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

dotData empowers Tableau users to derive deeper, more diverse, and more predictive insights from their data via no-code, AI Automation

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.

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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 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.

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