Scrum for Dealing With Big Data

What are companies doing with all the data collected? They are empirically identifying patterns and responding to what they’re learning from those patterns. As fast as the data can be collected, decisions about what to do with the data must be made even faster in order to achieve the goals of collecting the data: saving lives, reducing costs, innovating better solutions for customers, etc.

This is the scientific method: Hypothesis. Collect data. Analyze against the hypothesis. Repeat.

Scrum’s model for transparency drives frequent inspection and rapid adaptation to make sense of the rapidly growing world of data that surrounds us.


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