FAQs

Deep cataloging has three major characteristics: 1) Covering all types of technologies A data fabric provides a holistic view of data across the IT landscape. In this design, a [...]

First of all, the visualization of data lineage in EIIG is automated. The reduction of manual efforts in establishing data lineage not only saves costs but also increases accuracy [...]

Founded in 2017, the name Orion implies a hunter mentality and also the rising in the sky and dawning.  Our goal was to be a disruptor in the data [...]

Orion’s Enterprise Information Intelligence Graph (EIIG) augments data quality and bring it to life in the following ways:Determine data quality and aggregate all data quality information and assign quality scores [...]

Orion is headquartered in San Mateo, California with offices across the U. S. and in Germany, Sweden, Estonia, India, and Singapore.

EIIG enables the acceleration of modernization/cloud migration projects in several critical ways, including: Thorough understanding of the environment of the data assets customers plan to migrate: EIIG offers a [...]

Gartner defines data fabric as a design concept that serves as an integrated layer (fabric) of data and connecting processes. A data fabric utilizes continuous analytics over existing, discoverable, [...]

Very often projects are funded, planned, and run independently of each other. As a result, project data overlaps are not managed. This not only is wasteful and inefficient, but [...]

Orion’s Enterprise Information Intelligence Graph (EIIG) ingests information from more than 70 different technologies to automatically stitch a near real-time, self-defined data fabric. It is the most comprehensive knowledge graph [...]

EIIG automates the identification of golden / certified data sources, thus helps drive and control their usage in cases such as new application development. It can enable metadata discovery to [...]

Quite a few vendors claim that they offer a data fabric. However, what you will find is often a patchwork of loosely connected modules and even products by different [...]

With EIIG metadata analytics, organizations can automatically discover what data assets/data flows are non-preferred/redundant/non-used. EIIG also helps determine which data assets should be cleaned-up/minimized, migrated and/or decommissioned. The fact-based visibility provided [...]