News

Iguazio Receives Honorable Mention in Gartner MQ for Data Science and ML Platforms Second Year in a Row

Real-Time Feature Engineering

Ingest real-time data, perform data transformation, generate and share real-time features across environments and teams to build and deploy high-performance AI applications

Real-Time Feature Engineering
in Production

Feature engineering in machine learning is like an art—a very challenging art. Generating a new feature based on batch processing takes an enormous amount of work for ML teams, and those features must be used for the training stage as well as the inference layer. Feature engineering for real-time use cases is even more complex than for batch. Real-time pipelines require an extremely fast event-processing mechanism, that can running complex algorithms to calculate features in real time. With the growing business demand for real-time use cases such as fraud prediction, predictive maintenance and building real-time recommendation engines, ML teams are feeling immense pressure to solve the operational challenges of real-time feature engineering for machine learning in a simple and reproducible way. The Iguazio Data Science Platform solves these challenges, with one single logic to generate real-time and offline features for training and serving, and an extremely fast event processing mechanism to calculate features in real time.

Benefits

Real-Time Automation

Real-Time Automation

Faster Deployment of AI

Faster Deployment of AI

Improved Model Accuracy

Improved Model Accuracy

Collaborate and Re-Use

Collaborate and Re-Use

Learn More

Data Science Platform Tutorials

Tutorial

Get started with a comprehensive video tutorial

Data Science Platform Documentation

Documentation

Access overviews, tutorials, references and guides