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. Ingest, Transform
  3. Persist, Curate, Create
  4. Analyze, Learn, Predict
  5. 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
    • Ingest, Transform

    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. Manage (Technology-driven Characteristics): Spans the data management steps:
    • Ingest, Transform
    • Persist, Curate, Create
    • Analyze, Learn, 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. Exploit (Development-driven Characteristics): Spans the data management steps:
    • Analyze, Learn, Predict
    • 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).