DotData Launches Containerized AI Model for Real-Time Prediction
Highly scalable AI/ML container can be deployed in the cloud for ML orchestration or at the edge for intelligent IoT.
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DotData, a leader in full-cycle data science automation and operationalization for
the enterprise, has launched
dotData Stream, a new containerized AI/ML model that enables real-time
predictive capabilities for dotData users. DotData Stream was developed to
meet the growing market demand for real-time prediction capabilities for
use cases such as fraud detection, automated underwriting, dynamic pricing,
and industrial IoT.
DotData Stream performs real-time predictions using AI/ML models developed
on the dotData Platform, including feature transformation such as one-hot
encoding, missing-value imputation, data normalization, and outlier filter.
It is highly scalable and fast; a single prediction can be performed as
fast as tens of milliseconds or even faster for microbatch predictions.
Deploying dotData Stream is as easy and simple as launching a docker
container with AI/ML models downloaded from the dotData Platform with just
one click. An endpoint for real-time predictions becomes immediately
available. In addition, dotData Stream can run in cloud MLOps platforms for
enterprise AI/ML orchestration or at the edge servers for intelligent IoT
DotData provides AutoML 2.0 solutions that help accelerate development of
AI and machine learning (AI/ML) models for advanced predictive analytics BI
dashboards and 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.
It 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, visit