• If you’re choosing a platform for your team, it needs to be something that matches their skillset.
• How easy a tool is to learn is also key. You don’t want teams spending months just to gain proficiency with a data visualization tool.
• You need to find a platform that is best suited for the amount of data you have.
• You need to weigh up the price of the tool against your budget.
• If you teach yourself data visualization in order to be a more attractive job candidate, pick the software which is asked for most commonly by the companies you’re applying to.

• Tableau is the biggest data visualization tool out there. It has a very intuitive design and is very easy to learn for beginners.
• Chartio is an excellent choice for businesses seeking a more seamless way to share data across multiple teams. Popular with Product Managers, this platform lets you see real-time user behavior and feature performance.
• Plotly’s Dash platform is designed for data science teams who want to build analytic apps without relying on developers.
• MicroStrategy helps when you think big. Featuring a drag and drop interface, teams can easily build data discovery dossiers.

Python, R, and SAS can create awesome visualizations and can be a great addition to any platform.

With programming languages, you can also make some very specific visualizations. On the other hand, the more complex the visualization, the more complex the programming! It’s both a time and effort-heavy endeavor, and could be overkill if you’re only working with a small/medium amount of data.