Best Data Analysis Software for Git

x
View:
Open Source Commercial

Compare the Top Data Analysis Software that integrates with Git as of November 2025

Sort By:
Git Data Analysis Clear Filters

This a list of Data Analysis software that integrates with Git. Use the filters on the left to add additional filters for products that have integrations with Git. View the products that work with Git in the table below.

What is Data Analysis Software for Git?

Data analysis software is software used to collect, process, and interpret large datasets to identify patterns, trends, and insights. It allows users to visualize data through interactive charts, graphs, and dashboards, making complex information more accessible. These tools often incorporate statistical, predictive, and machine learning features to support informed decision-making. Data analysis software is utilized across various industries, including finance, healthcare, marketing, and research, to enhance strategic planning and operational efficiency. By transforming raw data into actionable insights, it empowers organizations to make data-driven decisions. Compare and read user reviews of the best Data Analysis software for Git currently available using the table below. This list is updated regularly.

  • 1
    Saturn Cloud

    Saturn Cloud

    Saturn Cloud

    Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack. Quickly spin up environments to test new ideas, then easily deploy them into production. Scale fast—from proof-of-concept to production-ready applications. Customers include NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. Get started for free at: saturncloud.io
    Leader badge
    104 Ratings
    Starting Price: $0.005 per GB per hour
    View Software
  • 2
    Code Ocean

    Code Ocean

    Code Ocean

    The Code Ocean Computational Workbench speeds usability, coding and data tool integration, and DevOps and lifecycle tasks by closing technology gaps with a highly intuitive, ready-to-use user experience. Ready-to-use RStudio, Jupyter, Shiny, Terminal, and Git. Choice of popular languages. Access to any size of data and storage type. Configure and generate Docker environments. One-click access to AWS compute resources. Using the Code Ocean Computational Workbench app panel researchers share results by generating and publishing easy-to-use, point-n-click, web analysis apps to teams of scientists without any IT, coding, or using the command line. Create and deploy interactive analysis. Used in standard web browsers. Easy to share and collaborate. Reuseable, easy to manage. Offering an easy-to-use application and repository researchers can quickly organize, publish, and secure project-based Compute Capsules, data assets, and research results.
    View Software
  • Previous
  • You're on page 1
  • Next

Related Categories