Manage semantic conflicts

Reduce complexity and eliminate guesswork

In a classical data integration approach, point-to-point mappings are created between disparate data formats. These mappings, possibly supported by a technical metadata repository, only say how one element from one data format relates to another entity in another data format. It does not specify what each of these entities mean. The essential step of making the meaning of these two entities explicit so it becomes clear to all stakeholders is skipped. Formats are transformed in a point-to-point fashion which comes with a number of critical problems.

• Ad-hoc solution: Manual creation of data translations is a black art with little methodological support. The solutions are very specific and mastered only by a few.
• Error prone: Much of the guesswork is left to the data mapper. Assumptions can be very dangerous and costly when they turn out to be wrong. It can take a long time before problems are discovered. The longer it takes, the higher the risks and the more expensive the consequences.
• Inefficient: Creating format translations is a very time consuming process that provides little reuse. It is especially problematic when mappings have to be changed or maintained over time. Because mappings remain at a technical level, it is very difficult for people to understand, even for the original developers.
• Inefficient: If you consider the above points, and multiply them with the complexity and the time-frame of your organization, your organization is left with an ever growing legacy that requires a state of permanent maintenance.

Business-context driven integration

Collibra's Semantic Data Integration solution enables business stakeholders to define and agree on the meaning of the business context on a business level. We are the first enterprise software company to implement the OMG's Semantics for Business Vocabulary and business Rules (SBVR) standard to enable business stakeholders to do that in a very easy and effective manner. The Business Semantics Glossary also makes it very easy to import existing data models (UML, XSD, Excel, Word, ...) to bootstrap this process.

Next, the Business Semantics Studio enables technical stakeholders to link existing applications or data sources (XML, Database, Web-services, ...) to this business context. These links, or what we call commitments, can be loaded into the Business Semantics Enabler to automatically generate a data transformation services to solve your data integration needs.

The figure below provides an overview of the solution:

Benefits

Reduce risk and costs, improve business / IT alignment, and increase your Data Integration project's succes by:

• Removing interpretation conflicts,
• Avoiding unnecessary debate,
• Involving the business in defining and governing your data definitions,
• Leveraging these business definition on your data integration and middleware infrastructure to reduce integration complexity and costs,
• Increasing governance and compliance.