How it works

Enterprise Information Intelligence Graph

Orion helps eliminate 80% of work on most application modernization and data migration efforts, by combining Data Cataloging, Impact Analysis, Process dependency tracking, Data lineage, Data Transparency and Trust propagation to become Data-Driven and Governed. The figure below illustrates how it is done.

EIIG platform

EIIG ingests metadata from numerous sources via Metadata Ingesters. These sources could be Structured Data, Unstructured data, Big Data, Business Glossaries etc EIIG then leverages an ML/AI brain to build the Orion EIIG Knowledge Graph. This provides the foundational Data Fabric for Metadata Discovery by allowing a Search capability against a Data Catalog that is automatically generated. Rest API’s can access this Data Catalog along with the numerous Orion EIIG suite of interfaces to provide a Discovery and Analysis environment. Data Stewards and Technical Custodians across the organization can leverage these capabilities in a Stewardship model to build a collaborative Data Governance layer for your organization.

The brain | Inner workings of eiig

Once Metadata is extracted from the sources of information flow by parsing the building blocks. The information is then converted and stored in Orion’s metadata repository in a vendor and technology agnostic manner.

Processes are activated that try to cluster information into meaningful groupings, while other processes that leverage supervised-ML try to connect the business concepts to the technology assets and generate a curated list for stewards to approve. Stitching processes get activated, one that connects assets within a system, based on possible relationships (lineage, impact, execution). The second stitching process looks for opportunities to connect different systems together.

What this means is that the picture of the connected enterprise begins to take shape. Active metadata can also be loaded on top of the knowledge graph that EIIG creates to further enhance the meaning of the picture that is produced. Analytics dashboards give the user useful insights, such as data quality trends, reliability of reports, overall coverage of the business concepts etc.


Enterprises are a grouping of different organizations, people, processes, technologies etc. It would be a highly capital intensive task to try to build a picture of the information flow within the enterprise manually. EIIG supports automation all the way from the start. This includes “No-code” support for ingesting 60+ technologies, automatically connecting assets with no prior human knowledge required, the ability to process information directly from the version control systems during deployment. This results in a Zero Impact to Production and a “Fire and Forget” kind of operation, whose output would be providing “near real-time” knowledge of information flows within the Enterprise.

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