Analytics Technology Fit
Select technologies that work in an integrated or interoperable manner and that support the required usage models — e.g. individual data exploration, embedded or automated analysis, and so forth.
Improvement Planning
Practices-Outcomes-Metrics (POM)
Representative POMs are described for Analytics Technology Fit at each level of maturity.
- 2Basic
- Practice
- Select and implement basic tools and technologies that staff can utilize for data analytics (e.g. spreadsheets or SQL).
- Outcome
- A basic toolset is used for data analytics and to access the available data sets.
- Metric
- Number of tools and technologies that support data analytics.
- 3Intermediate
- Practice
- Provide professional grade analytics tool sets to enable an effective data analytics service.
- Outcome
- Analytical technologies deliver data analytical goals from organization-wide data sets while protecting business operations from errant queries.
- Metric
- Number of tools and technologies that directly support the goals for data analytics.
- 4Advanced
- Practice
- Use advanced tools and technologies that provide comprehensive integration and interoperability to support advanced models for data analytics.
- Outcome
- Advanced analytical technologies deliver advanced goals and objectives.
- Metric
- Number of tools and technologies that exceed expectations for data analytics.
- 5Optimized
- Practice
- Enable and use the most advanced capabilities of the data analytics tool sets to answer complex data analytics questions.
- Outcome
- Data analysts are equipped with the best tool sets, that seamlessly interoperate or integrate with business ecosystem data sets, and are enabled to satisfy the most demanding data analytical tasks.
- Metric
- Cost to implement, integrate, and operate data analytics tools and technologies.