I have got more and more interested in working with Visual Analytics. When asking my ex-supervisor for good material on the topic, he did suggest this book, "Visual Analytics for Data Scientists" by Andrenko et al. 1.

I have started to read it, and it seems to be a thorough introduction to the field. Here they do not present the newest research but, as they say, go through  "... the main principles and describe the techniques and approaches that are ready to be put in practice ...". They state that today professionals have started to use visualisation in the analysing process and not only when presenting the findings. And many of them that publish visualisations do have a "quiet little idea of how to choose appropiate visualisation techniques and design correct and effective visualisation of the data they deal with ..." and how to use it. This knowledge gap is what this book is trying to change.

They start with a good example that goes through all the analysing steps. And they also do the iterations that are a vital part of visual analytics. Then they go through how to analyse the data before describing the distribution and finding patterns.

So far, it has been quite interesting, and I have a somewhat better understanding of the material. But it has not reviled much new material compared to what we learned in the visualisation group and could be a book in the master curriculum. My first impression so far is that it could be of interest to everyone that does a sort of analysis work, not only for a data scientist.

As a definition, they cite the following, "the science of analytical reasoning facilitated [made easier] by interactive visual interfaces" 2.
  1. Andrienko, N., Andrienko, G., Fuchs, G., Slingsby, A., Turkay, C., & Wrobel, S. (2020). Visual analytics for data scientists. Springer, www.springer.com/gp/book/9783030561451.

  2. Cook, K., & Thomas, J. (2005, May 9). Illuminating the path: The research and development agenda for visual analytics. OSTI.GOV. https://www.osti.gov/biblio/912515