TY - GEN
T1 - A Mechanism of Maturity Improvement for Data Quality Management in PT. ABC
AU - Romodhon, Rizki
AU - Cahyani, Widi Setia
AU - Siagian, Dewi Putri
AU - Ruldeviyani, Yova
AU - Hidayanto, Achmad Nizar
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - PT. ABC is an extension of the state's arm in charge of distributing compensation funds for road traffic accidents and public transport passengers. To realize the best service, integrated information technology is needed in order to provide accurate and reliable information in decision making. As a customer satisfaction-oriented company, it should pay attention to data governance, especially in data quality management. However, based on the results of interviews, observations and document searches related to the data used for the compensation settlement process, PT. ABC is faced with data quality management problems including incompleteness, inconsistency and accessibility of data. Therefore, it is necessary to measure the maturity of data quality management. Comparison has been made to choose the suitable model of data quality assessment in PT ABC. Based on the comparison, Data Management Maturity Model is the most suitable model to measure data quality management in PT ABC. The results of this study are the maturity level of data quality management in the data quality strategy, data profiling, data quality assessment, data cleansing and their recommendations.
AB - PT. ABC is an extension of the state's arm in charge of distributing compensation funds for road traffic accidents and public transport passengers. To realize the best service, integrated information technology is needed in order to provide accurate and reliable information in decision making. As a customer satisfaction-oriented company, it should pay attention to data governance, especially in data quality management. However, based on the results of interviews, observations and document searches related to the data used for the compensation settlement process, PT. ABC is faced with data quality management problems including incompleteness, inconsistency and accessibility of data. Therefore, it is necessary to measure the maturity of data quality management. Comparison has been made to choose the suitable model of data quality assessment in PT ABC. Based on the comparison, Data Management Maturity Model is the most suitable model to measure data quality management in PT ABC. The results of this study are the maturity level of data quality management in the data quality strategy, data profiling, data quality assessment, data cleansing and their recommendations.
KW - CMMI DMM
KW - Data Governance
KW - Data Quality Management
KW - DMBOK
KW - Maturity Assessment
UR - http://www.scopus.com/inward/record.url?scp=85123822049&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS53237.2021.9631342
DO - 10.1109/ICACSIS53237.2021.9631342
M3 - Conference contribution
AN - SCOPUS:85123822049
T3 - 2021 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021
BT - 2021 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2021
Y2 - 23 October 2021 through 26 October 2021
ER -
