This diagram shows the progression in a data-driven solution from strategic intent to measurable strategic outcome. This progression is a continuous cycle in which past measurable outcomes become input for future strategic intents.

The progression comprises the following data management steps, listed in sequence:

1. Discover: Discover and assess source data to deetermine if it addresses the use case requirements.
2. Connect, Ingest and Transform: Connect to the data sources, ingest data using several mechanisms, and transform it to address the use case.
3. Persist, Curate, Create: Persist transformed data as trusted, curated data from which data products are created to addresses current and future use cases.
4. Analyze, Learn, Predict: Analyze curated data products and information, gain new insights using both classical and generative AI and machine learning (ML) capabilities, and predict outcomes, helping you to make planned business decisions, rather than simply reacting to business events.
5. Measure, Act: Measure the business and anticipate future trends using trusted data products, KPIs, and AI and ML inferencing and then use these insights to improve measurable, strategic outcomes.