<![CDATA[Big Data development often encounters obstacles in data quality even though it already has a data warehouse. The lack of high-quality data is the root cause of this issue. One of the causes is the failure to implement metadata management, which leads to issues with non-standardized data, a lack of a common understanding of the meaning and content of a data element, and the use of different data formats and formulas. This leads to a variety of data issues, including data duplication, inconsistent data, inaccurate data, outdated data, and unreliable data. This condition is impacting companies, especially data warehouse managers, who still face problems in cleaning, organizing, and managing data. Therefore, conducting research on metadata management is crucial to determining the necessary preparations for big data development and ensuring the provision of high-quality data. This research utilizes the DMBOK 2 framework, maturity instruments from Standford, and the technical framework from CMMI. The results of the research can help companies with metadata management improve big data implementation.]]>
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