Thanks to it's distributed databases and streaming systems, Phi Suite makes it manageable to manipulate large quantities of data from various data sources.
By distributing processes and executing them in parallel, Phi Suite increases the execution speed and accelerates big data processing.
Machine learning models are plugged to the data source and automatically retrained to keep them synchronized with the new incoming data continuously.
Phi Suite automatically plugs every created event, database, or machine learning model to a dynamic API to make it instantly accessible to external systems.
Data engineering is built on top of software engineering and DevOps, skills we have been able to improve with VVF Luxembourg.
Industrial production pipeline automation is one of the best use-cases to challenge data engineering, a use-case we could test at R3D.