Standard Data model role in building Information Framework

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Overview

  1. First and foremost Industry-standard models represent a standard way of structuring, defining, and implementing an information framework.
  2. It provides a consistent and common vocabulary to cover enterprise knowledge at each abstraction level.
  3. It focuses on detailing the data landscape of an organization and best practices to cover the unknown requirements at the time of initiating a new request or during a change request.
  1. Data Elements
    It represents the metadata in a holistic manner so you can focus more on implementation rather than coverage aspects. It deals with common terms which are well understood across the partner ecosystem as well along with providing a consolidated and holistic Data Definition that helps you to jumpstart building the knowledge repository.
  2. Data structure
    It represents real-world information by translating real-world objects and their state representation in various ways by using Entity based model via the concept of decomposition of Hierarchies [subtype/role play/dynamic] and classification schemes.
  3. Data mapping
    At each abstraction level, data models enable you to map the information back to processes (business/technical) so it complements the business process(s) implementation in an unified manner.

Benefits

  1. Reduced time to market and thus expedites business solution
    In many ways, a template-based model substantially reduces the time to market for a product or feature implementation. While the common terminology aids the development/integration with the partner ecosystem the holistic nature of the data model provides coverage to all sets of requirements known/unknown. It often provides a jump start to all the teams involved in rapid prototyping the existing state of solution and also helps in doing the feasibility analysis of a new feature or solution
  2. Reduces cost of integration and improves overall efficiency
    When disparate teams converge on a common vocabulary, it is often observed that it improves the overall process efficiency by minimizing the cost of integration. Further, it aids the design of a unified business logic that can be implemented once and can be re-used by other teams.

Alignment to Data Strategy

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Balraj Bhardwaj

Balraj Bhardwaj

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