What Are the Strengths and Weaknesses of Data Visualization?
Data analysis is more important than ever before, with sophisticated tools that allow businesses of all sizes to gather data on their customers and operations, and rising competitive pressure from other companies in the same industry. Increasingly, companies are turning to data visualizations to help them perform their analytic responsibilities in an easier, more intuitive, and more approachable way.
Data visualization, in case you aren’t familiar, is the practice of simplifying or improving your data with the help of visual aids, like charts, graphs, or other illustrated depictions. These visualizations are often able to be manipulated, so you can see immediately how your big-picture assessments change in response to new bits of data or changed variables.
How effective is this approach, and are there any downsides?
Implementing Data Visualization
First, let’s talk about the implementation of data visualization within organizations. There are many software tools available that promote their ability to produce data visuals within their interface. In fact, you’d be hard-pressed to find any modern analytics tool that didn’t offer at least some visualization capacity.
But for most businesses, especially mid- to large-sized ones, these tools aren’t enough. They need the help of a management consulting firm, as well as the help of a team of developers, to design and create better data visualization tools (and better data analytics processes) that specifically fit their business needs. Not all businesses will benefit from the same collection of data analytics or visualization features.
The Advantages of Data Visualization
These are some of the greatest advantages of data visualization, and are why it’s become so popular:
. Instinctive Analysis.
If you were to calculate all the data on your own, it would take a long time to reach a conclusion. But when you’re looking at a graph or a chart, you can almost instinctively detect what’s going on. For example, does it look like there’s a clear trend, or are the data more chaotic? Humans are exceptionally good at processing visual information, so it makes sense that data visuals would appeal to us.
. Variable Analysis.
Visuals also make it easy to see how different sets of data might influence the results. We can change a variable or expand the range of time we’re looking at, and easily compare the two graphs that result. This is much faster than trying to compare data line by line, or running a new manual analysis every time you want to consider a new change.
. Trend Analysis.
Data visualization is also ideal for long-term trend analysis. It’s easy to get caught up in small jumps or plunges, but how are the numbers changing overall, and over the long term? With the help of a sufficiently sized graph or chart, you can easily spot the emergence of patterns.
. Real-Time Data Analysis.
Real-time data analysis is becoming more popular, because of its ability to help people make faster and more immediate decisions. But it’s hard to conduct real-time analytics without a visual component; otherwise, you’ll need to spend more time analyzing the data on your own. A compelling visual can make it clear how your numbers are changing in real time.
. Easy communication and sharing.
Data visuals are also extremely helpful for communicating data to people who might have difficulty understanding your deeper methodologies, or with people who only have a limited time to take in your conclusions. Even people with limited data analytics experience can notice a growth trend when presented with the right kind of visual aid.
The Disadvantages of Data Visualization
However, there are some weaknesses of data visualization as well:
. Lack Of Detail.
You may be able to get an idea of the big picture of your data set with a strong visualization, but you won’t have immediate access to the details. For example, are there any outliers that deviate from the general trend that are worth exploring?
. Inaccurate Conclusions.
Visuals tend to increase our confidence, so it’s possible for us to draw inaccurate conclusions from them. For example, with confirmation bias in play, we may believe that a visual reinforces or solidifies our foregone conclusions.
. Poor Design Or Planning.
Remember, data visualization technology is built by human hands. If it’s designed in an unsophisticated way, or if there’s a flaw in how it operates, it might lead to inaccurate presentations.
Much of your success with data visualization depends on how you implement it, and how you use it on a regular basis. If you work with a management consulting firm to better understand your data analytics needs and build a tool that directly addresses those needs, you’ll be in a much better position to succeed. Additionally, the more you acknowledge and work around these strengths and weaknesses, the easier it will be to emphasize them and compensate for them, respectively.