- Data warehouse implementation is a costly and complex undertaking, and can end up not serving the business' needs appropriately.
- Too heavy a focus on technology creates a data warehouse that isn’t sustainable and ends up with poor adoption.
- Emerging data sources and technologies add complexity to how the appropriate data is made available to business users.
Our Advice
Critical Insight
- A data warehouse is a project; but successful data warehousing is a program. An effective data warehouse requires planning beyond the technology implementation.
- Governance, not technology needs to be the core support system for enabling a data warehouse program.
- Understand business processes at the operational, tactical, and ad hoc levels to ensure a fit-for-purpose DW is built.
Impact and Result
- Leverage an approach that focuses on constructing a data warehouse foundation that is able to address a combination of operational, tactical, and ad hoc business needs.
- Invest time and effort to put together pre-project governance to inform and provide guidance to your data warehouse implementation.
- Develop “Rosetta Stone” views of your data assets to facilitate data modeling.
- Select the most suitable architecture pattern to ensure the data warehouse is “built right” at the very beginning.
Build an Extensible Data Warehouse Foundation Research & Tools
Start here – read the Executive Brief
Read our concise Executive Brief to find out why the data warehouse is becoming an important tool for driving business value, review Info-Tech’s methodology, and understand the four ways we can support you in completing this project.Besides the small introduction, subscribers and consulting clients within this management domain have access to:
- Build an Extensible Data Warehouse Foundation – Phases 1-3
1. Prepare for the data warehouse foundation project
Begin the data warehouse foundation by defining the project and governance teams, as well as reviewing supporting data management practices.
- Build an Extensible Data Warehouse Foundation – Phase 1: Prepare for the Data Warehouse Foundation Project
- Data Warehouse Foundation Project Plan Template
- Data Warehouse Work Breakdown Structure Template
- Data (Warehouse) Architect
- Data Integration Specialist
- Business Intelligence Specialist
- Director of Data Warehousing/Business Intelligence
- Data Warehouse Program Charter Template
- Data Warehouse Steering Committee Charter Template
2. Establish the business drivers and data warehouse strategy
Using the business activities as a guide, develop a data model, data architecture, and technology plan for a data warehouse foundation.
- Build an Extensible Data Warehouse Foundation – Phase 2: Establish the Business Drivers and Data Warehouse Strategy
- Business Data Catalog
- Data Classification Inventory Tool
- Data Warehouse Architecture Planning Tool
- Master Data Mapping Tool
3. Plan for data warehouse governance
Start developing a data warehouse program by defining how users will interact with the new data warehouse environment.
- Build an Extensible Data Warehouse Foundation – Phase 3: Plan for Data Warehouse Governance
- Data Warehouse Standard Operating Procedures Template
- Data Warehouse Service Level Agreement
Workshop: Build an Extensible Data Warehouse Foundation
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 delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
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
1.1 Identify foundation project team and create a RACI chart.
1.2 Understand what a data warehouse can and cannot enable.
1.3 Define critical success factors, key performance metrics, and project risks.
1.4 Develop rough timelines for foundation project completion.
1.5 Define the current and future states for key data management practices.
Outputs
Job Descriptions and RACI
Data Warehouse Steering Committee Charter
Data Warehouse Foundation Project Plan
Work Breakdown Structure
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
2.1 Understand the most fundamental needs of the business.
2.2 Define the data warehouse vision, mission, purpose, and goals.
2.3 Detail the most important operational, tactical, and ad hoc activities the data warehouse should support.
2.4 Link the processes that will be central to the data warehouse foundation.
2.5 Walk through the four-column model and business entity modeling as a starting point for data modeling.
2.6 Create data models using the business data glossary and data classification.
2.7 Identify master data elements to define dimensions.
2.8 Design lookup tables based on reference data.
2.9 Create a fit-for-purpose data warehousing model.
Outputs
Data Warehouse Program Charter
Data Warehouse Vision and Mission
Documentation of Business Processes
Business Entity Map
Business Data Glossary
Data Classification Scheme
Data Warehouse Architecture Model
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
3.1 Develop a technology capability map to visualize your desired state.
3.2 Establish a data warehouse center of excellence.
3.3 Create a data warehouse foundation roadmap.
3.4 Define data warehouse service level agreements.
3.5 Create standard operating procedures.
Outputs
Technology Capability Map
Project Roadmap
Service Level Agreement
Data Warehouse Standard Operating Procedure Workbook