Evolution of data science
Data-informed decisions will continue to be important for the next few decades, while data-driven decision making can only improve with the help of informed data.
The difference between data-informed decision making and data-driven decision making:
- Setting goals. Goals are measurable and quantifiable. Identifying and tracking goals are becoming increasingly data-driven. But setting the right quarterly and annual goals can only be partly automated.
- The process of defining a roadmap and strategy is mostly data-informed.
- Forecasting outcomes are primarily data-driven.
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