RiverPoint uses a rigorous approach for developing the data warehouse framework that today’s marketing and business intelligence solutions are based upon. This approach contains all the tasks for the data warehouse design, state-of-the-art matching technology, ETL development, reporting, and ad-hoc analysis. This approach outlines specific checkpoints for progress review and management update and develops a business-driven solution to meeting an organization’s analytical and operational information processing needs. Together, these objectives ensure a high quality, consistent, rapid approach to building flexible and scalable data warehouses
The RiverPoint data warehousing methodology represents a structured approach to planning and developing a marketing data warehouse. Our approach presents a development framework with seven tracks: Business Requirements, Operations, Data Modeling, Data Acquisition, Metadata, Technical, and Management. The use of tracks in the methodology emphasizes work being done in parallel by the project team and provides focus and responsibility for those individuals working within a track. Each step within the tracks has a deliverable. In aggregate, these deliverables comprise the work needed to successfully deliver a data warehouse/data mart implementation. There are appropriate quality assurance review and checkpoints within the phases for approvals on all deliverable and design directions.