Frankly, that might seem like a secondary job. Data is important, data driven decisions are crucial. But the visualization? Is that a job that is only as a preparation of slideshows for internal conferences, and such? Well, there's nothing more wrong about that. See how.

Data visualization job = data interpreter

To create a representation of data, is to create an interpretation of it, too. The data in its raw form is always unreadable. Unfathomable. It's the vortex, the chaos - and from that chaos, data science intends to draw conclusions, and to that's on job, to visualize it, it's the second one, but surely that could be combined.

From the binary to the iconic language of humans

Secondly, to present a data in visual form, is to already make a point. Usually, there are slideshows, and there is a presentation. However, a good data presentation, data visualization will make the charts and the visual materials speak for themselves.

That's a rhetoric trick - to make point, emphasize with a good chart, the point or a decision just made, statement uttered, and so on. So, when it comes to data visualization job, that's a crucial thing there is to be done in the interaction between the data, the binary world, and the human one.

academy.vertabelo.com/blog/why-data-visualization-two-perspectives/