Ability to change fast and frequently extends beyond the warehouse development process. Changes that occur in business requirements can be met with quick response. Responding to change in real time and without the delay of lengthy projects is the essence of business agility.
Speed is the critical factor that enables agility both for agile business and for agile development. Ability to generate quickly and to regenerate equally fast when change occurs are fundamental automation capabilities. The ability to fail fast is also important. Sometimes warehousing teams can’t deliver what the business needs due to data unavailability, data quality issues, or elusive and difficult to define business rules. Discovering these issues as early as possible reduces waste of time and resources.
Beyond developing and changing a data warehouse, automation offers many technical benefits that contribute to extended lifespan and ease of operations for the warehouse. Consistency of components in a data warehouse is improved through the ability to build in standards and conventions. Automated documentation capabilities ensure comprehensive documentation that stays in sync with the implementation. Impact analysis for planned changes is supported with extensive metadata capabilities. Testing is simplified with test automation both during development and as a validation capability of operations processes. Maintenance becomes easier with improved consistency, better documentation, simplified testing, version control, automated implementation of changes and standardized deployment methodology.
Ultimately, building better, building faster, and changing quickly when needed bring substantial cost savings to data warehouse development, operation, maintenance, and evolution.
Data warehouse automation delivers quality and effectiveness through the ability to build better solutions. Better solutions are those that best meet real business requirements, and it is especially difficult to get complete and correct requirements when limited to an early phase of a linear development process. With data warehouse automation, the business can make changes much later in the development process and change can occur more frequently with less disruption, waste, and rework. Iterative requirements discovery, however, is only one aspect of data warehouse quality. Automation brings quality benefits through standards enforcement and standardizing development processes.