Business Dimensional Lifecycle

Business Dimensional Lifecycle

Business Dimensional Lifecycle stands for the time needed for designing, developing, and implementing data warehouse systems as reported by Kimball et al., (1998). . We will quickly review business dimensional lifecycle phases here.

1. The phase for project planning includes the definition of system goals and properties, an assessment of the impact on organizational practices, an estimate of costs and benefits, the allocation of required resources, and a preliminary plan for the project to be carried out.
2. The phase for business requirement definition plays a vital role in making sure that designers properly and fully understand users' needs, to maximize the benefits and the profitability of the system under construction. At this stage, designers should detect key factors of decision-making processes and turn them into design specifications. The definition of requirements creates three parallel tracks, each consisting of different phases: data, technology, and application.
3. The first phase of the data track is dimensional modeling. At this stage, user requirements and an analysis of operational sources should lead to the definition of data structures in a data warehouse. The final result is a set of logical schemata and a set of relationships with source schemata. The subsequent phase of the data track is physical design. It mainly deals with the issues of logical schemata to be optimized and implemented into the selected DBMS, such as indexing and partitioning. Eventually, the phase fordesigning and developing data staging includes all the issues linked with data extraction, transformation, loading, and, last but not least, quality.
4. The technology track includes an architecture design that is based on the current technical specifications for business information systems and performance requirements set forth by users. This track also shows a phase for product selection and installation to study and assess usable hardware platforms; DBMSs; Extraction, Transformation, and Loading tools (ETL); and additional data analysis tools available on the market.
5. If you follow the application track, you can collect the specifications for the applications that will provide end users with data access. You can also assess the need for reports to be created, interactive navigation of data, and automatic knowledge extraction (user application specification phase). The analysis tools selected in the product selection phase should be set up and configured accordingly (user application development phase).
6. The deployment phase involves all the tracks previously mentioned and leads to the system startup.
7. The deployment phase does not mean that a system lifecycle comes to its end. A system needs continuous maintenance to provide users with support and training.

Project management should be accurate in every data warehouse lifecycle phase. This allows you to keep tasks in sync, to monitor current project conditions, and to check that the design team is closely collaborating with users.