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dotData and Snowflake Integration Automates Full-Cycle AI Development From Data Through Automated Feature Engineering to AutoML

  • Integration Empowers Customers to Quickly and Easily Gain Insights and Intelligence Faster From Their Data

dotData, a leader in full-cycle enterprise AI automation solutions, announced the availability of dotData Platform with Snowflake, a leading Cloud Data Platform.

The new integration streamlines and simplifies the movement of data between Snowflake and dotData to help the companies’ joint customers democratize data science for the enterprise and derive more value from their AI and machine learning initiatives. Now, with a few clicks, all Snowflake users can leverage dotData’s award-winning automated feature engineering to discover hundreds of feature patterns from massive amounts of data stored in Snowflake and to automate full-cycle AI development from data collection and preparation through Automated Feature Engineering (AutoFE) to machine learning operationalization.

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“We are thrilled to be able to provide the power of Automated Feature Engineering for Snowflake clients. This will open up a new world of possibilities for companies that leverage the data stored in their Snowflake ecosystem to be able to build and discover features automatically using dotData’s powerful Automated Feature Engineering,” said Ryohei Fujimaki, Ph.D., founder and CEO of dotData.

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dotData automates feature engineering, the most manual and time-consuming step in AI and ML projects. dotData’s proprietary AI technology automatically discovers hidden patterns behind hundreds of tables with complex relationships and billions of rows and AI-features for your AI and ML algorithms. Until now, feature engineering has 100 percent relied on intuition and experience of domain experts and data scientists. With dotData, you can leverage AI to discover unknown-unknowns and build greater AI and ML models.

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Experienced data science teams can leverage dotData’s AI features to augment in-house developed features. Automated feature engineering (AutoFE) provides a fast and automated means to rapidly prototype use cases, explore new datasets to find important patterns, and improve accuracy of AI and ML models. It is available as a Python library seamlessly integrated with your existing Python workflow, and cuts 80 percent of time to develop features for your AI and ML models.

Business intelligence and analytics teams can leverage dotData’s no-code AI/ML automation solution to make their reporting and dashboards more predictive and actionable. It offers a streamlined integration of AutoFE and automated machine learning (AutoML) and allows you to develop production-ready features and ML models from raw business data, in just days.

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