The Inmon approach (marketed as Corporate Information Factory) involves the holistic view of the Enterprise and its informational needs. First implementation step, according to this approach, is the design of the Enterprise data model, supporting all its activities with completeness and sufficient detail ((‘atomic data model’). This is not any existing database model, but an abstract model of the information, actually used by the Enterprise. The data model of the so called ‘Enterprise Data warehouse’ is designed based on this abstract model. Data are extracted from all operational systems and other sources and the unique ‘Enterprise Data warehouse’ is updated through an ETL process (as described in Part 1). Moreover, implementation of an integrated operational database, covering all the Enterprise, is proposed if operational systems are not integrated. This is known as an Operational Data Store (ODS), and has a dual role:

· Serving operational processes

· Support operational reporting & decision making. If an ODS is developed, it becomes the primary source of the Enterprise Datawarehouse. In that way, the implementation of ETL (extraction-transformation-loading) streams from multiple data sources is avoided.

According to the Inmon approach, data marts should be ‘fed’ exclusively from the ‘Enterprise Data warehouse’, in order to assure the single version of truth. This approach is known in the literature as ‘dependent data mart’ approach, given that the data marts depend on the ‘Enterprise Data warehouse’. According to Inmon, the development of independent data marts (which are fed directly from operational systems) creates information silos which are uncoupled, do not assure the single version of truth and do not allow the combined information analysis. Moreover, Inmon asserts that the existence of many independent data marts increases the staging area complexity (this assertion assumes that datamarts are unconnected).

The Inmon approach has received criticism focused on the following:

• The design method of the abstract Enterprise ‘data model’ is not clarified, given that in most cases information use is not standardised nor documented. The concept of the Enterprise ‘data model’ is abstract and unclear, therefore it is difficult to design such a model which can reflect successfully the reality for a long term period. The argument is further enforced by the fact that the business environment is rapidly changing in many markets.
• one-off development of the information model does not follow the general principle for phased-iterative development supported by post implementation review of each phase.
• it is a high risk approach, since it requires high investment in money and time for the design of the data model and the development of the Enterprise Data warehouse-EDW) which covers all the needs of the Enterprise. This argument is countered by s
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  ase model, but an abstract model of the information, actually used by the Enterprise. The data model of the so called ‘Enterprise Data warehouse’ is designed based on this abstract model. Data are extracted from all operational systems and other sources and the unique ‘Enterprise Data warehouse’ is updated through an ETL process (as described in Part 1). Moreover, implementation of an integrated operational database, covering all the Enterprise, is proposed if operational systems are not integrated. This is known as an Operational Data Store (ODS), and has a dual role:

  · Serving operational processes

  · Support operational reporting & decision making. If an ODS is developed, it becomes the primary source of the Enterprise Datawarehouse. In that way, the implementation of ETL (extraction-transformation-loading) streams from multiple data sources is avoided.

  According to the Inmon approach, data marts should be ‘fed’ exclusively from the ‘Enterprise Data warehouse’, in order to assure the single version of truth. This approach is known in the literature as ‘dependent data mart’ approach, given that the data marts depend on the ‘Enterprise Data warehouse’. According to Inmon, the development of independent data marts (which are fed directly from operational systems) creates information silos which are uncoupled, do not assure the single version of truth and do not allow the combined information analysis. Moreover, Inmon asserts that the existence of many independent data marts increases the staging area complexity (this assertion assumes that datamarts are unconnected).

  The Inmon approach has received criticism focused on the following:

  • The design method of the abstract Enterprise ‘data model’ is not clarified, given that in most cases information use is not standardised nor documented. The concept of the Enterprise ‘data model’ is abstract and unclear, therefore it is difficult to design such a model which can reflect successfully the reality for a long term period. The argument is further enforced by the fact that the business environment is rapidly changing in many markets.
  • one-off development of the information model does not follow the general principle for phased-iterative development supported by post implementation review of each phase.
  • it is a high risk approach, since it requires high investment in money and time for the design of the data model and the development of the Enterprise Data warehouse-EDW) which covers all the needs of the Enterprise. This argument is countered by
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    ational reporting & decision making. If an ODS is developed, it becomes the primary source of the Enterprise Datawarehouse. In that way, the implementation of ETL (extraction-transformation-loading) streams from multiple data sources is avoided.

    According to the Inmon approach, data marts should be ‘fed’ exclusively from the ‘Enterprise Data warehouse’, in order to assure the single version of truth. This approach is known in the literature as ‘dependent data mart’ approach, given that the data marts depend on the ‘Enterprise Data warehouse’. According to Inmon, the development of independent data marts (which are fed directly from operational systems) creates information silos which are uncoupled, do not assure the single version of truth and do not allow the combined information analysis. Moreover, Inmon asserts that the existence of many independent data marts increases the staging area complexity (this assertion assumes that datamarts are unconnected).

    The Inmon approach has received criticism focused on the following:

    • The design method of the abstract Enterprise ‘data model’ is not clarified, given that in most cases information use is not standardised nor documented. The concept of the Enterprise ‘data model’ is abstract and unclear, therefore it is difficult to design such a model which can reflect successfully the reality for a long term period. The argument is further enforced by the fact that the business environment is rapidly changing in many markets.
    • one-off development of the information model does not follow the general principle for phased-iterative development supported by post implementation review of each phase.
    • it is a high risk approach, since it requires high investment in money and time for the design of the data model and the development of the Enterprise Data warehouse-EDW) which covers all the needs of the Enterprise. This argument is countered by
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      operational systems) creates information silos which are uncoupled, do not assure the single version of truth and do not allow the combined information analysis. Moreover, Inmon asserts that the existence of many independent data marts increases the staging area complexity (this assertion assumes that datamarts are unconnected).

      The Inmon approach has received criticism focused on the following:

      • The design method of the abstract Enterprise ‘data model’ is not clarified, given that in most cases information use is not standardised nor documented. The concept of the Enterprise ‘data model’ is abstract and unclear, therefore it is difficult to design such a model which can reflect successfully the reality for a long term period. The argument is further enforced by the fact that the business environment is rapidly changing in many markets.
      • one-off development of the information model does not follow the general principle for phased-iterative development supported by post implementation review of each phase.
      • it is a high risk approach, since it requires high investment in money and time for the design of the data model and the development of the Enterprise Data warehouse-EDW) which covers all the needs of the Enterprise. This argument is countered by
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        difficult to design such a model which can reflect successfully the reality for a long term period. The argument is further enforced by the fact that the business environment is rapidly changing in many markets.
      • one-off development of the information model does not follow the general principle for phased-iterative development supported by post implementation review of each phase.
      • it is a high risk approach, since it requires high investment in money and time for the design of the data model and the development of the Enterprise Data warehouse-EDW) which covers all the needs of the Enterprise. This argument is countered by suggesting a phased implementation of the EDW, dealing in each phase with one or few enterprise subject areas.
      Copyright 2006 – Kostis Panayotakis