dotData releases data science automation platform; adds enhancements in AI-powered Feature Engineering, model operationalization

dotData announced on Monday availability of Version 1.2 of its dotData Platform. The new version adds 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 automates 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.

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.

dotData is a spinoff of NEC Corporation that focuses on delivering end-to-end data science automation for enterprises. Its fully-automated data science platform speeds time to value by democratizing, operationalizing and accelerating the entire data science process, from raw data ingestion through AI-powered feature engineering to ML models in production. dotData is delivering new levels of speed, scale and value in deployments across multiple industries.

The dotData Platform now comes automatically designed by the company’s AI-powered feature engineering. Attribute features are critical in use cases where very limited historical data is given, like 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 predictions in these types of challenging use cases.

It also enables IT/software engineers to redesign features and retrain machine learning models through dotData Retraining APIs. This enhancement eliminates the periodic and manual maintenance of the operationalized features and machine learning models in production. It includes new model porting that allows 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 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 time-consuming and labor- and skill-intensive aspects of a data science project, accelerating the data science process from months to days.       

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


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