There are different graph layout methods such as Force-based Layout, Tree Layout, Spectral Layout, Arc Diagrams, Circular Layout, Orthogonal Layout Methods, Dominance Drawing, Sugiyama-style Drawing. The unique arrangement of these vertices and edges provides understandability of databases. Graphs are a pictorial representation of the vertices and edges of graph’s database. Graph visualization constructs a 2D or 3D representation of graphs according to user’s requirements. Graph visualization has a wide range of applications such as organization charts, data flow diagrams, state-transition diagrams, entity-relationship diagrams, and networks. Data is illustrated (“visualized”) using various tools (which will be discussed soon) to draw a graph. In relational data visualization, data is automated for analysis such as extracting a graph from data and clustering. Here I will brief the graph techniques and different layouts of data visualization using Gephi using an example.ĭata Visualization is the process of representing information visually which provides a clear, effective and interactive understanding of abstract business or scientific data. Having experience or qualification in graphical design (or similar disciplines) is also advantageous in complementing data analytical skills – at least in my own experience. The results of much of our effort in data analysis end up before the eyes of our stakeholders or clients. Effective visualization is essential in gaining attention and in providing insightful and readily digestible representations, and an appreciation of the techniques and tools available to achieve this is most helpful.
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