What are the advantages and disadvantages of different data integration architectures and approaches?
Data integration is the process of combining data from different sources into a unified view for analysis, reporting, or other purposes. Data integration can be challenging due to the variety, volume, velocity, and veracity of data, as well as the different business and technical requirements of each project. To address these challenges, data integration architectures and approaches have evolved over time, each with its own advantages and disadvantages. In this article, we will compare some of the common data integration architectures and approaches, such as ETL, ELT, EAI, ESB, and data virtualization.