One of the biggest challenges with big data is operationalizing it—making it useful to the organization's groups and systems. Enterprises have spent a lot of money on analytics, but most never actually learn how to get the insights they need from these technologies. Now, with the machine learning available through TIBCO® Data Science-Team Studio software, you can search, monitor, and visualize all data flowing in and make the most of your big data assets.
In this demo, learn how you can guide your data science and machine learning projects through five key stages: define, transform, model, deploy, and act. How you can organize business stakeholders, data scientists, and engineers into project teams that collaborate to tackle the problem at hand. And how team members can share and annotate analytic assets such as data, scripts, and trained models within the project.
During the demo, Field Engineering team members will show how users:
- Access and prepare data within big data environments
- Create predictive modeling workflows
- Integrate Jupyter Notebooks within their workflows
- Collaborate with other data scientists and business users
- Deploy workflows to operational systems
Sign up for a demo today.