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dotData Enterprise Version 2.0 GA

July 20, 2020

dotData Enterprise Version 2.0 comes with significant updates and new features that completely change the AI/ML experience for citizen data scientists and deliver greater performance and transparency.

dotData released Version 2.0 as the Company continues to expand its product offerings and scale up operations to meet growing market demand for its full-cycle data science automation platform. In addition to full UX remodeling of its interface, additional key updates that deliver superior AI/ML experience include auto-balancing of accuracy and transparency, more accurate and interpretable auto-designed features, expanded out of the box connectivities and seamless model porting with dotDataPy and dotData Stream.

"We take the quality of features and quality of outcomes very seriously and are committed to continuous improvement of our platform," said Ryohei Fujimaki, Ph.D., founder, and CEO of dotData. "After we released dotData Enterprise 1.6.2 in December 2019, we made a big decision to fully remodel our UX to realize our commitment of democratizing enterprise data science. Today, we are very happy to announce the release of dotData 2.0 which redefines the AI/ML experience for all. This is a significant change that continues to expand our vision to simplify the data science process so that BI, data professionals, and analytics teams can accelerate the development of predictive analytics by taking advantage of AI and data science using automated machine learning."

Key updates of dotData Enterprise Version 2.0 include:

Full UX remodeling - Significantly simplified interface and workflow enable BI professionals to execute the entire ML/AI development process in just five minutes and more powerful visualizations enhance feature and model transparency.

Auto-balancing of accuracy and interpretability in AutoML - Automates the process to explore simpler ML models with minimal change in accuracy, in addition to pursuing the model for the highest accuracy. This enables users to balance accuracy and interpretability based on their business requirements.

More accurate and interpretable features - Version 2.0 introduces various improvements in its AI-powered feature engineering to produce more accurate and more interpretable features such as advanced categorical encoding, more natural feature explanation, and more robust feature selection to avoid multicollinearity.

Seamless BI+AI experience - Is realized through out-of-box connectivities with third-party data and business Intelligence platforms including Tableau, Teradata, and MS SQL / Azure database.

Flexible deployment options via dotDataPy and dotData Stream - Features and models developed using Version 2.0 are deployable both on dotDataPy as customizable Python end-points and on dotData Stream as real-time stream end-points.

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.

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