Aible announced the upcoming launch of its new Aible for Tableau Extension. The Aible for Tableau extension empowers viewers of Tableau to optimize business impact with AI in Tableau. With Aible and Tableau, Tableau authors can easily create and democratize AI across the enterprise for anyone to get predictions, run what-if scenarios, and get actionable recommendations.
Aible business-ready AutoML provides a simple guided experience for Tableau authors to build predictive models right within Tableau in minutes. With point-and-click ease, Tableau talent can automatically create machine learning models using popular open source algorithms such as TensorFlow, GBM, H2O.ai, Spark, Scikit-learn and more. The company will be giving live demonstrations at booth #424 during Tableau Conference.
Aible partnered with Tableau Software, the leading analytics platform, to enable Tableau users to easily add AI to their existing BI environment and deliver more value from their BI investment. The Aible Extension for Tableau is an AI amplifier that provides Tableau users with a seamless end-to-end BI+AI experience that delivers measurable business impact.
“Over the past decade, analytics managers have struggled to find data scientists and upskill existing data analyst talent. Steep data science learning curves, long experimental projects, and unfamiliar terminology prevented AI success,” said Jen Underwood, VP of Product Management for Aible. “With the Aible for Tableau extension, data analysts can finally easily build and use actionable predictive and prescriptive models within Tableau. Our business-ready AutoML shows AI results in meaningful business language with actionable recommendations to rapidly get value.”
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Aible takes into account real cost-benefit tradeoffs to understand the net business impact of AI. It adjusts constraints and capacity in real time to simulate and optimize AI recommendations as situations change, and crafts an AI customized to a user’s unique business conditions. Anyone can click on a graph in Tableau to analyze the cause and effect of different variables to compare scenarios and understand predicted outcomes.
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