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Outcome (O)

The data scientist wants to know how the data and/or insights will be used. How will it be integrated into the organisation? Who will use the data, and why?

An example of outcome: The marketing team needs to be trained in using the model (or software) to guide their decisions, and the success of the model needs to be gauged in its effect on the sales..

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Most people approach data the wrong way: They start with a data set, then use their favourite tools and techniques on it. This produces a narrow set of unsurprising results.

Vision is when we take a glimpse of what it will look like to meet the need with data. The vision consist of the following:

We find context when we know who we are working with and why they're doing what they are doing. We learn the context when we talk to them about their long-term goals. The context provides a project with larger goals and helps to keep us on track.

We can find structure when we create the scope for a data problem. A scope is the outline of a story of why we are focusing on this problem.

What needs could be fixed by intelligently using data? When we clearly explain a need, we are showing what could be improved by better knowledge.

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