One of the major issues enterprises have is tapping into business information that’s trapped in many different siloed applications. Customer data platforms (CDPs) are supposed to unify structured data about customers from several siloed applications and make that information accessible to a broad range of users.
However, textual content, because it behaves differently in digital form, is disconnected from images and video, which are in turn disconnected from customer transactional data. Yet, API-centric enterprises could work across all of these silos, orchestrating both content and data resources so they could be custom assembled and delivered to a range of different external and internal consumers. Such a metasystem, or “system of systems,” can harness content and data teams together to solve internal business issues as well as improve customer outreach.
What’s needed for cross-enterprise content and structured data orchestration at scale is a tiered grouping of ontologies and taxonomies that disambiguate and connect the different business contexts in a logically consistent way. Large enterprises have content, knowledge management, and data management managed separately. Software that manages information resources most often is designed to handle content or structured data separately, not both. Software is most often designed to divide and conquer rather than unify.
Teams responsible for orchestration have to work across these departments. They have to deal with data and content cartels of the kind that prosper under passive leadership. Orchestration initiatives will often suffer delays resulting from attempts to gain access permission to content and data repositories.
The need for orchestration becomes yet another argument for fundamental data layer transformation. Fundamental transformation tackles the organizational issues, the architectural shortfalls, and the data and content problems holistically.
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