Why is Data Visualization Important?
Picture the scene, I’m browsing the web looking for statistics for a specific topic and come across an important article on the question I’ve queried.
This article depicts some of its information and answers in various patterns and shapes of graphs and metrics.
These graphs are providing the answer that I’m seeking in a visual format.
Finding this helpful, I try to further understand the data depicted, while wondering to myself, why is data visualization important?
Data visualization is important because of how the brain processes information. Using visual representations, such as charts or graphs, allows the understanding of complex data.
Data visualization is stylised, scalable and conveys significant meaning more effectively than other data methods.
Data visualization enables decision making bodies to make more informed decisions. Because of this, many high level organisations use data visualization to highlight important statistics.
As a result, better decisions are made as there is more understanding of key metrics.
A similar scenario might occur when looking at an info graph. An experience I’ve also encountered while browsing the web.
If you have ever observed the patterns and statistics of an infographic you’ll understand how visual representation of data is much easier to understand than its spreadsheet equivalent.
The same data depicted in this spreadsheet would have difficulty conveying the same meaning.
Data visualization can also:
- Identify areas that need attention or improvement.
- Clarify which factors influence customer behavior.
- Help you understand which products to place where.
- Predict sales volumes.
However, this is only briefly highlighting how data visualization is important.
Let’s examine other fundamental aspects of data visualization.
What is Data Visualization?
You’ve probably heard of data visualization in relation to the current state of web development.
Some consider it a buzz word, others are unsure of how to define it. So, what actually is data visualization?
Well, the general term data visualization describes any effort that helps describe the significance of data in a visual format. This can be charts, graphs, statistics, tables and geometric shapes.
Data visualization helps to inform the user of patterns, comparisons and scales that may not be as obvious from just reading the data.
Having the data presented visually increase the capabilities of user to understand it (“a picture says a thousand words!“).
The user processes this information further to create his/her own decisions based on the data.
Essentially, data visualization is the presentation of data in a pictorial or graphical format.
It refers to various techniques used to communicate insights from data through a visual representation.
Its primary purpose is to breakdown large datasets into visual graphics that enable an easier understanding of the complexity.
When presented in a visual format, the key metrics of the data being depicted become more obvious. Those viewing the data can identify important patterns much faster.
This provides the data’s inherit value to those that need to make decisions from it.
The ability to recognise this pattern also enables decision makers to make informed predictions of where metrics might rise or fall.
Using the latest in web technologies, data visualization can be made interactive.
With interactive data visualization, there is more engagement with the user.
The user can dive deeper into charts and graphs for more detail, interactively changing what data they see and how it’s processed.
Interactions like this allow the user to manipulate the data under different criteria e.g between two dates.
This gives a stronger sense of how datasets differ from each other. The user is able to contrast and compare with their own interactions.
Data Visualization Examples
While researching this topic, it wasn’t immediately obvious of where to look at for examples of good data visualization.
I wanted to find examples that weren’t just standard static info-graphs. The most useful type of data visualization is when it’s interactive.
I wanted to find more creative examples that go outside the standard charts and graphs.
So, I’ve curated a few examples that I thought show meaningful user interaction with interesting data.
While from Black Friday 2017, I thought this one was particularly well styled.
The hovering effect is effective for showing an initial weighted metric and if you click onto an individual item a detailed window gives further information on the brands social statistics for that time period.
This website highlights different modes of commuting. I think the design is nice clean and simple.
There isn’t much user interaction here, however, clicking a mode of transport switches the current overview of the map.
I think this is effective for focusing on an individual mode of commuting.
This is a very creative data implementation of various objects in space. I really like the originality of this and is a great demonstration of how data can be presented outside ordinary charts and graphs.
While these data snippets of space objects aren’t particularly valuable, its a great indicator of how creative data visualization can draw more attention.
This website is a little less focused on depicting conventional data visualization in favour of user map interactions. A user can add their own initiatives to any location the map.
I personally liked the muted blue colours for the map and I imagine that this could be expanded to show metrics of initiatives created.
An impressive piece by the Washington Post demonstrates all the potential solar eclipses over a lifetime.
This is interactive, highlights its information effectively and has interesting data to show.
For me, this is the pinnacle of a data visualization example as its meaningful but not overly stylised for the sake of it.
Apart from Brand Love Score, there isn’t a huge amount of business value in these examples. But this is a result of the data used.
In a scenario where valuable data is used creatively, I think it can draw more attention than ordinary data visualization implementations.
