Their various products-from Dash to Chart Studio-are open-source and highly customizable.

Pros: Highly customizable visuals, with many different tools available under the Plotly banner.Ĭomputing start-up Plotly has produced several data visualization libraries, mostly built using Python.

Commonly used by: Data analysts and data scientists.

Availability: Open-source software with enterprise versions available.

This includes those often used for data analytics, as well as some that are better suited to non-technical users.

Many of these are designed to streamline-and even automate-the data visualization process.įrom free, open-source software to commercial solutions, in this post, we’ll explore our top seven data visualization tools. And while creating visualizations can be time-consuming, there’s a booming demand for data viz tools. This is also useful for creating dashboards and reports that non-data-savvy decision-makers can understand. To make sense of all this information, we often represent it visually to aid our natural pattern-spotting abilities. Working with big data means grappling with thousands, if not millions, of discrete data points. But what visualization tools can we use to help? Let’s take a look. Interpreting datasets often involves representing them visually.

Technology tools for data analysis