Architecture
Work with enterprise architects and enterprise information modellers to enable the efficient provision of data for analytical purposes — by using the appropriate business and technical architectures.
Improvement Planning
Practices-Outcomes-Metrics (POM)
Representative POMs are described for Architecture at each level of maturity.
- 2Basic
- Practice
- Work with enterprise architects and data modellers to agree the architecture guidelines for data analytics.
- Outcome
- There is awareness and agreement on the data analytics architecture guidelines.
- Metric
- Number of architecture guidelines for data analytics.
- 3Intermediate
- Practice
- Provide technology roadmaps for data analytics, highlighting where business value can be generated and created.
- Outcome
- The architecture roadmap provides guidance on the preferred organizational structures, processes, tools, and technologies that should be used and the timings for any proposed changes.
- Metrics
- Number of technology roadmaps in use for data analytics.
- Number of approved changes to data analytics roadmaps.
- 4Advanced
- Practice
- Monitor and enforce architectural compliance for supporting tools and technologies, with the guidelines and roadmap for data analytics.
- Outcome
- The supporting tools and technologies for data analytics comply with the architectural guidelines and roadmap, or are scheduled to be compliant.
- Metric
- Percentage compliance of supporting tools and technologies for data analytics with the guidelines and roadmap.
- 5Optimized
- Practice
- Use the latest research available, including vendor and industry best practices, to drive continuous architectural improvement.
- Outcome
- The organization is aware of and uses all of the available options for data analytics, when and where they are appropriate.
- Metric
- Number of improvements to the architecture for data analytics in the last year.