Avgidea has implemented new Data Exchange and Function capabilities in the Avgidea Data Platform (ADP) as an environment for business-to-business data exchange and execution of AI predictive models. Data engineers and data scientists can reduce their workload in exchanging/processing data and deploying AI predictive models with customers and group companies.
In addition to Avgidea's SaaS offering, ADP can also be deployed as an OEM product in a company's Google Cloud™️ project and offered as a service to its own users. Once deployed as an OEM product, Avgidea will add new features, apply updates, and perform maintenance tasks such as monitoring, operation, and maintenance.
Two new components have been added to the Avgidea Data Platform.
Avgidea Data Exchange (ADX)
ADX integrates with various data services in the public cloud provided by different vendors, allowing users to move data to different storage and databases with no code. In addition, data owners can limit the scope of data sharing by explicitly selecting where and with which data is exchanged.
Like social networking services, users can communicate with other users in a closed environment, as data is shared only among users on the platform.
Avgidea Function (AFX)
By utilizing AFX, preprocessing operations such as data cleansing and character code conversion that occur before importing data into the database can be performed on files and directories stored in the ADP storage as functions written in Python.
You can also attach AI prediction models built with custom Python packages, TensorFlow™️, PyTorch™️, scikit-learn™️, etc. as libraries and run them against files in ADP's storage. functions registered in AFX can be explicitly shared on the GUI, allowing end users to directly execute AI predictive models created by data scientists.
Running scikit-learn clustering: https://youtu.be/DBF0_DAPMPY
Avgidea Data Platform Usage Scenarios