Combining data from different sources into a unified, consistent view.
Organizations rarely store all their data in one place. Data integration brings together records from databases, APIs, spreadsheets, and external feeds so they can be analyzed together. This requires resolving differences in formats, identifiers, and schemas across sources.
Example: A regional transit authority integrates ridership data from fare card systems, GPS feeds from buses, and weather data from Environment Canada. The combined dataset lets analysts study how weather affects ridership patterns across routes.
Data integration is foundational to business intelligence, open data publishing, and any analysis that spans more than one system.