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Visual Data Analysis - 29 Sep 17

Visual Data Analysis - 29 Sep 17

Visual Data Analysis Best Practices

Data Visualisation is defined as any method where images, diagrams, infographics or animations are used to convey a message. It’s an effective means of transforming a difficult subject into an easily understandable and memorable message.

The basic structure

In the connected age there is no lack of information or data. One has to remain selective about what should be included/excluded, especially when it comes to a visual analysis.

To ensure a visual analysis will be successful when presented, it needs to stick to the question you are trying to answer with it. Within 30 seconds, the audience needs to understand the data visualisation and how it will be used to present the facts.

Selecting a chart

There are various charts generally used for different purposes.

A trend chart is the best choice for highlighting trends over a specific timeframe, while comparison and ranking charts are both useful for analysing data. Both could be used for something as simple as comparing prices between competitors, or to look at where an entire company ranks between its main competitors.

Share of voice or product media impact vs competitors.

A bar chart works well for comparisons, because it’s an easy and accessible way for everyone in a company to understand the different values and how they compare.  

A correlation chart, or scatter diagram, is perfect for analysing the correlation between two variable, or if you suspect that one variable is having a large impact on another.

It’s worth investigating the different types of charts available to see if there might be a better way of presenting the data to your audience. Ideally, you want a chart that will not only convey the most important facts, but also in a way that is eloquent, attention grabbing and easy to understand.

Detail can be lost, so ensure the storytelling is not lost through incorrectly illustrating the figures. Don’t simply show your data - use it to communicate with decision makers meaningfully

Effective views

Once the basic outline of the analysis has been selected and the chart it will be presented on has been selected, one has to ensure that it will be as effective as possible when viewed.

As a starting point, select the most important data. This is the data that needs to be highlighted in the final visualisation. The emphasis you place on this data stems from the basic structure, which is the main question you’re trying to answer.

It’s also worth investing in the clearness or legibility of the visualisation. You want it to be easy to understand and easy to engage with, without losing any of its power.

Avoid overloading a visual analysis with data and limit the amount of elements used. The use of these elements will undoubtedly add to the effectiveness of a visualisation, but too much will end up distracting the audience. As stated earlier, only emphasize the most important data.

The most effective way to communicate a message is to understand the audience you are catering to and whether this particular data visualisation caters to their needs.

Bare in mind that graphs will be used for presentations, so brandling and simplicity are key components for success in data visualisations.

Explore limitless visual analytics - be creative. Build and perform ad hoc analyses and share your work with anyone and make an impact on your business. From global enterprises to early-stage startups and small businesses, make use of our amazing tools.

Happy graphing!


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