A CONCEPTUAL FRAMEWORK FOR MEASURING THE PERFORMANCE OF BIG DATA ANALYTICS PROCESS

Abstract

Processes are described as a sequence of steps which result in a specific output based on a given input. The use of term, process, is common and used in different settings including more recently as big data analytics(BDA) process, and Extract, Transform, Load (ETL) process for traditional data warehousing and business intelligence in the past. BDA process starts from data acquisition and selection of the sources, to data preparation, analysis and modeling, to visualization and interpretation phases. Looking at big data analytics in a process perspective has major benefits since improving process drives a better outcome. This study focuses on how the performance of BDA process can be measured. The major contribution will be performance measurement framework of BDA process. The concept of process performance is broadly covered in the literature, mainly in the areas of business process and software process. Thus, process performance measures are available. Time, quality, cost, and flexibility are four of them. Do they apply to BDA process? This is a major question to be dealt with in this research. The overall structure of this research is shown in Figure 1.

Keywords

• Process
• big data analytics process
• performance measures
• conceptual framework.