality have been proposed, and the data quality problem in the big data environment has received attention. The big data characteristics Vs model describes the dimensions and attributes information of data sources in detail, which can be implemented in big data quality measurement. In this paper, a novel rigorous big data quality measurement architecture is proposed for automatically and parallelly quantifying the value of six big data Vs, which are Volume, Variety, Velocity, Veracity, Validity, and Vincularity according to the developed algorithms in every big data process step and time phase of the big data pipeline. Thresholds for the six big data Vs are provided correspondingly for analyzing the result values. The hierarchical measurement model is constructed with multiple-based measures, derived measures, and indicators. The model is verified by comparative experiments and experiments results indicate that the designed architecture can improve the outcomes of data source implementation.

I. Introduction

With the rapid development of information technology such as the Internet, Internet of things (IoT), and cloud computing, a surging amount of massive data are generated anytime and anywhere in various fields such as e-commerce, biomedicine, and financial investment [1]. The scale of these data is growing daily, promoting the advent of the era of big data. As a hot research field, big data brings new challenges and opportunities to the development of information technology on the one hand. Analyzing and processing big data has become a popular technical issue in the industry [2]. Meanwhile, big data itself is still becoming a strategic resource, with which one can become a dominant player in the big data market and even in the field of information technology [3].