Putting all the information in one place which describes a business object like a product, a customer or a certain technology can ease the life of many people significantly. Unfortunately, the automatic integration of data from various sources can cause tremendous efforts. Data in enterprises is organised such that data remains locked up in its database. Knowledge workers are forced to collect information from a series of data silos manually to put those pieces together like a puzzle in order to create the basis for a decision making process. Data integration projects most often are built upon yet another inflexible data structure. Numerous amendments or additions made to the structure or to the semantics of an information component cannot be reflected properly by the integration layer. The result is a landscape consisting of data silos which are scarcely connected to each other. Intelligent linkages happen only in the course of ad hoc processes which are not readily comprehensible.
Our solution approach
Web data, but also data in enterprises are characterized by a great structural diversity as well as frequent changes. This poses a great challenge for applications based on that data. We address this problem by using a flexible data model that supports the integration of heterogeneous and volatile data. We make use of linked data technologies for data integration purposes which relies on graph-based models. This allows to incrementally extend the schema by various properties and constraints. Linked data is based on open standards which makes the effort future-proof.
- 360o views on specific business objects (‘topic pages’) like products, companies, technologies etc.
- Reports based on sometimes complex queries which can only be answered if data is used from various sources
- Mashups of unstructured (e.g.: business news, social media, etc.) and structured data (e.g.: statistics, legacy data, etc.)
- Mashups of data from the web (e.g.: open government data) and internal data sources