Data Gathering
Identify data from internal and external sources that is likely to deliver on the analytical goals and objectives and make it available for analytic processing.
Improvement Planning
Practices-Outcomes-Metrics (POM)
Representative POMs are described for Data Gathering at each level of maturity.
- 2Basic
- Practice
- Set out and document the data collection goals, to identify and gain access to the pertinent data sets.
- Outcome
- The focus is on identifying and accessing pertinent data sets.
- Metrics
- Number of data sets identified.
- Number of data sets that can be accessed.
- 3Intermediate
- Practice
- Develop operational definitions and procedures so that the correct data sources are identified and made available for analytics.
- Outcome
- Data sources are identified and made available for analytics.
- Metric
- Number of data sets available to analytics.
- 4Advanced
- Practice
- Use metadata standardization and enrichment, together with research and experimentation to collect and supplement the existing data, and to answer new questions.
- Outcome
- Metadata standardization and enrichment are used to combine existing with new data, and to address new questions.
- Metric
- Number of external data sets used by analytics.
- 5Optimized
- Practice
- Regularly update and improve the data gathering processes based on feedback from across the business ecosystem and the latest research from academia, vendors, and industry.
- Outcomes
- Research identifies new data sets and new combinations of data sets for analytics.
- Data collection is continually and effectively readjusted in line with changes in requirements and input from research.
- Metrics
- Number of new and revised data sets identified.
- Number of improvements to the data gathering process.