- Chris Debo, Senior Manager, Schneider Downs & Co., Inc.
- Jaison Dominic, Lead Architect, Enterprise Data Warehouse, Moffitt Cancer Center
- Liselle Ramcharan, Project Manager, TD Insurance
- Randy Piscione, Enterprise Data Architect, BMO Financial Group
- Sree Pulapaka, Director of Enterprise Business Innovation and Analytics, Metropolitan Washington Airports Authority
- 1 anonymous contributor
- 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.
- 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.
This guided implementation is a seven call advisory process.
Guided Implementation #1 - Prepare for the data warehouse foundation project
Call #1 - Discuss structuring your project team, defining success metrics and risks, and organizing a steering committee.
Call #2 - Discuss the impacts of other data management practices on your data warehouse foundation project.
Guided Implementation #2 - Establish the business drivers and data warehouse strategy
Call #1 - Walk through how to characterize operational, tactical, and ad hoc business processes that will guide the data warehouse.
Call #2 - Discuss the four “Rosetta Stones” for data modeling.
Call #3 - Develop an architecture strategy based on business and data needs, and review the data warehouse vendor landscape.
Guided Implementation #3 - Plan for data warehouse governance
Call #1 - Plan for the formation of a data warehouse center of excellence.
Call #2 - Discuss defining standard operating procedures and service-level agreements for the data warehouse.
Book Your Workshop
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 roadmap in place to complete your project successfully.
Module 1: Prepare for the Data Warehouse Foundation Project
- 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.
Identify foundation project team and create a RACI chart.
- Job Descriptions and RACI
- Data Warehouse Steering Committee Charter
Understand what a data warehouse can and cannot enable.
Define critical success factors, key performance metrics, and project risks.
- Data Warehouse Foundation Project Plan
Develop rough timelines for foundation project completion.
- Work Breakdown Structure
Define the current and future states for key data management practices.
Module 2: Establish the Business Drivers and Data Warehouse Strategy
- 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.
Understand the most fundamental needs of the business.
- Data Warehouse Program Charter
Define the data warehouse vision, mission, purpose, and goals.
- Data Warehouse Vision and Mission
Detail the most important operational, tactical, and ad hoc activities the data warehouse should support.
Link the processes that will be central to the data warehouse foundation.
- Documentation of Business Processes
Walk through the four-column model and business entity modeling as a starting point for data modeling.
- Business Entity Map
Create data models using the business data glossary and data classification.
- Business Data Glossary
- Data Classification Scheme
Identify master data elements to define dimensions.
Design lookup tables based on reference data.
Create a fit-for-purpose data warehousing model.
- Data Warehouse Architecture Model
Module 3: Plan for Data Warehouse Governance
- 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.
Develop a technology capability map to visualize your desired state.
- Technology Capability Map
Establish a data warehouse center of excellence.
Create a data warehouse foundation roadmap.
- Project Roadmap
Define data warehouse service level agreements.
- Service Level Agreement
Create standard operating procedures.
- Data Warehouse Standard Operating Procedure Workbook
After each Info-Tech experience, we ask our members to quantify the real time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this Blueprint, and what our clients have to say.