This diagram shows the progression in a data-driven solution from strategic intent to measurable strategic outcome.

The progression comprises the following data management steps, listed in sequence:
  1. Discover
  2. Connect and ingest
  3. Transform
  4. Persist, curate and create
  5. Analyze, learn and predict
  6. Measure and act

Within the data management progression are the following conceptual stages, listed in sequence:

  1. Understand (data pattern-driven characteristics): Spans the data management steps:
    • Discover
    • Connect and ingest

    Data science methodologies identify and validate data from all available sources so the enterprise can leverage the data to produce insights and measurable value.

  2. Create (technology-driven characteristics): Spans the data management steps:
    • Connect and ingest
    • Transform
    • Persist, curate and create
    • Analyze, learn and predict

    A flexible and efficient technology platform stores and transforms the data for high-value outcomes based on the ever-increasing and changing flow of data.

  3. Use (development-driven characteristics): Spans the data management steps:
    • Analyze, learn and predict
    • Measure and act

    Advanced analytics and visualization methods leverage the data to help produce new models, services, and experiences that address the enterprise's key performance indicators (KPI).