
How can we build a (healthier; safer; resilient) world?
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When asking a question, we first need to access to all data in an organization – in one place.
SAS helps you capture this in the data catalog, create metadata and profile the quality of the data. Once we’ve done that, we can join it from different data sets, adding new calculations and building derived columns. The goal? To make a prediction or classification.
We can take a data set and build a tournament of models throughout the enterprise.
From this, we can determine the champion model, which performed the best at predicting the target variable.
During this phase of the life cycle, we can manage the model, allowing us to group it with other models or decisioning assets.
Now we can deploy this model into a business process. In your case, it might be a clinical pathway where we need to make a decision about the right care for the patient. Then, we have to monitor the model’s performance.
We can continue to iterate and learn using the analytics life cycle.
This is how you leverage data and AI to scale human productivity and decision-making. Because, if you’re learning faster, you’re one step closer to a healthier world.





