Figure 1: Traditional Integration
A next step was Service Oriented Architectures (SOA-s), that organize and combine data integration functions into a hierarchy of components (services) with a formal interface. Technical standards for these services were developed to allow systems and companies to exchange data even easier over intra- and internet. Vendors adopted these standards to develop systems that were able to exploit these new self-descriptive interfaces, like Business Process Management (BPM) platforms.
IBM, Tibco and webMethods are players of the first hour. Other vendors like SAP (XI, PI), Oracle (Fusion) and Microsoft (BizTalk) stepped in as the market emerged.
Parallel to EAI a second Integration need drove a completely different market: Data integration for Business Intelligence (BI). BI is usually based on aggregated historical data, optimized for reporting and online analysis. This data is commonly extracted from transaction systems, combined and enriched with the other data and finally fed into Data Warehouse (DWH) and consecutive dedicated Data Marts. This process is called Extract-Transform-Load (ETL). ETL is generally batch driven. This in contrast to most Application Integration solutions, which are generally transaction based – either synchronous (request – reply) or asynchronous (publish-subscribe)
The importance of data sharing is ever increasing. The shift of focus from systems to data (“datafication”) is the new mindset, and data is considered an asset now, where before it was merely a by-product of business processes. It requires to value data value and to manage data quality, consistency, security, lineage, traceability and timeliness. This calls for specific functions like Master and Reference Data Management (MDM/RDM), Data protection, Meta Data Management and Data Governance.