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- Create a notebook in which you run Python, R, or Scala code to prepare, visualize, and analyze data, or build a model.
- Automatically analyze your tabular data and generate candidate model pipelines customized for your predictive modeling problem.
- Create a visual flow that uses modeling algorithms to prepare data and build and train a model, using a guided approach to machine learning that doesn’t require coding.
- Create and manage scenarios to find the best solution to your optimization problem by comparing different combinations of your model, data, and solutions.
- Create a flow of ordered operations to cleanse and shape data. Visualize data to identify problems and discover insights.
- Automate the model lifecycle, including preparing data, training models, and creating deployments.
- Work with R notebooks and scripts in an integrated development environment.
- Create a federated learning experiment to train a common model on a set of remote data sources. Share training results without sharing data.
- Deploy your AI models and manage your deployments.
- Find and share your data and other assets.
- Import asset metadata from a connection into a project or a catalog.
- Enrich imported asset metadata with business context, data profiling, and quality assessment.
- Create and run masking flows to prepare copies of data assets that are masked by advanced data protection rules.
- Create your business vocabulary to enrich assets and rules to protect data.
- Create a flow with a set of connectors and stages to transform and integrate data. Provide enriched and tailored information for your enterprise.
- Create a virtual table to segment or combine data from one or more tables.
- Measure outcomes from your AI models and help ensure the fairness, explainability, and compliance of all your models.
- Replicate data to target systems with low latency, transactional integrity and optimized data capture.
- Create visually stunning dashboards that are fully interactive with a simple drag-and-drop user interface. Find hidden insights in your data and then share them with others in your organization.
- Consolidate data from the disparate sources that fuel your business and establish a single, trusted, 360-degree view of your customers.
- Develop sophisticated machine learning models using Notebooks and code-free tools to infuse AI throughout your business.
- Deploy, manage, and integrate machine learning models into your applications and services in as little as one click.
- Discover, profile, catalog, and share trusted data in your organization.
- Create ETL and data pipeline services for real-time, micro-batch, and batch data orchestration.
- View, access, manipulate, and analyze your data without moving it.
- Monitor your AI models for bias, fairness, and trust with added transparency on how your AI models make decisions.
- Build and deliver visually stunning dashboards that accelerate your journey towards a data driven business.
- Improve trust in AI pipelines by identifying duplicate records and providing reliable data about your customers, suppliers, or partners.
- Provide efficient change data capture and near real-time data delivery with transactional integrity.
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