Whitepaper

Introducing Tableau Business Science

Author
Andrew Beers, CTO (teknikansvarig), Tableau

This paper introduces Tableau Business Science, a new class of AI-powered analytics that brings data science capabilities to business domain experts.

Using AI, machine learning, and other statistical methods to solve business problems has largely been the purview of data scientists. Many organizations have small data science teams focused on specific mission-critical and highly scalable problems. But, there are a large number of business decisions that rely on experience and knowledge in addition to data.

With Business Science, analysts and business users who understand the context of their data can train and deploy explainable machine learning models to problems that small, focused data science teams don’t have the time or resources to prioritize.

At Tableau, analysis has always been about letting people ask that next question, explore that next hypothesis, test that next idea. Now, we’re taking it further and helping more people elevate their human judgment with practical, ethical AI that brings predictions into their business problems today. This helps organizations make even faster, more confident decisions across their lines of business, while expanding their analytics use cases and deepening their understanding of their own data.

Fortsätt läsa …

Det tar bara 15 sekunder att fylla i. Om du redan är registrerad kan du logga in.
Adress

Om författaren

image

Andrew Beers

Chief Technology Officer, Tableau

As Chief Technology Officer, Andrew Beers is responsible for Tableau's long-term technology roadmap and emerging technologies. During his tenure at Tableau, he has led many engineering teams, created new products, and personally written pieces of the product code.

Andrew has been at the heart of Tableau's engineering for most of the company's existence. Prior to joining Tableau in 2004, Andrew ran the engineering group at Align Technology, makers of the Invisalign system, building software to support large-scale customized manufacturing. He holds a master's degree in computer science from Stanford University, where he worked in Pat Hanrahan's computer graphics research group.