Data Science Notebook
OpenText Magellan for Data Scientists
Empower smarter, data-driven decisions with machine learning projects on an AI and analytics platform featuring a data science notebook
Why data science notebooks?
Collect and operationalize huge volumes of structured and unstructured data
An AI data-powered data science notebook automates big data processing by connecting to a variety of repositories and leveraging data mining techniques. This minimizes tedious tasks for data scientists and allows them to focus on solving complex challenges through powerful models.
Share insights from machine learning models
Data scientists can publish and share machine learning models across the enterprise with the Magellan data science notebook. Subject matter experts and business users can explore this information through analytics dashboards, drag and drop capabilities and data visualization options that match their preference.
Meet changing business needs
Data scientists can combine machine learning models with evolving big data and big content to create a predictive modelling knowledge base that scales with the organization.
OpenText Magellan for Data Scientists includes
OpenText Professional Services:
Al & Analytics Services
The OpenText™ Magellan™ Professional Services team includes data scientists and experts on application machine learning, text mining and algorithms in data analytics scenarios.
They have a deep expertise with Magellan and analytics technologies and are experienced working with organizations across many industries to glean insight from their data.Learn more
Get a free guided tour of the data science notebook
- Solution overview: Solving the unstructured data puzzle with AI-powered analytics
- Product overview: OpenText Magellan
- Infographic: AI data analytics
- Blog: The hidden message in reams of text
- Blog: 7 steps to getting started with your AI journey
- Blog: OpenText Insights from Gartner Analytics and BI Bake-Off
- White paper: Cognitive computing reshapes enterprise decision-making
- Webinar: Deriving Value from the 80% of Data You’re Not Using