Artificial Intelligence Powered By Knowledge Graph


End-to-End Machine Learning Process In A Single Platform To Accelerate Time To Production Results, And Deliver Better Results!

 

Increase Context For Machine Learning With Graph

DataWalk can be utilized as a graph machine learning platform that enables you to quickly integrate and link all your internal and external data in a business representation through connections between business entities, processes, and events. This knowledge graph foundation allows you to derive new insights and patterns from vast amounts of existing data and metadata quicker than ever. DataWalk embeds AI technology to automatically complete, clean, overwrite, fix and enrich data so that it can quickly be used for further analysis.
 
 

Collaboration At The Enterprise Level

The knowledge graph interface allows data engineers, data scientists and citizen data scientists who are less technical to collaborate and accelerate results from machine learning. You no longer need to keep separate data workflows!
 
 

Automated Data Engineering Pipeline

With DataWalk’s graph machine learning platform capabilities you do not need to think about maintaining dozens of ETL tasks created from hundreds of lines of code. DataWalk is designed to support an entire enterprise data processing pipeline, automating it in the most optimal way, such that you can eliminate the need for further optimization regardless of whether it’s feature generation or any other data manipulation.
 
 

Jupyter Notebook Interface

With DataWalk you can access your knowledge graph via the Jupyter Notebook interface*, which enables you to create a sandbox with a separate data model for machine learning usage. Then you can use a variety of machine learning algorithms to train your model, even for vast amounts of data.
 
 

AutoML And Explainable AI

If desired, you can automate the tasks of applying machine learning with AutoML, including feature selection, hyperparameter tuning, iterative modeling, and model assessment. Then the model can be explained using various global Explainable AI (XAI) techniques.
 
 

One-Click Production Deployment

The DataWalk graph machine learning platform provides a Kedro starter** that guides Data Scientists to follow a predefined project structure to create both training and inference pipelines. When the best performing model is selected, it can then be instantly deployed in production without re-coding, with just a single click.
 
 
 
 

Instant Feedback Loop

Fast feedback is critical to effectively tune models, and with DataWalk ML/AI feedback is instantaneous and based on real data. When your models are deployed, then feedback is automatically captured. Better, faster feedback helps enable superior results.
 

Use Cases For DataWalk AI/ML

 

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