Data visualization is being hailed as the next great revolution in data analytics. But besides the fancy name and the slick-looking graphs produced by the technology, how can this new addition improve your already-efficient organization?

If harnessed correctly, data visualization has the power to improve your company’s productivity, client relationships and profitability all at once.

But how?

Let’s start by dissecting the core strengths and effects of data visualization. Assuming all other factors (including staff, data sources, etc.) are equal, data visualization has the potential to add the following:

  • Interpretability. The hallmark improvement offered by data visualization is its interpretability. In other words, a set of data illustrated in a visual chart is much easier to understand than a complex spreadsheet containing the same information in a numerical format. This makes the process of data analysis more accessible and faster, to a wider range of users.
  • Speed. Data visualizations themselves aren’t exactly new; we’ve been using charts and graphs for hundreds of years. The big difference here is leveraging platforms that can quickly and precisely adjust those visualizations to account for new variables, different conditions, and other customizations requested by a user. The production element has hastened significantly.
  • Utility. We should also consider the near-universal utility of data visualization, since it can be used in almost anything, from studying demographic trends to analyzing employee productivity. This means you can harness the power of data visualization for almost any department or application, provided you have information to study.

Key effects to harness

So, how can you apply these advantages in a way that improves your entire organization?

  • Analytics approachability for employees. Because data visualization is pretty intuitive, and because it’s available for countless applications and departments, it’s possible for employees of almost any department to become data analysts in their own right. More data analysts on staff means more analytic power within your organization, and the potential to optimize almost any role for greater productivity and profitability.
  • Big data reduction. Until recently, companies have pushed to collect as much data as possible; after all, more data is always better, right? The answer isn’t so straightforward. Collecting more data leads to more vulnerability and storage costs, but also more complexity, and more difficulty drawing accurate conclusions. The imminent arrival of the General Data Protection Regulation (GDPR) introduces new privacy considerations. Data visualization takes big data and condenses it to a more intuitive, accessible form, allowing companies to make use of big data while eliminating one of the risks. Hypothetically, that means releasing a core limitation in data advancement within an organization.
  • Easing client communication. Effectively demonstrating your results and efforts to clients is one of the toughest challenges for any B2B company. Data visualization eases this problem, giving you an intuitive tool you can use to make almost any concept easier to understand. Visual tools make conversations go smoother and minimize miscommunications.

Future trends to watch

These benefits are just the start; in the future, data visualization will likely improve even further, especially along these dimensions:

  • Higher-dimensional data. You can chart two variables against each other with a simple line graph with an X- and Y-axis, with each axis representing a variable. You can chart a third or fourth variable by adding more lines or bars to your chart, or by utilizing some kind of Z-axis. But what if you want to visualize 10 variables or more? High-dimensional data visualization is the answer, but it’s a technology still in its infancy. It’s hard to make high-dimensional data as intuitive as low-dimensional data, but researchers are striving to find an efficient way to make this happen.
  • VR and AR. The advent of virtual reality (VR) and augmented reality (AR) can also change our relationship with data visualizations. Rather than interacting with a static projection on a computer screen, users could feasibly reach out, touch, and interact with data in a 3D environment.
  • Machine learning and AI. Already, machine learning and artificial intelligence (AI) algorithms are making data analytics platforms more intuitive and faster for users. When they become more efficient, they may be able to not only generate custom visualizations, but also recommend what type of visualizations to render based on available data. In effect, they could serve as analysts in and of themselves.

The organizations most willing and able to make good use of data visualization technology are the ones likely to remain competitive for the foreseeable future. If used correctly, this can be more than a superfluous add-on to your existing platforms; it can help you transform your department, or your entire organization for the better.

(This post originally appeared on the ISACA blog, which can be viewed here).

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