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At a minimum, there should be separate physical application and database servers as well as separate ETL/ELT, OLAP, cube, and reporting processes set up for development, testing, and production.Building separate physical environments ensure that all changes can be tested before moving them to production, development, and testing can occur without halting the production environment, and if data integrity becomes suspect, the IT staff can investigate the issue without negatively impacting the production environment.Developing a disaster recovery plan while gathering requirements, ensures that the organization is prepared to respond quickly to direct and indirect threats to the data warehouse.Once the business requirements are set, the next step is to determine the physical environment for the data warehouse.Not updating either of them in a timely manner could lead to reduced system performance.Taking the time to explore the most efficient OLAP cube generation path can reduce or prevent performance problems after the data warehouse goes live.Once requirements gathering and physical environments have been defined, the next step is to define how data structures will be accessed, connected, processed, and stored in the data warehouse. During this phase of data warehouse design, is where data sources are identified.
The goal of ETL is to provide optimized load speeds without sacrificing quality.
The three critical elements of OLAP design include: During development, make sure the OLAP cube process is optimized.
A data warehouse is usually not a nightly priority run, and once the data warehouse has been updated, there little time left to update the OLAP cube.
At this point, business requirements have been captured, physical environment complete, data model decided, and ETL process has been documented.
The next step is to work on how users will access the data warehouse.