dotData Launches dotData Py Lite, Putting the Power of AI Automation on Every Data Scientist

dotData and Tableau Partner to Accelerate Augmented and Predictive Analytics for The Business Intelligence Community

September 14, 2021

dotData empowers Tableau users to derive deeper, more diverse, and more predictive insights from their data via no-code, AI Automationmpowers Databricks users to explore 10x more data and discover 100x more features to deliver greater ML models

SAN MATEO, Calif., Sept 14, 2021 dotData, a leader in full-cycle enterprise AI automation solutions, today announced a partnership with Tableau, the world’s leading analytics platform, to enable Tableau users to leverage the power of dotData’s AI Automation Capabilities.  

As a result of this partnership, Tableau users will be able to build customized predictive analytics solutions faster and more easily. By combining Tableau’s data preparation and visualization capabilities with dotData’s augmented insights discovery and predictive modeling capabilities, Tableau users can perform full-cycle predictive analysis from raw data through data preparation and insight discovery through AI-based predictions and actionable dashboards.

“This partnership empowers a new class of citizen data scientists through our low code and no-code platforms and allows users to discover deeper, more diverse, and more predictive insights,” said Ryohei Fujimaki, Ph.D., founder and CEO of dotData. “We are very excited about this partnership with Tableau, one of the world’s most renowned analytics platforms. This partnership accelerates our vision to democratize augmented and predictive analysis for the enterprise through AI automation.”

dotData automates the full-cycle AI/ML development process, including data and feature engineering, the most manual and time-consuming step in AI and ML development. dotData’s proprietary AI technology automatically discovers hidden and multi-modal insights from relational, transactional, temporal, geo-locational, and text data. 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 automated feature discovery and automated machine learning (AutoML) and allows BI teams to develop full-cycle ML models from raw business data, without wiring code.  

About dotData

dotData pioneered AI-Powered Feature Engineering to accelerate and automate the process of building AI/ML models, to drive higher business value for the enterprise. dotData’s automated data science platform accelerates ROI and lowers the total cost of model development 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 scalable, flexible platform enables data scientists to discover and evaluate outstanding AI features; and empowers business intelligence professionals to addAI/ML models to their BI stacks and predictive analytics applications quickly and easily. Fortune 500 organizations around the world use dotData to accelerate their ML and AI development to drive higher business value.

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 a CRN “emerging vendor to watch” in the big data space in 2019 and featured on CRN’s 2020 and 2021 Big Data 100 list, and was named to CB Insights’ Top 100 AI Startups in 2020. For more information, visit, and join the conversation on Twitter and LinkedIn.

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.