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Every organization needs an enterprise approach to manage its data assets; every program should be based on common guiding principles

Many organizations struggle to obtain the full benefits of their Enterprise Information Management (EIM) initiative by approaching the framework components as a set of projects and not as an interdependent program.  This type of approach leads to a series of separate, perhaps non-enterprise initiatives without a cohesive information strategy or goals. It is important to have a set of guiding principles to sustain an effective EIM program.

Framework Foundation

Every enterprise initiative needs to be built using a framework, which is a basic structure underlying a system, concept, or text.  It is a defined approach for making complex concepts understandable, manageable, and capable of implementation.  Since EIM, also known as “data management” is a complex set of components, it is essential to use a framework for organizing and implementing this collection of disciplines.

Without a framework, the various EIM component projects fail to leverage the possible collaboration and benefits that are required to build an efficient and agile data management organization.  As a result, the organization will be left without enhanced capabilities for information creation, capture, distribution, and consumption that could have been achieved if they had used an EIM Framework and discovered the connections among the components.

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Figure 1- Framework for Enterprise Information Management

After having accepted the framework, it is important for the organization to identify, accept, and communicate their EIM Guiding Principles.  These guiding principles should become part of the foundation in any successful EIM program.  They will serve as the basis for leveraging the dependencies between the EIM components that will enable the organization to achieve better, more robust, and more lasting results from their EIM program and the component projects.

There are some critical foundational areas and key activities that must be addressed before an organization can begin to use EIM principles and practices effectively to support existing or planned enterprise projects.  While time is of the essence in many organizations and a company must move as quickly as possible to support and address these critical enterprise projects, it is important to understand and apply the base foundational principles.

These guiding principles represent fundamental aspects about Enterprise Information Management, and how to implement it.  These key principles should shape and inform all organizational recommendations concerning EIM.  They also demonstrate some of the key dependencies that need to exist between the EIM components for an organization program to be successful.  These key principles may seem obvious, but many EIM efforts have failed by not adopting them.

  1. Data and information are enterprise assets.
    • As such, they must be managed to ensure quality, appropriate use and maximum business value.
    • Enterprise data orientation requires a conscious change of focus from individually developed applications to a unified, cross-functional view of data and its use as the foundation of information and knowledge.
    • Enterprise thinking requires stepping outside and beyond functional job responsibilities, interests and perspectives.
  2. Management of data assets is a shared responsibility between business data stewards and technical data stewards.
    • Business Data Stewards: Trustees of enterprise data assets, with assigned ownership and accountability on behalf of the enterprise.
    • Technical Data Stewards: Custodians of enterprise data assets, providing professional services and guidance under the governance of Business Data Stewards.
  3. Data governance and data stewardship are most effective when all participants take an enterprise-wide perspective.
    • An enterprise-wide Data Governance Council (DGC) should plan and oversee EIM strategy, policies, standards, projects and procedures, chaired by a Chief Data Steward (a senior business person) and the Data Governance Program leader (who should be a data governance professional).
    • Larger organizations should have a Data Stewardship Coordination Group composed of all the Lead Business Data Stewards from the various business areas, led by the a Chief Data Steward (a senior business person) and the Data Governance Program leader (who should be a data governance professional).  This group resolves data steward team challenges before they reach the Data Governance Council and supports the various data stewardship teams.
    • Data Stewardship teams should be organized by subject area, not by organization, function or application.
    • However, no two data stewardship and governance programs are alike – each must be customized based on these foundational principles for the organization and its culture.
  4. Metadata is the key to managing data assets.
    • The managed metadata environment (MME) is the platform supporting effective data management.
    • Metadata management enables data governance and provides the characteristics to measure data quality.
    • Metadata is the fabric that connects all of the other components of EIM; it is key for EIM success.
    • Metadata (including data definitions) is an enterprise resource contributing directly to improved information quality, reference & master data, and enterprise capabilities for data usage.
  5. The enterprise information architecture provides the blueprint for managing data assets.
    • The focus of information architecture is to define and use master blueprints for semantic and physical integration of enterprise data assets.
    • These master blueprints provide a clear definition of how the data is structured, collected, shared, maintained, and stored from both the IT and business community perspectives.
  6. Enterprise data warehousing and business intelligence is the most effective means of enabling more informed and effective decision-making.
    • Data warehousing / business intelligence environments must be managed to make data easy to access, understand, manipulate and safeguard.
    • The success of all analytics programs rely on the quality and accessibility of data and metadata.  These characteristics are the responsibility of EIM.
  7. Enterprise Information Management is not an easy effort; it is a strategic commitment and can be accomplished with consistent dedication from all parts of the enterprise.
    • Most organizations underestimate the complexity of EIM and the difficulty in establishing it.
    • EIM requires significant cultural changes and can be a very challenging effort.
    • EIM can be accomplished and has been successful implemented at many different types of organizations.


Organizations can realize many benefits from embracing an Enterprise Information Management initiative by adopting these key principles into their program and understanding the value that the guiding principles bring to the success of any EIM initiative, and to the realization of the organization’s general goals and objectives.


Dr. David P. Marco, LinkedIn Top BI Voice, IDMMA Data Mgt. Professional of the Year, Fellow IIM, CBIP, CDP

Dr. David P. Marco, PhD, Fellow IIM, CBIP, CDP is best known as the world’s foremost authority on data governance and metadata management, he is an internationally recognized expert in the fields of CDO, data management, data literacy, and advanced analytics. He has earned many industry honors, including Crain’s Chicago Business “Top 40 Under 40”, named by DePaul University as one of their “Top 14 Alumni Under 40”, and he is a Professional Fellow in the Institute of Information Management. In 2022, CDO Magazine named Dr. Marco one of the Top Data Consultants in North America and IDMMA named him their Data Management Professional of the Year. In 2023 he earned LinkedIn’s Top BI Voice. Dr. Marco won the prestigious BIG Innovation award in 2024. David Marco is the author of the widely acclaimed two top-selling books in metadata management history, “Universal Meta Data Models” and “Building and Managing the Meta Data Repository” (available in multiple languages). In addition, he is a co- author of numerous books and published hundreds of articles, some of which are translated into Mandarin, Russian, Portuguese, and others. He has taught at the University of Chicago and DePaul University.

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