These Questions Will Help You Choose the Right Data Visualization Tool for Your Business

Data visualizations have become a key part of how organizations understand the mountains of data they produce daily. As a major component of business intelligence (BI) platforms, or on its own, a good data visualization tool can greatly amplify the insights you gain from your data – and help with comprehension and alignment across your teams.

After all, nearly 65% of people consider themselves visual learners, and we can process massive amounts of data with our eyes in seconds. Moreover, companies that use visual data discovery and visualization tools are almost 30% more likely to identify relevant, game-changing information than those that don’t.

However, not every data visualization method is as useful as the next in any given situation, and different organizations have unique needs that make for specific requirements. Choosing the right set of tools for your company is an important consideration, and before you decide, there are several aspects to consider.

Here are some of the big questions you need to answer before you can make sure you’ve chosen the right data visualization solution for your company.

1. What Kinds of Queries Does Your Organization Need Addressed?

Although all organizations produce data, the information they generate is unique and offers different insights based on what questions are being asked. While it’s true that all professional-grade data visualization tools will give you a clearer picture of your operations, there may be some that are more optimized to your specific industry or market segment.

However, the first step is to understand what you want to learn from your data visualizations. Are you looking for quick reporting that measures KPIs and displays them easily? Or, are you looking for drill-down analysis that comes with more customizability and the ability to create deeper visualizations? Is your organization more focused on historical data, or are you looking for predictive analysis?

These questions will frame the type of visualizations you need and the tools that can provide them for you.

2. How Tech-Savvy Are Your Team Members?

Data visualization and BI tools today run the gamut from easy, out-of-the-box solutions to fully customizable suites that are built for rugged analytics and more focused approaches. However, these two ends are meant for significantly different organizations with vastly different levels of technological capital and skill.

Smaller organizations may not have the available budget for an analyst-based data visualization tool that requires dedicated operators and heavy coding. On the other hand, some companies may have specific needs that require a more in-depth tool.

Understanding your team’s skill level is also crucial, as complex tools may lose some of their value if they aren’t properly configured or used. Before choosing a data visualization tool, it’s worth auditing your organization’s technological capital to understand both your constraints and your needs.

3. How Much Data Do You Use, and How Is it Stored and Formatted?

This is another important consideration to have. While almost every company collects data from hundreds of touchpoints across their operations, they don’t all use it or store it the same way.

For some companies, data can be used largely historically—that is, without any demand for minimized latency. This means that data can be parsed, prepared, and optimized for visualizations long before they reach end-users. On the other hand, some organizations require large amounts of data processed and visualized on the fly, often in the form of KPIs, sales metrics and other transactional information.

This largely affects how you keep data and store it, whether in a data warehouse, lake, or other structure. More importantly, it also changes the range of analytics and visualizations you can apply and the purpose of your visualizations. If your organization uses reports and dashboards extensively, you may require visualization tools that combine both current and historic data. On the other hand, if you’re mostly performing analyses on past transactions, you may not need auto-refreshed dashboards and visualizations.

4. What Kinds of Visualizations Do You Need?

The Last important factor to consider is the type of visualizations that best fit your company’s data profile and needs.

Again, you’re the specifics of the organization will largely define the type of visualizations work best, even if it’s more than one or two. However, there are some major data visualization types that are most commonly used:

  • Hierarchical visualizations such as tree diagrams and ring charts are great for studying data clusters that span from a single point and can show relationships in data more clearly.
  • Geospatial visualizations show your data along geographical lines and can be excellent to understand sales trends, logistics, and supply chain bottlenecks.
  • Multidimensional visualizations give you different ways to interpret and compare data sets to find new correlations.
  • Network visualizations are excellent at finding the ways datasets connect to each other, and how they interact.

These are just some of the most popular types, but your organization may use one or more of them. Based on what you need, it may be worth exploring different tools.

Visualize Your Business’s Success

The right visualization tool is not a single answer, but rather the result of a better understanding of your company’s data needs. By taking the time to consider the right data visualization tools you need to match both your existing capital and your requirements, you can ensure that you’re getting the most out of every visualization you create.

Adwaith
Meet Adwaith, a tech-savvy editor who's all about gadgets and gizmos. With a degree in Computer Engineering and a passion for all things tech, he's been guiding readers through the world of hardware for 10 years. Known for his clear, insightful reviews, Adwaith is the trusted voice behind TechLog360. Off-duty, he loves building PCs for charity.

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