Fabric provides automated data profiling, augmentation, cleaning and selection, in a continuous flow to improve training data and models performance.
Start improving the quality of your data and you Machine Learning models performance at scale within days not months.
Ingest data from FileSystems to RDBMS' in a few steps
Understand your data assets with automated data profiling
Generate synthetic data in a few clicks
Experiment in a familiar environment with Jupyter Labs and VS Code
Build, version & iterate your data preparation flows with pipelines
Simplified, scalable and simple connection to a variety of data sources. Understand your data assets through automated profiling and detection of quality issues for faster exploratory data analysis and data preparation.
On-demand development environments with configurable hardware (including GPUs). Support for Python & R for a no-learning curve data experimentation space.
Supercharged with the most popular DS libraries and the YData SDK.
Artificially generated data that doesn’t match any individual record. While resembling real data, synthetic data ensures both business value while being compliant with privacy regulations.
Synthetic data is great to enable data-sharing initiatives or to boost ML models performance.
General-purpose job orchestrator with built-in scalability, modularity for experiment tracking capabilities. Pipelines bring the Ops to your Data-Centric AI workflows.
Become the best in class by delivering faster and better AI solutions with improved data.