5 Out-of-Box Visualization that will Change the way you Look at Data Forever

With the proliferation of the Internet in the last decade, there has been a massive expansion in the field of information and its displacement. Creating, capturing, copying, and consuming data globally can now be done in a matter of seconds. There are diverse data visualization techniques to choose from to manage such large amounts of data. This article focuses on the five most daunting and out-of-the-box data visualization techniques that have revolutionized this process. At the end of the article, you know the most exciting visual elements' features, advantages, and disadvantages and utilize them optimally for your data. Let us begin with understanding what data visualization is.

FIVE REVOLUTIONARY DATA VISUALISATION TECHNIQUES

?Choosing a personalized data visualization technique for your business is paramount. There are multiple techniques of visualization data such as maps, dashboards, tables, charts and graphs, plots, matrices, timetables, word clouds, etc. Each technique has pros and cons, and it must be chosen according to the metrics mentioned above. Here we describe five of the most inspiring ones that can uncover insights that traditional BI chart cannot:

Sankey Diagram

A classical Sankey diagram has directional arrows with a width proportional to the visualized data value. For instance, if the flow of the arrow is three times as wide, it stands for thrice the value of the data. Sankey diagrams are the futuristic way of depicting mundane flow charts, bar graphs, and pie charts.

- Areas of Application

Sankey diagrams are very beneficial for energy management, supply chain management, marketing analysis, process control, etc., and are thus usually used to represent one hybrid system.

-?Advantages

• Since they are always drawn between at least two processes, they convey two kinds of information in just a glance- flow values and fundamental distribution of the values in a whole system.
• Sankey diagrams can successfully draw the readers’ attention to the largest data value in the system since data can easily be highlighted where needed.
• Errors and other discrepancies are easy to spot.

- Disadvantages

• Difficult to read and understand without prior knowledge. Sankey diagrams are usually paired with tedious explanations.
• If not spaced correctly, visualized data can overlap and get cluttered.
• If the width of the directional arrows is similar, then inferring insights from a Sankey diagram is very difficult.

Sunburst Chart

?Sunburst charts, also known as ring charts and radial treemaps, are commonly used to visualize data that must be presented hierarchically. As shown in the diagram below, this hierarchy is depicted through rings of concentric circles wherein each ring stands for a level in the hierarchy. Individual circles may further be proportionally segmented to add more details. These segments and each level of a sunburst chart are usually differentiated using multiple colors.

-? Areas of Application

A sunburst chart is a great idea for visualising data such as demography, budgeting, website management, bookkeeping, etc. since it allows for adequate space for many segments of a whole to be represented on the same plane.

-??Advantages

• Since it is made in a radial shape, a sunburst chart utilizes space more effectively than standard data visualization techniques that are linear such as bar graphs, thereby making the insights more impactful.
• Even though it looks similar to a pie chart, a sunburst chart visualizes way more data sets and provides a coherent relationship analysis between them.?
• These charts are straightforward to learn to read, making the insights more impactful.

-??Disadvantages?

• The radial structure of the chart means an angular label, which is difficult for the human eye to read at a glance.?
• For geometrical reasons, the farther away a concentric circle is from the center, the deeper its slice becomes, which may not represent data values accurately.

Violin Plots

The characteristic feature of a violin plot is the distinctive shapes of the ‘density curves’ it has. Through such density curves that showcases both the distribution and probability density of the numeric data entered, this graph can depict numeric data for one or more data sets. Violin plots combine the best of box plots and density plots into one.

-??Areas of Application?

Violin plots are great for when the distribution of numeric data between multiple groups needs to be compared and presented in one chart. The components of the density curves (peaks, valleys and tails) may be compared to figure out the relationship they share.

-??Advantages

• Despite its similarity to a box plot, a violin plot shows the full estimated data distribution.?
• It can efficiently show summary statistics of the data set(s) input

-??Disadvantages

• Violin plots are relatively unknown to a large audience compared to the other data visualization techniques.?

Parallel Coordinates Plot

A parallel coordinates plot very efficiently uses 2-dimensional space to represent high-dimensional data. As picturized in the diagram below, this chart constitutes various vertical axes placed equidistantly parallel to each other. A data entry (a single line) will pass through all these vertical axes, meeting them at a certain point according to their value. Different colors may be used to depict different data entries.

-??Areas of Application

A parallel coordinates plot is the best way to visualize data that infers the relationship between multiple data sets and variables, for instance, the stock market.

-??Advantages?

• Even though it occupies a 2-D space, it visualizes data in a high-dimensional manner that allows readers to perceive trends.?
• The placement of axes is flexible.?

?-??Disadvantages?

• There may be many overlapping lines on a particular point for typical data values that make the chart look congested and challenging to read.?

Race Bar Chart

?A bar race chart represents statistical data generally grouped in a graph sheet and depicts the change in trends over time. It is also beneficial for comparative analysis between different actors on the same data metric. What is most interesting about this particular type of data visualization is that a race bar chart may be animated to engage the viewers more.

-??Areas of Application

Race bar charts can also be recognized reasonably well since they show change over time between two comparative categories, especially when competing in nature. Recording the market survey responses, change in population size during the census can be shown on a race bar chart as quickly as the competition between political candidates, football teams, etc. These are a few instances where bar graphs are handy.

-??Advantages

• Race bar graphs can very quickly concisely summarise a lot of data.?
• One of the best ways to infer upcoming trends in the market.?
• Very easily understood by most people, so race bar graphs are very accessible.?
• Provides impactful comparative insights between discrete categories through animated aspects of the graph.??

?- Disadvantages?

• Manipulations to tweak the results in a particular shade are pretty easy.?
• Bar graphs simply depict values without explanations, effects, reasons, analysis, etc.?
• Double bar graphs make it challenging to find percentages in your data.

Today's visualization tools have thoroughly considered all of these factors to develop a product that meets all your advanced data visualization needs, e.g., a Tableau-supported toolkit that is as easy as plug-and-play. The templates are ready to use, and all you have to do is input the data you wish to visualize. The toolkit would have a diverse collection of impactful advanced data visualization techniques, making this essential process 100% faster, more efficient, and affordable. Invest in this revolutionary toolkit right now!