dotData Announces Enhancement of MLOps Capability 
with dotData Stream and Amazon SageMaker Integration

dotData Announces Enhancement of MLOps Capability 
with dotData Stream and Amazon SageMaker Integration

October 27, 2020

Integration Augments dotData’s Model Deployment and Operationalization Framework and Enhances dotData’s MLOps Capability for AWS Users

San Mateo, CA – October 20, 2020 dotData, a leader in AutoML 2.0 software to help accelerate AI/ML development and operationalization for the enterprise, today announced that dotDataStream now fully supports Amazon SageMaker integration, one of the top MLOps platforms in the industry.

Amazon SageMaker is a fully managed service that provides developers and data scientists with the ability to deploy machine learning (ML) models quickly. Now, with simple point-and-click operations, dotData users can launch dotData Stream on Amazon SageMaker and leverage the platform’s fully-managed capability to monitor, manage, orchestrate, govern and maintain AI/ML models developed using dotData Platform.

This integration provides dotData/AWS users with a full-cycle data science automation experience, from automated AI/ML development using dotData Enterprise through instant AI/ML deployment using dotData Stream to AI/ML lifecycle management with AWS SageMaker. The combination of dotData and Amazon SageMaker helps make AutoML 2.0 accessible to more enterprises and propels data-driven intelligence for business.

“We are continually improving the capabilities of our end-to-end AI automation platform, and this is an important milestone that enhances dotData’s model deployment and operationalization framework, a critical component in the enterprise AI lifecycle,” said Ryohei Fujimaki, Ph.D., CEO and Founder of dotData. “We are pleased to extend our partnership with AWS to help our mutual customers accelerate their digital transformation initiatives and drive greater ROI from their data science and AI projects.”

In July, dotData announced dotData Stream, an extremely portable containerized AI/ML engine that enables real-time predictive capabilities. dotData users can develop AI/ML models using dotData Enterprise or dotData Py and then deploy AI/ML models just with a single docker command using dotData Stream. dotData Stream is designed to be easily deployable on an out of the box MLOps platform or container orchestration frameworks.

dotData provides AutoML 2.0 solutions that help accelerate the process of developing AI and Machine Learning models for use in predictive analytics BI dashboards and advanced analytics applications. dotData makes it easy for BI developers and data engineers to develop AI/ML models in just days by automating the full life-cycle of the data science process, from business raw data through feature engineering to implementation of ML in production utilizing its proprietary AI technologies. dotData’s AI-powered feature engineering automatically applies data transformation, cleansing, normalization, aggregation, and combination, and transforms hundreds of tables with complex relationships and billions of rows into a single feature table, automating the most manual data science projects that are fundamental to developing predictive analytics solutions.

dotData democratizes data science by enabling BI developers and data engineers to make enterprise data science scalable and sustainable. dotData automates up to 100 percent of the AI/ML development workflow, enabling users to connect directly to their enterprise data sources to discover and evaluate millions of features from complex table structures and huge data sets with minimal user input. dotData is also designed to operationalize AI/ML models by producing both feature and ML scoring pipelines in production, which IT teams can then immediately integrate with business workflows. This can further automate the time-consuming and arduous process of maintaining the deployed pipeline to ensure repeatability as data changes over time. With the dotData GUI, AI/ML development becomes a five-minute operation, requiring neither significant data science experience nor SQL/Python/R coding.

For more information or a demo of dotData’s AI-powered full-cycle data science automation platform, please visit

About dotData

dotData Pioneered AutoML 2.0 to help business intelligence professionals add AI/ML models to their BI stacks quickly and easily. Fortune 500 organizations around the world use dotData to accelerate their ML and AI development to drive higher business value. dotData’s automated data science platform accelerates ROI and lowers the total cost of ownership by automating the entire data science process that is at the heart of AI/ML. dotData ingests raw business data and uses an AI-based engine to automatically discover meaningful patterns and build ML-ready feature tables from relational, transactional, temporal, geo-locational, and text data. dotData’s automated platform discovers patterns, optimizes ML models and makes it easy to deploy predictive algorithms without impacting operational data.

dotData has been recognized as a leader by Forrester in the 2019 New Wave for AutoML platforms. dotData has also been recognized as the “best machine learning platform” for 2019 by the AI breakthrough awards, was named an “emerging vendor to watch” by CRN in the big data space and was named to CB Insights’ Top 100 AI Startups in 2020. For more information, visit, and join the conversation on Twitter and LinkedIn.

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Jennifer Moritz
Zer0 to 5ive for dotData



dotData Inc.

dotData Automated Feature Engineering powers our full-cycle data science automation platform to help enterprise organizations accelerate ML and AI projects and deliver more business value by automating the hardest part of the data science and AI process – feature engineering and operationalization. Learn more at, and join us on Twitter and LinkedIn.