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.

When we want to gain knowledge from the data, we should first do some thinking.

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.

The scope of a project consists of four parts, which is expressed as the mnemonic CoNVO.

• Context
• ...

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.

An example of c...

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.

An example of needs:  We want to place our ads in a smart way. What should we be optimising?

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:

• A mockup explaining the intended results: It could take the form of reporting the outcome of the analysis in a few sentences, a ...

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 so...