When considering the migration to new Document management software or Enterprise content management (ECM) system the question to ask is, “What do I do with my existing images and data?” The effort to convert these images ranges from relatively simple to complex, depending on their format, the available indexing information and how they are stored. The process is disruptive, costly and “was everything transitioned”
Data Migration Becomes a Relic of the Past
The solution is repository-neutral for greater access to data regardless of location and allows for access and editing-in-place instead of migrating content to the user’s location.
The “Intelligent Metadata Layer” (IML), is the central component of the architecture, where the meta data-driven and intelligence components reside,along with multi-repository search.
All of the typical capabilities of an ECM system are supported here, features such as search, version management, workflow, security and collaboration and check-in/check-out. In addition, search is federated from the typical ability to search one repository to encompass the notion of “enterprise search” or the ability to craw land index content and data in other repositories for quick search and retrieval.
Also supported are metadata-driven ECM capabilities such as “Dynamic Views,” that are dynamically generated “virtual folders” based on metadata. This is the realization of the notion where in content can“show up” in multiple“places”without duplication.Think of it like how the iPhone handles music, for instancea single unique song can show up by artist, album, genre or date, although with IML the variation sare essentially unlimited.
In addition,this layer supports analytics to provide automatic classification and metadata definition.This aspect of the architecture is also open,such that third-party “metadata providers” can be plugged into the solution to address the needs of specific industries, use cases or geographic regions and languages. This layer is also designed to support not only text analytics, but technologies such as machine learning to improve performance over time based on user behavior,wherein content and information can be “recommended” to users. This could been visioned as something akin to “Netflix for the enterprise,” where in content like that one has retrieved before, or content that other sin similar roles have frequently accessed, is also suggested.