Enterprise Architecture
Problem – Advanced Enterprise Information Architectures Must Include All Information Assets
While the enterprise data warehouse is often the primary source for significant volumes of enterprise information, other sources are also critical today. This has the potential to increase in the future, as data grows exponentially and complexity continues unabashed. Increasingly enterprises are seeking unified ways to integrate warehouse and other data in an enterprise-wide information architecture. According to Forrester Research, “new architectural approaches such as information-as-a-service (IaaS) have emerged to provide flexible, real-time, service-oriented data integration and data-quality capabilities that support both structured data and unstructured content, delivering a true information integration platform.”
Solution – Integrate Data Warehouses into Enterprise Information Architectures
Composite Data virtualization integrates data warehouses into an unified enterprise information architecture. The data virtualization middleware forms an enterprise data virtualization layer that is home to a logical schema covering multiple consolidated and virtual sources in a consistent and complete fashion. In design, developers use data virtualization design tools to develop these semantic abstractions in the form of web services or relational views. At run time, end user-level applications, reports or mash-ups can call these web data services on demand to query, federate, abstract and deliver the requested data to these information consumers.
Integrating Data Warehouses into an Enterprise Data Virtualization Architecture
Selected Examples
- Virtualizing Refinery Data Enterprise-wide – To provide disparate data warehouse and operational data from more than a dozen refineries to diverse technical and business user communities globally, this energy company deployed Composite data virtualization on an enterprise scale. This common approach allowed them to increase refinery yields, proactively maintain equipment, and comply with a myriad of regulations more consistently for less.
- Sharing Intelligence Data across Government Agency Boundaries – To enable intelligence analysts to use information from other agencies and better control threats, multiple government agencies leverage a common Composite data virtualization layer. This allows other agencies such as the Drug Enforcement Administration and the Immigration and Naturalization Service to access passenger, crew and manifest data from a U.S. Coast Guard port arrivals data warehouse, for example.
