Data visualization: how important is it to communicate results in an understandable way? Should we be explaining our models to the organizations and people we hand them to? Should there be full transparency regarding the decisions made in the work?


Data visualization plays the key role in the interpretation of the communicated information by the audience. A variety of methods can be used to communicate information including textual forms, however, these are often overwhelming to interpret due to complexity or/and amount of data. As a result, the audience can misinterpret the information which is why it is crucial to present data in a way which is easily understood.

I think we should understand the target audience before deciding the inclusion and exclusion of the models. But, yes we should try to make people understand the working of the model using some user stories. 
When we are handing over our models, the recipient can be a team from the business side and IT people. Business people will be interested in the results and IT people will be interested in "HOW" we have achieved those results? 

Yes, I agree with this point. We should have transparency in the work. We should involve the people from the organization, discuss with them our outline, take their views, hold a debate and finally draft the final flow of the project. Keep the users of the products in the loop is referred as Agile development. It helps the user, to know how the system works, what it can do, what it can't-do and what should be added as future development.

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