The Union of Salesforce, Tableau Yields Hybrid ‘Business Science’
Saleforce’s June 2019 acquisition of Tableau Software gave the cloud-based CRM giant a foothold in the business intelligence visualization market. Nearly two years later, the combination has yielded what looks like a new product category dubbed “business science” that attempts to put data science and AI techniques in the hands of domain experts.
The package released this week includes an AI-based business science analytics tool aimed at analysts with little or no data science expertise. The democratization effort seeks to provide domain experts with AI-based tools that replace traditional data science capabilities.
The hybrid business science category is designed to deliver “self-service AI” that can be used for predictive analytics and scenarios like scenario planning, forecasting and model building. The package seeks to reduce friction by enabling users to click on AI-based tools rather than write code.
Available later this month, the initial version of Tableau 2021 platform also integrates Salesforce Einstein Analytics as the parent company enters the race to provide “augmented analytics.” Those enhancements include AI-assisted data preparation and insight generation.
Salesforce (NYSE: CRM) said the integration of its Einstein Discovery would allow users to bring its real-time predictions and recommendations directly into Tableau. The Einstein Discovery machine learning platform is widely used by Salesforce customers to quickly discern patterns in millions of rows of data, doing so without complex data models.
Aimed at both business analysts and data scientists, Tableau promotes its augmented analytics tools as democratizing data science across enterprises. The goal is making advanced analytics more accessible to business analysts with domain expertise. Potential uses cases include supply chain optimization and inventory control—including COVID-19 vaccine distribution.
Other capabilities integrated with the Tableau 2021 platform include connecting data to Microsoft Azure SQL Database. Tableau said it now supports Azure Active Directory via Azure Synapse and Azure Databricks connectors.
Meanwhile, and “extension gallery” enables search for connector and dashboard extensions within Tableau.
The business science package is the latest to seeking to replace complex data science modeling with “no-code AI”. The approach allows business analysts and domain experts to simply click on a “what-if” scenarios, forecasting models and analytics tools while providing “guided” model building.
According to a Tableau business science white paper, “It’s not about fine-tuning super precise models, but [rather] guiding people closest to the problem in the right direction.”
“Data science has always been able to solve big problems but too often that power is limited to a few select people within an organization,” added Francois Ajenstat, Tableau’s chief product officer, “We need to unlock the power of data for as many people as possible.”
Those features represent improvements over, say, static resource planning systems that struggle to keep pace with growing data complexity. Still, skeptics remain unconvinced that the shift to augmented analytics and no-code AI can handle the inherent complexity of use cases like dynamic supply chain management.
Dismissing the no-code trend, Stephen Pratt, CEO of explainable AI and workflow specialist Noodle.ai, asserted, “AI is not easy.”
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