Data quality

The Central Statistics Agency (BPS) is a government institution that has the authority to carry out statistical activities in the form of censuses and surveys, to produce statistical data needed by the government, the private sector and the general public, as a reference in planning, monitoring, and evaluation of development results. Therefore, providing quality statistical data is very decisive because it will have an impact on the effectiveness of decision making. This paper aims to develop a framework to determine priority of solutions in overcoming data quality problems using the Analytic Hierarchy Process (AHP). The framework is built by conducting interviews and Focus Group Discussion (FGD) on experts to get the interrelationship between problems and solutions. The model that has been built is then tested in a case study, namely the Central Jakarta Central Bureau of Statistics (BPS). The results of the study indicate that the proposed model can be used to formulate solutions to data problems in BPS.

Over the last 20 years, and particularly with the advent of Big Data and analytics, the research area around Data and Information Quality (DIQ) is still a fast growing research area. There are many views and streams in DIQ research, generally aiming at improving the effectiveness of decision making in organizations. Although there are a lot of researches aimed at clarifying the role of BIG data quality for organizations, there is no comprehensive literature review that shows the main differences between traditional data quality researches and Big Data quality researches. This paper analyzed the papers published in Big data quality and find out that there is almost no new mainstream about Big Data quality. It is shown in this paper that the main concepts of data quality does not changes in Big Data context and that only some new issues have been added to this area.