TY - GEN
T1 - Data Quality Management Maturity
T2 - 10th IEEE International Conference on Communication, Networks and Satellite, Comnetsat 2021
AU - Indriany, Henny Sri
AU - Hidayanto, Achmad Nizar
AU - Wantania, Lellyana Juliet
AU - Santoso, Budy
AU - Putri, Widha Utami
AU - Pinuri, Welly
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/7/17
Y1 - 2021/7/17
N2 - Data quality determines the organizations decision-making, strategic planning, and organizational resources components in achieving organizational goals. Data quality must be a concern in government organizations. Research Data and Information Center (RDIC) National Narcotics Board (NNB) is a work unit whose main tasks and functions are data and information services. As the main problem, several work units do not yet understand the importance of data quality, which carries out their data collection in their own format, as it is known that drug data is unique data. Hence, it is necessary to measure the maturity of Data Quality Management (DQM). This research is qualitative research conducted by assessing the working group team in data and information using Loshins data quality framework to measure the data quality RDIC NNB. The results showed that the maturity level is repeatable (level 2). Many improvements need to increase the maturity level of data quality. The characterizations that have not yet been implemented are mapping on data quality DMBOK2 activities. RDIC needs to formulate data governance policies, data standards, data steward, and data quality monitoring systems to improve data quality.
AB - Data quality determines the organizations decision-making, strategic planning, and organizational resources components in achieving organizational goals. Data quality must be a concern in government organizations. Research Data and Information Center (RDIC) National Narcotics Board (NNB) is a work unit whose main tasks and functions are data and information services. As the main problem, several work units do not yet understand the importance of data quality, which carries out their data collection in their own format, as it is known that drug data is unique data. Hence, it is necessary to measure the maturity of Data Quality Management (DQM). This research is qualitative research conducted by assessing the working group team in data and information using Loshins data quality framework to measure the data quality RDIC NNB. The results showed that the maturity level is repeatable (level 2). Many improvements need to increase the maturity level of data quality. The characterizations that have not yet been implemented are mapping on data quality DMBOK2 activities. RDIC needs to formulate data governance policies, data standards, data steward, and data quality monitoring systems to improve data quality.
KW - data quality management
KW - DMBOK2
KW - DQM
KW - government
KW - maturity model
KW - NNB
UR - http://www.scopus.com/inward/record.url?scp=85115703021&partnerID=8YFLogxK
U2 - 10.1109/COMNETSAT53002.2021.9530824
DO - 10.1109/COMNETSAT53002.2021.9530824
M3 - Conference contribution
AN - SCOPUS:85115703021
T3 - 10th IEEE International Conference on Communication, Networks and Satellite, Comnetsat 2021 - Proceedings
SP - 206
EP - 212
BT - 10th IEEE International Conference on Communication, Networks and Satellite, Comnetsat 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2021 through 18 July 2021
ER -