Access data of any complexity, size or speed with a robust suite of data management tools.

Streamline data preparation with native access engines, integrated data quality, and data preparation tools that use AI to automate time-consuming tasks.

Take advantage of traditional, structured data as well as new formats, such as streaming sensor data.

Tackle problems of any size or complexity with an extensive suite of proven analytic techniques.

Take advantage of programming-language flexibility, which gives you broader access to algorithms and a larger talent pool to hire from.

Make powerful analytics accessible to everyone across your organization, regardless of skill or experience.

Select the best model and govern its use – whether you're building one or thousands – with robust model governance. Evaluate and select the champion model from all competing models. Then register it in a centralized repository, with version control, for visibility and simplified compliance processes.

Get the best models into production quickly with faster, easier model deployment – no recoding needed. Deploy models in a few clicks to a range of targets – e.g., in database, streaming, a container or a REST API. Or deploy them into a decisioning/workflow engine.

Build models once and deploy them anywhere – without recoding and without an additional testing cycle. The Viya unified code base saves you immense time and effort.

Lineage

Gain an upstream and downstream understanding of how data is used and transformed – from sources to transformations, models and reports – with a visual overview. And identify related data that has potential value.

Monitoring

Automatically monitor model performance over time to ensure models continue to perform as expected, regardless of the language used to create them. Track models from inception to usage to retirement. Get notified automatically when performance degrades so you can improve, replace or remove the model from production.

Automation

Improve efficiency and effectiveness throughout the analytics life cycle. Speed data preparation with intelligent tagging that uses AI to identify data type within a column. Generate models fast using templates and automated analysis. Use automated workflows to streamline operationalizing and updating models.