Data integration comprises the practices, architectural techniques and tools for achieving consistent access to, and delivery of, data across a wide range of enterprise data subject areas and data structure types to meet the data consumption requirements of applications and business processes. Data integration is concerned with consistency of values and common semantics.
Data integration tools support a combination of four main data delivery styles
1. Bulk Data Movement (also referred as ETL (Extract, Transform, and Load)): In this model, the data is moved from primary sources to target source to build a data warehouse by updating existing data and adding the new data. This model mainly used to migrate data from legacy system to modern system.
2. Federation views (also referred as enterprise information integration): In this model, the data is collected from various sources and creates a view of these sources within a single data interface such as SQL row set, Extensible Markup Language (XML) or Web services interface. This model is mainly used to launch pivot integration application efforts or to build data prototypes.
3. Synchronization/replication: This model synchronizes data between two or more database management systems (DBMSs) and schemas, whether of the same type or different, while replication focuses on copying data from an authoring data system to subordinate systems that are used for read-only purpose. This model supports high-volume, mission-critical scenarios, such as keeping operational data current in multiple systems. This model is used when the input data are from disconnecting input devices such as handheld devices.
4. Message/queue integration (also known as enterprise application integration (EAI)): Various systems write data into queue and based on the business logics EAI updates the target system. This model is used when a real time updating is required.
To know more about data integration refer Giordano, A. D. (2011). Data integration blueprint and modeling: Techniques for a scalable and sustainable architecture, IBM Press.
