OpenText Integration Center
OpenText Integration Center is a data and content integration platform used to extract, enhance, transform, integrate and migrate data and content throughout the entire information ecosystem. Integration Center supports a complete view of the relevant information across the enterprise, allowing organizations to access information that is up-to-date and complete, and use it for business intelligence, process optimization, and business intelligence purposes.
Integration Center was designed as a component-based, hub-and-spoke system with a centralized and open repository, which allows full control of all data exchange processes, business rules, and metadata.
This allows access to data involved in all projects within the enterprise, instead of separating the data into siloed systems.
OpenText began developing its solutions in 1991, when its full-text indexing and string-search technology evolved out of the Oxford English Dictionary (OED) project at the University of Waterloo.
In 2003-2006, OpenText introduced its ECM solutions for Oracle, and in 2005, introduced a complete ECM ecosystem using Livelink ECM as the intelligent bridge between Microsoft (including SharePoint and Office 12) and SAP solutions.
In 2017, OpenText was named a leader in Gartner’s 2017 Magic Quadrant for Customer Communications Management Software. Recent acquisitions include certain customer experience software assets of HP Inc (including HP TeamSite, HP MediaBin, and more), and Dell EMC’s Enterprise Content Division (ECD).
What it Does
OpenText Integration Center is used to move unstructured, semi-structured, or structured data between any source and target system. It is built on client/server architecture, and incorporates a centralized and open metadata repository.
As part of Integration Center‘s hub-and-spoke architecture, a centralized engine and metadata repository (the hub) exchanges data among data sources and targets (the spokes).
Integration Center offers a procedural approach to data transformation and exchange processing. With this approach, users are free to develop their own reusable transformation code to any degree of complexity.
Integration Center can be implemented within a distributed deployment model, allowing multiple developers to work on projects simultaneously with complete version control and customized access privileges.
For simple ETL-type scenarios, Integration Center can be installed on a server between the source and target systems. For high-volume, time-critical projects, Integration Center can be installed on multiple servers with multiple engines defined on each box. For additional performance gains, Integration Center can be installed on the same server as the target RDBMS database to avoid network latency.
- Enterprise connectivity:
- Provides access to any business or legacy system, such as ERP, CRM, SCM, ECM, and custom applications;
- Supports multiple database and repository connectors, including connectors to OpenText repositories, file shares, multidimensional databases, and so on;
- Supports all middleware, providing ODBC, command-line interfaces, web services, or MOM.
- Content and data extraction:
- Uses simple to complex business logic to extract both structured and unstructured objects from business systems; Supports bulk and incremental extraction;
- Supports management of complex data structures such as hierarchical data dumps from mainframes;
- Supports a wide range of transformation complexity, replacing most custom language-based development.
- Process optimization and audit control: Provides track changes, impact analysis, auto-documentation features, audit-trail capabilities, metadata management, and version control.
- Initiates processes based on pre-determined schedules or events;
- Provides process monitoring as well as full history and audit-trail reporting;
- Manages large volumes of logs stored on the repository.
- Support for Windows, UNIX and Linux platforms;
- Repository can reside on a variety of RDBMSs, including MSSQL and Oracle;
- Performs parallel processing and multi-CPU utilization for high-volume transactions.