understanding of the content of the data and the relationships between the variables and observationswe explore this in the next section step exploratory data analysis during exploratory data analysis you take deep dive into the data (see figure information becomes much easier to grasp when shown in picturetherefore you mainly use graphical techniques to gain an understanding of your data and the interactions between variables this phase is about exploring dataso keeping your mind open and your eyes peeled is essential during the exploratory data analysis phase the goal isn' to cleanse the databut it' common that you'll still discover anomalies you missed beforeforcing you to take step back and fix them data science process setting the research goal retrieving data data preparation simple graphs combined graphs data exploration data modeling link and brush nongraphical techniques presentation and automation figure step data exploration the visualization techniques you use in this phase range from simple line graphs or histogramsas shown in figure to more complex diagrams such as sankey and network graphs sometimes it' useful to compose composite graph from simple graphs to get even more insight into the data other times the graphs can be animated or made interactive to make it easier andlet' admit itway more fun an example of an interactive sankey diagram can be found at mike/sankeymike bostock has interactive examples of almost any type of graph it' worth spending time on his websitethough most of his examples are more useful for data presentation than data exploration