Best Statistical Analysis Software for GitHub

Find and compare the best Statistical Analysis software for GitHub in 2026

Use the comparison tool below to compare the top Statistical Analysis software for GitHub on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Domo Reviews
    Top Pick
    Domo has become a part of Progress Software, integrating its AI and data platform into Progress' suite of offerings. This cloud-native AI data readiness platform not only enhances but also expands Progress' existing data solutions, fostering significant synergies that facilitate the development of innovative, secure, and scalable AI data readiness solutions on a global scale. These combined strengths will assist clients in transforming fragmented enterprise data and insights into governed, AI-ready intelligence, thus elevating the security, governance, and cost-effectiveness of AI-driven projects. Positioned as the agentic platform for the intelligent enterprise, Domo empowers organizations to connect, govern, activate, and disseminate both data and AI effectively. Collaborating with cloud data platforms such as Snowflake, BigQuery, and Databricks, Domo enables the conversion of governed data into various AI agents, applications, workflows, dashboards, and analytics. Additionally, its robust data foundation, activation, and distribution layers empower teams to create and implement intelligence precisely where their work occurs, all while ensuring governance, security, and access controls are firmly in place across both data and AI initiatives. This comprehensive approach not only streamlines operations but also enhances the overall effectiveness of data-driven decision-making within organizations.
  • 2
    SAS Viya Reviews
    SAS Viya is an advanced cloud-native data and AI platform designed to help organizations manage data, develop AI models, and operationalize analytics from one unified environment. The platform combines data access, machine learning, analytics, governance, and decision deployment into a scalable system built for enterprise use. SAS Viya enables businesses to connect to data across multiple sources while maintaining transparency, lineage, governance, and auditability throughout the AI lifecycle. Organizations can use the platform to accelerate model development, streamline workflows, and deploy trusted AI solutions faster and more efficiently. The platform includes built-in governance features that support fairness, explainability, compliance, and responsible AI practices across teams and business processes. SAS Viya also supports secure AI agent integration through the SAS Viya MCP Server, allowing AI-driven tools and copilots to interact with enterprise workflows responsibly. Businesses can deploy the platform in cloud, hybrid, or on-premises environments based on operational and security requirements. SAS Viya is used across industries for applications such as fraud detection, healthcare analytics, forecasting, customer intelligence, and AI model operationalization. The platform is designed to improve productivity by simplifying complex AI workflows and enabling collaboration between data scientists, analysts, and business users. Backed by decades of analytics expertise, SAS Viya helps organizations transform raw data into transparent and actionable business decisions at scale.
  • 3
    Bytesafe Reviews

    Bytesafe

    Bitfront

    €1100 per month
    Enhance your security framework for open source by implementing automated best practices, creating an integrated workflow that benefits both security and development teams. This cloud-native security solution minimizes risk and safeguards revenue while allowing developers to maintain their pace. The dependency firewall effectively isolates harmful open source elements before they can affect developers and infrastructure, thus preserving data integrity, company assets, and brand reputation. Our comprehensive policy engine examines various threat indicators, including recognized vulnerabilities, licensing details, and rules defined by the customer. Gaining visibility into the open-source components utilized in applications is essential for mitigating potential vulnerabilities. The Software Composition Analysis (SCA) and dashboard reporting provide stakeholders with a complete perspective and prompt updates regarding the existing environment. Additionally, you can detect the introduction of new open-source licenses within the codebase and automatically monitor compliance issues involving licenses, effectively managing any problematic or unlicensed packages. By adopting these measures, organizations can significantly improve their ability to respond to security challenges in real time.
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