dotData Releases Updates to the First and Only End-to-End Data Science Automation Platform

Adds significant enhancements in AI-powered feature engineering, model operationalization, and feature/model insights

dotData, the first and only company focused on delivering end-to-end data science automation and operationalization for the enterprise, announced the availability of Version 1.2 of its dotData Platform. The new version adds significant enhancements to the platform, enabling users to have even deeper insights, more transparency, and greater business impacts in the development and operationalization of their data science projects.

The AI-powered dotData Platform completely automates the entire data science process, from data collection through production-ready models. As a result, the entire data science process is accelerated from months to days, enabling companies to rapidly scale their AI/ML initiatives to drive transformative business changes.

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The dotData Platform also democratizes the data science process by enabling more participants with different skill levels to effectively execute on projects, making it possible for enterprises to operationalize 10x more projects with transparent and actionable outcomes.

“The new enhancements available in Version 1.2 are significant in that they add measurable benefits to users,” said Ryohei Fujimaki, PhD, dotData’s CEO. “We can now provide even stronger features, easier model operationalization, greater transparency, and deeper insights.”

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Key updates of the dotData Platform include:

New Attribute Features

• Are now automatically designed by dotData’s AI-powered feature engineering. Attribute features are critical in use cases where very limited historical data is given, e.g., making product recommendations to a new customer about whom little is known. Attribute features are generated by taking into consideration customers with similar attributes, offering powerful predictions in these types of challenging use cases.

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Enhanced Model Operationalization

• Enables IT/Software engineers to redesign features and retrain machine learning models via dotData Retraining APIs. This enhancement eliminates the periodic and manual maintenance of the operationalized features and machine learning models in production.
• Includes new Model Porting, which enables users to port a developed process from the initial development environment to the production environment in just a few clicks. This enhancement provides a more flexible way to operationalize data science projects throughout the enterprise.

Feature and Model Insights on dotData GUI

• New feature insights provide natural language explanations and “blueprints” of AI-derived features, as well as visualization of feature statistics and distributions, delivering more transparency and deeper insights.
• New model insights provide comparisons of hundreds of machine learning models and visualization of detailed model statistics and accuracy metrics, to name a few, enabling data scientists to better understand model performance.

Unique to the dotData Platform is its proprietary, AI-powered Feature Engineering, which eliminates the most time-consuming and labor- and skill-intensive aspects of a data science project, accelerating the data science process from months to days.

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