Enhanced capabilities in dotData Ops 1.4 include seamless operationalization of SQL-based data & feature transformations and Python machine learning models.

SAN MATEO, California, SEP 17, 2024 – dotData, a pioneer and leading provider of feature discovery platforms, today announced version 1.4 of dotData Ops, which revolutionizes MLOps with data, feature, and model orchestration. This latest version introduces significant new capabilities, including seamless operationalization of SQL-based data, feature pipelines, and Python machine learning models. In simpler terms, dotData Ops now orchestrates any data transformation and predictive models developed outside of the dotData ecosystem, all within a single platform. Version 1.4 is tailored for organizations that require a high degree of customization and control over their data processing and machine learning pipelines, enabling a fully customized data science workflow that aligns precisely with unique operational requirements and strategic goals. 

“Today’s enhancements are a testament to our commitment to simplifying and accelerating enterprise AI and ML,” said Ryohei Fujimaki, CEO and founder of dotData. “By enabling the deployment of external Python models and supporting advanced SQL features in our pipelines, dotData users can flexibly develop and deploy their domain-specific features alongside programmatically discovered features using dotData.”

Key updates of dotData Ops Version 1.4 include:

Advanced Support for SQL-based Data and Feature Transformation

Version 1.4 grants organizations the utmost flexibility to deploy their own SQL-based data and feature transformations. Users can now utilize their in-house developed SQL scripts and queries to preprocess data and generate features. This new deployment option – enabled by the recent integration between dotData Feature Factory and dotData Ops – allows users to combine their domain-specific features with programmatically discovered features using the dotData Feature Factory. This enhancement significantly boosts dotData Ops’ unique ability to orchestrate both data and feature transformations, extending well beyond just predictive models.

Advanced Support for Python Machine Learning Models

Version 1.4 expands its capabilities to include support for Python machine learning models developed outside the dotData ecosystem. Once features are engineered – either manually or via dotData’s Feature Factory – users can train their preferred Python machine learning models using these features. The developed Python models are then converted into the ONNX format, the industry’s most widely recognized standard for machine learning models, and are deployed within dotData Ops. This crucial update creates a more inclusive environment for deploying a diverse array of machine learning models. It allows users to integrate their existing data science workflows without significant modifications, thereby enhancing their ability to tailor predictive models to specific business needs.

Python SDK to Automate dotData Ops with Seamless Feature Factory Integration

Version 1.4 introduces a flexible Python SDK that enables programmatic access and operation of dotData Ops from Python. Equipped with this new SDK, users can automate their entire ML lifecycle—from data preprocessing to feature generation to predictions—accelerating their workflows significantly. Moreover, the SDK ensures seamless and streamlined integration with dotData Feature Factory, another component of the dotData product family that operates on Python. Users of dotData Feature Factory can now deploy their data and feature pipelines to dotData Ops with just a few lines of code using the new Python SDK.

dotData’s continuous innovation in automating data science tasks—from data preparation to feature engineering and operationalization—positions dotData Ops as a pivotal solution for businesses looking to harness the power of their data for strategic advantage.

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About dotData

dotData’s pioneering automated feature discovery and engineering platform addresses the most complex challenge of AI/ML projects. Our Feature Factory technology uncovers hidden gems, providing transparent, explainable features by connecting the dots within large-scale data sets in hours, eliminating human bias. It allows data scientists to explore up to 100X more features, including those yet to be imagined, and augments AI/ML projects in an agile manner, delivering business value faster. In an era of rapid change, insights discovered through AI can be a game-changer for business growth and innovation across industries. The power of dotData’s platform to provide game-changing insights is why Global Fortune 500 organizations trust dotData.

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dotData
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