Machines learn from data.
People learn from data.
People learn from people.
As we know, people engage with data in a variety of ways:
- Strategize – Define the vision, goals, and purpose for data use.
- Architect – Design scalable, efficient data systems and pipelines.
- Collect – Gather raw data from various sources.
- Transform – Clean, structure, and prepare data for use.
- Enrich – Add context, making data more meaningful.
- Store – Securely maintain data for accessibility and longevity.
- Govern – Ensure quality, security, and compliance.
- Describe – Summarize trends, patterns, and past events.
- Analyze – Extract insights and valuable patterns.
- Interpret – Make sense of the findings in context.
- Label – Assign meaning for machine learning models.
- Visualize – Communicate insights effectively.
- Model – Simulate scenarios and explore possibilities.
- Predict – Forecast likely outcomes based on trends.
- Prescribe – Recommend actions based on insights.
- Automate – Enable intelligent systems to take action at scale.
- Decide – Drive business impact through informed choices.