Data Integration
Data Integration is the process of combining data from disparate sources into a unified, consistent view for analysis, reporting, or operational use. It involves techniques like ETL (Extract, Transform, Load), data synchronization, and real-time streaming to ensure data quality and accessibility across systems. This concept is fundamental in data engineering, business intelligence, and modern data architectures.
Developers should learn Data Integration to build scalable data pipelines, support data-driven decision-making, and enable interoperability in complex IT environments. It is essential for use cases such as data warehousing, migrating legacy systems, implementing data lakes, and powering analytics platforms where data from multiple databases, APIs, or files must be harmonized.