Standardized Approach to Automatization of Data Quality Control

Data is an inexhaustible resource, which potential significantly exceeds the potential of minerals. It is used to make effective management decisions, create new products or improve existing ones. The opposite effects arise from the use of low quality data: it is misleading, organizations suffer reputational and financial losses. They can be avoided if the data is checked on time and the low quality is revealed. Stable speed and quality of data quality control can be ensured only by the automatization. Currently, there is no standardized approach to data quality control that satisfies business conditions – criteria of speed, quality and versatility. Organizations that monitor the quality of their data use unique automatization solutions based on proprietary technologies. They cannot be duplicated, their development and implementation require large financial costs. In this work, such a standardized approach was proposed. It includes 7 indicators for checking the quality of the data, the methodology for their calculation and recommendations for automatization solution. It is based on an analysis of existing approaches for their compliance with the criteria of speed, quality and versatility. The compliance of this standardized approach with the business conditions was proved experimentally by successful testing of MVP (minimum viable product) that automatizes calculation of the proposed indicators.