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Understanding Data-Oriented B2B Application Integration

Migrating data from one database to another sounds straightforward and reasonable enough, but for data-oriented B2B application integration to actually work, architects and developers need to understand both the complex world of database technology and the way in which information flows throughout an enterprise. EAI expert David S. Linthicum discusses the issues behind creating a successful data-oriented B2B application.

Migrating data from one database to another sounds straightforward and reasonable enough, but for data-oriented B2B application integration to actually work, architects and developers need to understand both the complex world of database technology and the way in which information flows throughout an enterprise. EAI expert David S. Linthicum discusses the issues behind creating a successful data-oriented B2B application.

Data-oriented B2B application integration represents the "entry point" for most enterprises that are considering B2B application integration—which makes perfect sense. Data-oriented B2B application integration allows for data to be moved between data stores. Relevant business information can be shared among these data stores and, ultimately, with trading partners. Data level as an entry point for B2B application integration has the added benefit of numerous tools and techniques that enable the integration of information from database to database, tools and techniques that adapt information "on the fly" so that it is represented correctly by both the source and target applications.

Accessing databases at the data is a relatively easy task, accomplished with few, if any, significant changes to the application logic or database structure. This is a tremendous asset because altering applications is not possible in many problem domains, where you are likely dealing with systems that are beyond your direct control.

However, the straightforward appearance of data-oriented B2B application integration should not create the impression that it is simple. It is not. Migrating data from one database to another sounds straightforward and reasonable enough, but for data-oriented B2B application integration to actually work, architects and developers need to understand both the complex world of database technology and the way in which information flows throughout an enterprise. Moreover, it's just dangerous to update databases without understanding any integrity issues that may exist at the application level. Therefore, people employing data-oriented B2B application integration need to make it their job to understand how the application handles data integrity, making sure that any integrity rules are not violated.

In most trading communities, databases not only number in the thousands, but they also represent a complex and complicated mosaic of various database technologies and models that provide data storage for applications. This reality makes integrating databases a difficult task, one that would have been nearly impossible before the introduction of powerful many-to-many, B2B application integration data movement and transformation tools and technologies.

However, this problem is even more complex. Data from one system may not be compatible with a different system. The semantics are so different that the two systems just can't understand each other—for example, sales accounting practices might be different. Thus, data-oriented B2B application integration is not just about moving information between data stores, but it's also about managing the differences in metadata and applications semantics.

Going for the Data

B2B application integration data access demands an "end run" around application logic and user interfaces to extract or load data directly into the database. Fortunately, most applications built in the recent past decouple the database from the application and interface, but many do not. As a result, this once-daunting task is transformed into something relatively simple—that is, relatively simple if you are dealing with a recently created application. Unfortunately, there are still many databases that are tightly coupled with the application logic. In these scenarios, it is impossible to deal with the database without dealing with the application logic as well. As we have suggested, this is a much more difficult proposition—so difficult that it may be reason enough to employ method or application interface-oriented B2B application integration along with data-oriented B2B application integration, or even to consider using another type of B2B application integration exclusively.

Data-oriented B2B application integration's simplicity and speed to market advantages are the consequences of a business logic that rarely has to be altered (a cohesive rather than coupled approach). It frees the enterprise from having to endure seemingly endless testing cycles, or the risk and expense of implementing newer versions of applications. Indeed, most users and applications will remain blissfully ignorant of the fact that data is being shared at the back end.

Numerous database-oriented middleware products allow architects and developers to access and move information between databases, thereby simplifying data-oriented B2B application integration. These products can integrate various database brands, including Oracle and Sybase. They also allow for the integration of different database models.

The advent of B2B application integration-specific technology, such as message brokers, B2B application integration management layers, and simple data movement engines, enables the enterprise to move data from one place to another—from anywhere to anywhere—without altering the target application source. What's more, this can now be done in real time, within online transaction-processing environments.

Although the technology for moving data between two or more data stores is familiar and well-tested in real applications, this familiarity does not exempt the architect or developer from understanding the data that is being moved, or from understanding the flow and business rules that must be applied to that data.

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