Data Integration Techniques

This chapter provides a thorough investigation into the vast landscape of strategies and methodologies used to consolidate disparate data sources into a unified, accessible format. The first part of this chapter introduces two prominent data integration models – point-to-point and middleware-based integration. Each model’s benefits, drawbacks, and use cases will be meticulously examined to offer you a nuanced understanding of their application in diverse contexts.

This chapter will then transition into a detailed exploration of various data integration architectures, namely batch, micro-batching, real-time, and incremental. Each architecture will be dissected to present you with their unique advantages, trade-offs, and potential applications, thereby providing a comprehensive view of their roles and performances in the data integration domain.

Then, this chapter will delve into commonly used data integration patterns, such as Extract...