EIQ Products are basically adapters that build and maintain their own indexes, and process standard query language (SQL) queries across multiple, disparate and distributed structured, unstructured and semi-structured data sources.  Data remains in data sources, and is read, cleansed, transformed and standardized to build and maintain indexes in near-real-time.  SQL queries against the indexes are highly successful and fast because of the quality of the indexes, and the processing load is absorbed by EIQ Products; not the data source systems.  Results data are read from data sources and put through the same data quality processes as indexes or inverted from indexes, merged with other data source results and provided to third-party calling applications/middleware. 

EIQ Products combine technologies from the conventional approaches of data warehousing, federated adapters and enterprise search.  EIQ Products are dataless hybrids that retain most of the advantages and overcoming most of the disadvantages of conventional approaches.  To learn more about the advantages and disadvantages of the conventional approaches, and their comparison with EIQ Products, see the links to the right.  Or, read an article published by Information Management (also linked in the Articles section).

Other products may superficially sound like they do what EIQ Products do, but they do not.

It's All About Data

The problem with data that most organizations face is that they are awash with it and it is rarely available in a useable form.  All data access, integration, sharing and interoperability approaches attempt to address these problems to a greater or lesser extent.

EIQ Products power the best-of-all-worlds solutions by leaving data where it is, but provide queryable metadata layers that work with original data sources and data source schemas and formats.  And, unlike other approaches, EIQ Products address all of the above-listed data issues.

EIQ Products provide the real alternative to conventional approaches for data access, integration, sharing and interoperability across multiple, disparate data sources with higher success, and lower complexity, implementation time and cost.  This provides real value for business intelligence (BI), analytics, marketing, customer data integration (CDI), master data management (MDM) and other data-centric solutions.