<![CDATA[The importance of high quality data is a top priority for PT XYZ’s Human Capital Management (HCM) in handling Talent Management, Career Management, and Employee Performance Management. information security audit revealed several issues, such as delayed data updates and inconsistencies across functions. To address these issue, an assessment of the Data Quality Management (DQM) maturity level is needed to evaluate the implementation of consistency, accuracy, and integrity. This study uses David Loshin’s framework, with the results explained referring to DQM guidelines in DMBOK. Results show DQM maturity level is at level 2 (Repeatable), with an average score of 2.3. Three dimensions with the lowest scores are the main focus for improvement, which Data Quality Expectations (1.6), Data Quality Protocols (1.8) and Data Quality Technology (1.2). Recommendations from this study focus on enhancing these dimensions to improve data quality and address the issues highlighted in information security audit.]]>
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