Tableau, the world’s leading analytics platform recently introduced Business Science, a new class of AI-powered analytics that lowers the barrier to data science techniques, enabling business users and analysts to make smarter decisions faster. In a market where agility is the ultimate competitive advantage, Business Science empowers more people with data, with simplified model creation, predictions, what-if scenarios, forecasting and other analytical methods, all using clicks, not code.
Tableau will deliver Einstein Discovery in its 2021.1 update, the first major release enabling Business Science. Integrating Einstein Discovery’s trusted, real-time predictions and recommendations into Tableau will help people go beyond understanding what happened and why it happened, to explore likely business outcomes and inform proactive action. For more than five years, Einstein Discovery has helped Salesforce customers surface insights and understand patterns across millions of rows of data in minutes, without requiring sophisticated data models.
In the present world, data science is out of reach for most business users. Business analysts have relied on data scientists to extract powerful, precise insights using sophisticated models. But getting to those insights can be complex, expensive and time consuming. While data science can unlock powerful insights, there is sometimes a trade-off between precision and time-to-insight. Business Science recognizes that trade-off and seeks to make data science accessible and actionable for more people.
Customers can use Business Science to improve supply chain efficiency, predict likelihood of purchase or maximize delivery of goods or services, for example. Data science could help with vaccine research and development, while Business Science could help with distribution and get shots in people’s arms.
Machine Learning platforms like Einstein Discovery are the next frontier in democratizing data science. Einstein Discovery integrated into Tableau brings predictive capabilities to the existing inventory of dashboards companies already have, and when that’s combined with auto-generated machine learning models, businesses can explore patterns, trends and correlations in their historical data without writing a single line of code. Layering ML/AI capabilities on existing BI infrastructure opens up a world of possibilities in day-to-day business problem solving.
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