es and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence pr

During the design of a BI infrastructure, certain well known steps should be followed:
• prioritization of business processes, to be monitored vis-?-vis their performance
• development of a roadmap for a phased implementation (e.g. using the bus architecture matrix in a dimensional infrastructure)
• business requirements analysis with the SME’s
• data source & organizational readiness assessment
• translation of business requirements into conceptual data modeling
• definition of analytical applications to be implemented
• decisions on the sourcing model (insourced / outsourced)

Whether the whole endeavor or parts of it, is insourced or outsourced, directly influences the needed internal know-how and skills and affects the degree of control of the Business. Strategic know how and skills should not be outsourced, since they can evolve to an important competitive advantage for the Business.

If all work is left to a consultant-integrator Consortium, the Business runs the risk of loosing control and being led to suboptimal decisions, techniques or infrastructure architectures.

How many design steps and which distinct design skills are needed before implementation starts, is not successfully determined by many Businesses. A Consultant who is specializing in datawarehouse design and/or dimensional modeling is often not skilled enough to analyse business requirements and identify analytical applications to be implemented (e.g. a data modeler is often not knowledgeable on Customer segmentation and/or Customer retention techniques). Therefore he may not be able to identify the information needed, or the facts to be derived. On the other hand, a database marketing specialist is often unable to evaluate BI infrastructure architectures and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence pro

equirements into conceptual data modeling
• definition of analytical applications to be implemented
• decisions on the sourcing model (insourced / outsourced)

Whether the whole endeavor or parts of it, is insourced or outsourced, directly influences the needed internal know-how and skills and affects the degree of control of the Business. Strategic know how and skills should not be outsourced, since they can evolve to an important competitive advantage for the Business.

If all work is left to a consultant-integrator Consortium, the Business runs the risk of loosing control and being led to suboptimal decisions, techniques or infrastructure architectures.

How many design steps and which distinct design skills are needed before implementation starts, is not successfully determined by many Businesses. A Consultant who is specializing in datawarehouse design and/or dimensional modeling is often not skilled enough to analyse business requirements and identify analytical applications to be implemented (e.g. a data modeler is often not knowledgeable on Customer segmentation and/or Customer retention techniques). Therefore he may not be able to identify the information needed, or the facts to be derived. On the other hand, a database marketing specialist is often unable to evaluate BI infrastructure architectures and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence pr

t competitive advantage for the Business.

If all work is left to a consultant-integrator Consortium, the Business runs the risk of loosing control and being led to suboptimal decisions, techniques or infrastructure architectures.

How many design steps and which distinct design skills are needed before implementation starts, is not successfully determined by many Businesses. A Consultant who is specializing in datawarehouse design and/or dimensional modeling is often not skilled enough to analyse business requirements and identify analytical applications to be implemented (e.g. a data modeler is often not knowledgeable on Customer segmentation and/or Customer retention techniques). Therefore he may not be able to identify the information needed, or the facts to be derived. On the other hand, a database marketing specialist is often unable to evaluate BI infrastructure architectures and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence pr

dimensional modeling is often not skilled enough to analyse business requirements and identify analytical applications to be implemented (e.g. a data modeler is often not knowledgeable on Customer segmentation and/or Customer retention techniques). Therefore he may not be able to identify the information needed, or the facts to be derived. On the other hand, a database marketing specialist is often unable to evaluate BI infrastructure architectures and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence pr

es and data models which are suitable for the analytical applications identified (e.g. how to model a data mart aiming to perform RFM analysis).

It is clearly identified by many BI thought leaders that BI professionals need to have both business & IT know-how and skills.

At the leadership level, the success of a business intelligence endeavor often depends on the ability to ‘see the whole picture’. In case of a Customer Intelligence project, combined skills of the project leader, on the identification of the appropriate marketing strategy and the implementation of the latter based on a successful design & implementation, allow him to identify issues early-on and steer the project successfully.

On the other hand, if we have to decide on the most critical success factor, business requirements analysis comes first. A leader with a clear vision on the business goals and the strategy to achieve them, can probably search and find the rest of the skills. Some may argue though, that it’s not possible to identify the full set of business requirements in advance, in a dynamically changing environment. Therefore the design of a flexible & extensible data model, would allow future enhancements.