Build an Extensible Data Warehouse Foundation
Establish a well-architected core model with just enough oversight and governance.
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Data warehouse implementation that focuses too heavily on technology results in:
- A mismatch between business needs and platform services.
- Greater business-user frustration due to information needs not being met.
- A lack of enterprise-adoption and greater distrust of IT.
- An inability to produce efficient, repeatable, and reliable reporting that can be shared cross-functionally to create collective wisdom.
An initial project that places emphasis on governance and data modeling:
- Helps subsequent iterations on the foundation stay in line with the overall data warehouse vision.
- Provides a clearer understanding of the business needs and processes that will simplify technology selection.
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Onsite Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn’t enough, we offer low-cost onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.
Book NowModule 1: Prepare for the Data Warehouse Foundation Project
The Purpose
- Identify the members of the foundation project team.
- Define overarching statements and define success factors/risks.
- Outline basic project governance.
Key Benefits Achieved
- Defined membership, roles, and responsibilities involved in the foundation project.
- Establishment of a steering committee as a starting point for the data warehouse program.
| Activities: | Outputs: | |
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| 1.1 | Identify foundation project team and create a RACI chart. |
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| 1.2 | Understand what a data warehouse can and cannot enable. |
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| 1.3 | Define critical success factors, key performance metrics, and project risks. |
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| 1.4 | Develop rough timelines for foundation project completion. |
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| 1.5 | Define the current and future states for key data management practices. |
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Module 2: Establish the Business Drivers and Data Warehouse Strategy
The Purpose
- Define the information needs of the business and its key processes.
- Create the components that will inform an appropriate data model.
- Design a data warehouse architecture model.
Key Benefits Achieved
- Clear definition of business needs that will directly inform the data and architecture models.
| Activities: | Outputs: | |
|---|---|---|
| 2.1 | Understand the most fundamental needs of the business. |
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| 2.2 | Define the data warehouse vision, mission, purpose, and goals. |
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| 2.3 | Detail the most important operational, tactical, and ad hoc activities the data warehouse should support. |
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| 2.4 | Link the processes that will be central to the data warehouse foundation. |
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| 2.5 | Walk through the four-column model and business entity modeling as a starting point for data modeling. |
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| 2.6 | Create data models using the business data glossary and data classification. |
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| 2.7 | Identify master data elements to define dimensions. |
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| 2.8 | Design lookup tables based on reference data. |
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| 2.9 | Create a fit-for-purpose data warehousing model. |
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Module 3: Plan for Data Warehouse Governance
The Purpose
- Create a plan for governing your data warehouse efficiently and effectively.
Key Benefits Achieved
- Documentation of current standard operating procedures.
- Identified members of a data warehouse center of excellence.
| Activities: | Outputs: | |
|---|---|---|
| 3.1 | Develop a technology capability map to visualize your desired state. |
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| 3.2 | Establish a data warehouse center of excellence. |
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| 3.3 | Create a data warehouse foundation roadmap. |
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| 3.4 | Define data warehouse service level agreements. |
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| 3.5 | Create standard operating procedures. |
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