Analysis and Design of a Data Architecture Management Assessment Guide using DAMA-DMBOKv2 and Process Assessment Model

Data is a vital asset for companies, as it has the potential to significantly enhance business value when appropriately managed. Effective management of corporate data assets, often called data management, is critical in ensuring that data serves its intended purpose. One key aspect of data management is data architecture management, which focuses on organizing and governing the company’s data to ensure optimal usage and consistency across the enterprise. This is particularly important because corporate data is frequently dispersed across multiple platforms in various departments, leading to challenges such as duplicated or redundant data. Moreover, many organizations struggle with outdated, inconsistent, or incomplete data, which can cause significant problems in business operations and decision-making. Data architecture management is crucial for aligning information systems with business objectives. However, existing frameworks often lack comprehensive assessment tools. This study proposes an assessment guide using DAMA-DMBOKv2 and the Process Assessment Model to fill this gap. The guide was validated by five experts, achieving a CVR score of 1. This indicates high relevance and applicability. The results demonstrate the guide’s effectiveness in enhancing organizations’ data governance and architecture alignment. This research focuses on designing a comprehensive guide and assessment techniques for implementing data architecture management within companies. It draws on the Data Management Body of Knowledge (DAMA-DMBOKv2) and the Process Assessment Model (PAM) to provide a structured approach to improving data architecture and ensuring data management aligns with broader business goals.