Published in Data Science and Engineering (DSE) Record 2024 Vol. 5 No. 1 pp. 62-79
Abstract
This study implements data quality assessment framework to rapid eco-nomic indicators. Due to the outbreak of the COVID-19 pandemic abruptly halted economic activities worldwide. Assessing its economic im-pact us-ing traditional economic indicators has proven insufficient for the ur-gent ana-lytical and decision-making needs. The advent of Big Data, charac-terized by its diverse sources and frequent reporting for real-time monitoring. However, a critical challenge is the absence of standardized data quality as-sessment frame-works. Neglecting data quality assessment while employing Big Data for decision- making may lead to erroneous decisions. This study evaluates rapid eco-nomic indicators, Apple Mobility Index, Global Normalcy Index, and Google search trends. An existing data quality assessment frame-work and data quality dimensions—accuracy, timeliness, and validity—are assessed by Talend Open Studio for Data Quality. Findings reveal the Global Normalcy Index as a promising rapid economic indicator for timeliness and validity. However, accuracy testing yielded inconclusive results due to its fluctuations. This highlights the need for a nuanced approach with consider-ing data character-istics. Future endeavors should diversify data quality di-mensions and refine the assessment framework to enhance data quality as-sessment efficiency.