Providing solutions since 1994

Data Warehouse Methodology

The bulleted items below summarize the five major steps in creating a data warehouse. Although every project possesses some distinctive characteristics, and we reflect those considerations in the project plan, our basic methodology remains consistent.

  • Meet with client personnel to identify immediate and long–term data requirements.
  • Produce a Requirements Specification for the client’s approval.
  • Assemble a Design Specification, beginning with recommendations for the necessary hardware and Business Intelligence software. The Design Specification also includes a data model and mock–ups of the key user interface screens. Work with the client’s project team to refine the design for client approval.
  • Develop, test, and document the software described in the Design Specification. Throughout this process, transfer knowledge about system support and long–term maintenance to the client’s IT staff.
  • Prior to the production roll–out of the data warehouse, provide “train the trainer” instruction for end users of the system.

There is a range of other data warehouse concepts and methodologies including:<?p>

  • Logical data model
  • Conceptual data model
  • Physical data model
  • Star Schema
  • Data mining
  • Staging area
  • Multi-dimensional analysis
  • Snowflake schema
  • OLAP tools