via TechTarget

Numerous tools are available for data science applications. Read about 15, including their features, capabilities and uses, to see if they fit your analytics needs.

The increasing volume and complexity of enterprise data, and its central role in decision-making and strategic planning, are driving organizations to invest in the people, processes and technologies they need to make sense of and gain insights from their data assets. That includes a variety of tools commonly used in data science applications.

A powerful data science application is just half of the equation. Having the right high-performance system to process all that data, custom built for your workflow and location, is what makes it a complete data science solution. Explore NextComputing’s best-in-class systems for analysis.