Predictive Analytics

Predictive Analytics

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  • Plan for releases

    Reduce development risks and costs while supporting hybrid application development methodologies. Plan for quality and test management across complex application portfolios.

  • Build quality codes

    Actively optimize code builds for efficient and accurate application development of integrated solutions.

  • Scale continuous testing

    Accelerate application quality for continuous assessment that works at enterprise scale; to reduce defect rates with test efficiencies and root cause analysis.

Plan-Develop-Test-Operate app delivery with Predictive

Intelligent predictions and recommendations reduce defect backlogs and optimize resource usage, for software teams to continuously deliver quality applications.

Harness the power of application dark data for actionable insights.

Start planning for success using Predictive.

Setup application release for success. From story points to capacity requirements, analyze software teams’ past performance for more accurate planning and estimation of the actual development timelines.

Build Predictive into the continuous assessment pipelines.

Improve efficiency and accuracy when writing code across a complex application portfolio. Learn to identify code commits that are likely to break the build, and avoid rework by leveraging code for reuse.

Test continuously with Predictive, for quality application delivery.

Accelerate continuous application testing by predicting defect rates. Reduce time to fix by identifying the root cause of a failed test. Based on code changes, see recommendations for tests to reuse.

Collaborate across dev-test and operations with Predictive.

Promote collaboration among Development, Test, and Operations teams. Track and report on test coverage to actual use with production data, for test efficiencies that identify missed defects and resource gaps.

Under the hood with Micro Focus and Predictive

  • Learn

    Micro Focus Predictive Analytics algorithms leverage machine learning techniques to tune the calculations to historical data from the application development lifecycle to deliver tailored results.

  • Analyze

    Multivariate analysis, cluster analysis, and other advanced analytics are used to predict what is most likely to happen in current projects, based on learnings from team’s actual projects.

  • Recommend

    Micro Focus Predictive Analytics provides actionable, tactical recommendations for optimizing resource investments, increasing quality, mitigating risk, and improving timelines estimates.