However, getting too creative may inhibit a users ability to compare significant information which might defeat the purpose of valuable visualizations.
In order to create creative and valuable data visualization a suitable balance is required .
What Makes for Great Data Visualization?
Having data visualization implemented on a website or web application is all well and good.
But how is it optimised to provide as much value as possible?
What makes for great data visualization?
Well, from what I’ve seen, there are two pieces of additional functionality that separate a standard piece of data visualization to something with significantly more value.
User Input
Perhaps, one of the most important decisions when creating a data visualization page is whether or not the user can to interact with it, or alter it?
Take an example of this energy recycling dashboard.
It is a real-time data fed dashboard where the user can highlight on the scatter nodes for further information.
Its informative and constantly updated while still giving interactivity to the user. Its value is evident from combining those three aspects:
- Real-time
- Interactivity
- Relevant Data
Here are some user input concepts that you might consider:
- Can the user filter data by certain criteria (e.g category)?
- Can the user can highlight points of interest for further details?
- Is the dashboard in real-time?
- Are the metrics displayed likely to be understood to the user?
These are all important considerations when trying to make your data valuable.
With all this mind, its important to remember that while not all data are inherently useful, the ability to traverse through the information in a specific dataset is key to making vital business decisions.
Realtime data
Data can be static or in realtime. Static data represent datasets that do not change and are fixed.
Whereas real-time data are ever changing and are constantly receiving live updates.
As a result of these live updates the data will dynamically change. This is perhaps the most valuable aspect of data visualization for a business or product.
Multiple studies have been conducted regarding how real-time data assist major firms to come to a final verdict regarding important decisions.
Real time data visualization enables decision makers or viewers to have the most up to date information either for observation purposes or to make time-sensitive decisions based on that information.
When combined with user input, real-time data can become incredibly beneficial for organisations to analyse the latest information, as well as for users to contribute their input.
This input is in turn reflected instantaneously through the visual medium used to display that input.
Organisations feel more confident in their decisions when they know they are fact-driven, as opposed to when they are relying on their own instinct or intuition.
Importance of data visualization in modern business
What drives the value of data visualization is how a modern business can use it.
Many modern business have adapted data visualization as the best way to depict some of their most important metrics such as sales, conversions and user retention rate.
This is perhaps most apparent, when taking into consideration that data visualization can provide a parity of understanding amongst many different types of employees.
This means that even those without much training in big data can propose their own solution to a problem that being highlighted in a companies metrics.
This might not be the case if the data was not understand properly.
There is a type of visual regression when consistently looking at excel sheets as no visual feedback means that there is no sense of the scale of comparison.
As hinted at earlier, anyone using data visualization can make a more informed decision from understanding that data. For a business, data-led decisions can have huge implications on profits and growth.
Vital decisions being made from looking at visual data, spotting patterns and predicting where it will go next. Therefore, it is important to make interpretation of the data as user-friendly as possible.
This really could be any kind of metric including sales, stock, user retention etc. However, used creatively, data visualization can depict overall growth of business, peaks and troughs of the financial year and much more.
Data visualization can also be used to highlight important statistics that would otherwise be difficult to explain for anyone that is not closely involved of the inner working of a business or product.
While the benefits for large business are evident, something that is perhaps overlooked is how beneficial data visualization can be for smaller businesses. Providing the ability to make informed data based decisions at early stage can be key to maximising growth.
Having realtime feedback of where your business stands in it early stages provides incredible value for those who are looking for predictions, patterns, comparisons etc.
Data Visualization Techniques
The techniques used for depicting data visualization can vary greatly.
When taking into account that any visual format displaying data can be considered a form of data visualization.
With this in mind, there are a few considerations that should be taken into account when thinking of using a data visualization technique.
- What data am I trying to highlight/indicate?
- Is the data static or in real-time?
- Will the user have input?
- Will the dataset be interactive?
Once you know what your dataset is, it is equally as important to know how you want to depict it. This defines what technique will be used.
I wanted to highlight the most common techniques so here are some basic chart formats that most simple datasets can use:
Please note that these are the most basic forms of data visualization and their complexity can increase according to the shape of your data.
Think about how you would apply the same metrics to your business or product.
Overall, data visualization can be seen all the over the web. It can be displayed in many different ways. Some use cases may present rudimentary charts, whereas others can appear to be styled in creative ways.
Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments.
I hope this information was useful and that the benefits or using data visualization are apparent. In the next topic I want to focus in on real-time data visualization.
In the meantime, if you are interested in adding data visualization visualization to your business or product you can get in touch here.