Skytree enables data scientists to build more accurate models faster. But what does that mean for you?
Make game-changing business decisions. Data-driven decisions are only as good as the models you build. With Skytree, your models will be more predictive. If even a 1% increase in model accuracy increases customer satisfaction, revenue and cost savings by millions of dollars, imagine the results of a 5% or 10% improvement.
Create an agile business environment. Faster models means responding in real time to business developments with highly relevant analytics. Address more use cases and solve more problems in more areas of your business.
Get direct access to your analytics. Even business analysts and citizen data scientists can build machine-learning models with Skytree’s automation, streamlined workflow and intuitive graphical user interface. Self-documenting models allow for full oversight with minimal time required from advanced data scientists while reducing time required for model management, collaboration and validation. Your model governance process just got a lot simpler. Plus, Skytree’s powerful visualization tools make interpreting and explaining models to executives and regulators much easier. What will the data scientists do with all their extra time?
Maximize your investment in big data. If your data isn’t being used for predictive analytics, it’s costing you money instead of delivering quantifiable results that can save or make the company millions. Skytree can be up and running in days, providing quick and measurable returns on your big data investment and ROI for your analytics initiatives.
Scale, utilize and secure your data like never before. Unlike open-source machine learning technologies, Skytree’s high performance computing architecture is specifically designed to scale hardware and data to fit enterprise-grade big data needs, now and in the future. It comes out of the box with secure LDAP authentication and Kerberos support, allowing you to centrally and securely authenticate users and provide support for single sign-on, as well as provide security for your data. In the event of Edge node failure, Skytree improves uptime to meet SLAs by supporting Edge node stateful failover so you don’t need to restart a job from scratch.
Integrate machine learning into your existing infrastructure. Built from the ground up to run on big data environments, Skytree works with the tools you already have. Its intuitive GUI allows administration without weeks spent learning a new language. On the backend, Skytree is certified on all the latest major Hadoop distributions and can be installed on your existing Hadoop cluster. It leverages YARN for prioritization, Spark for data processing and a highly collaborative IT controlled resource management. Models are deployed into production using PMML, a REST API, and/or JAR, making it easy to integrate models into existing environments, third party scoring engines or business intelligence infrastructure.
Skytree uses the full dataset and automated modeling using artificial intelligence. But what does that mean for you?
Use all your data and experiment more. You never need to train models on sample data again. Using the full dataset means capturing more rare events in your analysis, utilizing more features and sophisticated algorithms, and building more predictive models. Skytree’s artificial intelligence let you identify the best fitting machine learning model for more iterative and accurate modeling.
Build and deploy faster than ever before. We’ve made everything easier and faster – data prep, building models and deployment. Skytree’s machine learning transformations simplify the data prep process so that you never have to use another platform or write 100s of lines of code to utilize structured or unstructured text data. And with increased automation you can respond with more agility and focus on more high-value use cases.
Easily explain and share your models. Skytree demystifies the data science process with visualization capabilities that enable you to explain your models to executive management, regulators and citizen data scientists when asked. You can also easily share your models with collaborators and bring increased transparency and flexibility to your organization’s advanced analytics.