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Context - The exponential growth of data is becoming a significant concern.Managing this data has become incredibly challenging, especially when dealingwith various sources in different formats and speeds. Moreover, Ensuring dataquality has become increasingly crucial for effective decision-making andoperational processes. Data Architecture is crucial in describing, collecting,storing, processing, and analyzing data to meet business needs. Providing anabstract view of data-intensive applications is essential to ensure that thedata is transformed into valuable information. We must take these challengesseriously to ensure we can effectively manage and use the data to ouradvantage. Objective - To establish an architecture framework that enables acomprehensive description of the data architecture and effectively streamlinesdata quality monitoring. Method - The architecture framework utilizes ModelDriven Engineering (MDE) techniques. Its backing of data-intensive architecturedescriptions empowers with an automated generation for data quality checks.Result - The Framework offers a comprehensive solution for data-intensiveapplications to model their architecture efficiently and monitor the quality oftheir data. It automates the entire process and ensures precision andconsistency in data. With DAT, architects and analysts gain access to apowerful tool that simplifies their workflow and empowers them to make informeddecisions based on reliable data insights. Conclusion - We have evaluated theDAT on more than five cases within various industry domains, demonstrating itsexceptional adaptability and effectiveness.

Architecting Data-Intensive Applications : From Data Architecture Design to Its Quality Assurance