7 Data Visualization Types You Should be Using More
The advent of advanced business intelligence systems and arrival of various visualization software solutions has virtually transformed the business intelligence landscape today. Laced with an array of rich open source B.I. tools and B.I. applications, top analytics companies in India and abroad are pushing the arena of analytics and business intelligence to an all new level every single day. Studies suggest that business intelligence tools can be more helpful and agile in arriving at enhanced insights, if they’re used in conjunction with B.I. dashboard tools leveraging some specific data visualization types. Let’s have a look upon them.
Slopegraph is a form of chart that compares changes usually over time for a list of variables that are located on an interval scale. Being used in creating dashboard reports by a number of analytics and business intelligence companies, it helps in the creation and evaluation of advanced designs that organize complex information in a hierarchical manner.
If a dashboard report needs to display complicated multivariate datasets, parallel coordinates may be used for visualizing and analyzing high-dimensional geometry. In order to show a set of points in an n-dimensional space, a backdrop is drawn in parallel coordinates. It consists of various parallel lines, typically vertical and equally spaced. A point in n-dimensional space is represented as a polyline with vertices on the parallel axes.
Alluvial diagrams are used in business intelligence systems and visualization software tools to diagrammatically represent continuous changes having taken place within a network structure over a period of time. Both the visual appearance and the emphasis of alluvial diagrams on flow resemble with alluvial fans that are naturally formed by the soil deposited from streaming water, hence the name.
If the dataset is a complex collection of hierarchical data, the sunburst chart comes in handy for displaying it in a lucid and easy to understand manner. Within the chart, each level of the data hierarchy is represented by one ring or circle with the innermost circle as the top of the hierarchy, usually in open source B.I. tools and B.I. applications. A sunburst chart without any hierarchical data looks almost similar to a doughnut chart.
The chart type known as Circle Packing is a sort of Treemap chart, though it uses circles instead of rectangles. Area inside each circle represents a level in the data hierarchy, each branch of the tree is represented as a circle and its sub-branches are visually represented as circles inside of it. The area of each circle can also be used to represent an additional arbitrary value, such as quantity or file size. Growing number of analytics and business intelligence enterprises across the globe are adopting this chart type in their presentations now.
At times, one has to visually represent a huge list of results that would become crowded if displayed vertically. In such conditions, horizontal bar charts prove to be more efficient and useful than vertical bar charts. Integrating this technique with the ability to change the chart height, exceptionally long lists of datasets can also be represented visually in a simple and straightforward manner. Often, it is used in data transformation tools and open source reporting tools to prepare dashboard reports.
A stream graph is almost similar to a Stacked Area Graph, though the difference is that instead of plotting values against a fixed, straight axis, it has values displaced around a varying central baseline. It is especially used to represent the changes in data over time of different categories through the use of flowing, organic shapes that somewhat resemble a river-like stream. This makes stream graphs both visually beautiful and statistically meaningful at the same time.
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