IBM Watson Studio helps you get to insights faster with self-service, drag-and-drop data analytics right from your desktop.
- Data preparation
- Eliminate time-consuming, repetitive tasks and harness the power of IBM Data Refinery to explore, prepare and refine data. An intuitive spreadsheet-like interface makes it easier to sample even the largest data sets and identify missing fields, outliers, unusual distributions and other data quality issues. Then you can define transformations to remediate any problems before the modeling process begins.
- Text analytics
- Items such as reports, web pages, emails and call center notes contain a wealth of insights. Without the technology to analyze it, you’re leaving those insights undiscovered. Leverage built-in, industry-leading dictionaries and a simple UI to explore this data with text analytics.
- Model development
- Use the SPSS Modeler canvas embedded in Watson Studio Desktop to build models using a simple drag-and-drop design process. The intuitive graphical interface helps to visualize each step in the data mining process as part of a stream, so analysts and business users without coding experience can add expertise and business knowledge to the process.
- Model Deployment
- Put your models to work by deploying them in applications throughout your business. Leverage IBM Watson Machine Learning Server (sold separately) to quickly and securely deploy models created using: (1) Jupyter Notebooks or SPSS Modeler from within Watson Studio Desktop, (2) SPSS Modeler standalone, (3) pure open source tools or (4) an open source-SPSS hybrid.
- Support for many data sources
- Get a complete view of your business by analyzing data no matter where it lives — in flat files, spreadsheets or major relational databases. Access it all with IBM Watson® Studio Desktop.
- Data visualization
- Build sophisticated visualizations of your data analytics results and communicate the insights you’ve discovered by easily exporting them. Business users can explore their data sets with live charting and a large variety of charts and graphs.
- Explore data sets, run experiments, describe your methods and share the results with your team. Notebooks provide an interactive environment where data, code and visualization exist side by side, so teams can repeat and verify each other’s methods and confirm results easily.
- Project management
- Create and manage projects to organize your data, models and documentation for both offline use and online collaboration. Combine your own data sets with assets from your organization’s data catalog, while maintaining full compliance with security and governance policies.
- Machine learning methods and algorithms
- Take advantage of decision trees, neural networks and regression models available from IBM SPSS® Modeler as part of Watson Studio Desktop. Include ARMA, ARIMA and exponential smoothing; transfer functions with predictors and outlier detection; benefit from ensemble and hierarchical models; support vector machine and temporal causal modeling; and employ time series and spatial AR for spatiotemporal prediction. Generative adversarial networks (GANs) and reinforcement also enable deep learning.
Who can get Watson Studio Desktop Free Student License
Established in 2005, the IBM Academic Initiative allows and encourages faculty, students and researchers at accredited academic institutions to leverage IBM tools, courses, and other resources in the classroom. Our mission is to enable students to graduate with direct hands-on experience on “industrial strength” tools that will help them in their chosen career.
Watson Studio Desktop, with unlimited compute, is free 30-day trial without credit card if you have a normal free account. But it is now available for free to students and faculty for teaching and learning purposes via a 1 year subscription. Because this is a subscription, new features and functionality will be added every few weeks through in-product updates. In addition, a student or faculty member can re-register after 1 year as long as they remain a student or faculty member.