Tableau adding new storytelling tool to analytics platform

Tableau on Tuesday unveiled a new data storytelling feature, the result of its acquisition of Narrative Science in late 2021, along with an updated cloud version of its analytics platform and additional self-service data science capabilities.

The vendor, founded in 2003 and based in Seattle, revealed the new tools in Las Vegas during Tableau Conference 2022, its annual user conference and first in-person event since November 2019 before the COVID-19 pandemic. The new cloud version of the Tableau analytics platform is now generally available, while the data storytelling and self-service data modeling capabilities are expected to be generally available before the end of 2022.

Each of the new tools is aimed at furthering Tableau's goal of helping people more easily see and understand data, according to Francois Ajenstat, Tableau's chief product officer.

"The opportunity we have is to make data useful for everyone," he said. "There is a data revolution going on, and we want to bring data everywhere for everyone."

Despite advances in augmented intelligence capabilities -- like natural language processing that enable users to type and speak natural language to work with data rather than requiring them to write code -- and advances in embedded analytics that enable users to work with data in normal workflows rather than a business intelligence environment, data and analytics are still the domain of a minority of workers within most organizations.

Studies have shown that only about one-quarter to one-third of employees use analytics as part of their job, and that number has held steady for years despite the best efforts of vendors to develop easy-to-use tools.

One hope for breaking through the barrier to analytics is data storytelling, which is simply an automatically generated explanation of data so that the data doesn't have to be interpreted by someone with data literacy training. In its attempt to make analytics easy and accessible for as many workers as possible, Tableau acquired Narrative Science, a data storytelling vendor, and on Tuesday unveiled Data Stories.

Data Stories is a direct result of Tableau's acquisition of Narrative Science, according to Ajenstat. Once released, the tool will automatically generate plain-language explanations of Tableau dashboards, potentially enabling more users to work with data -- and enabling those who already do work with data to develop insights more quickly.

And that will be a significant benefit for Tableau customers, according to Doug Henschen, an analyst at Constellation Research.

"Integration points already existed between Tableau and Narrative Science, but Narrative Science's best capabilities were optional," he said. "Narrative Science had great capabilities, so this will be a plus for Tableau customers."

Ajenstat, meanwhile, noted that Data Stories represents the latest step in Tableau's efforts to make analytics accessible to as many users as possible.

"For years, we've been focused on making data easy, making it accessible," he said. "So when I think about Data Stories, it's a follow-on to the acquisition, and we think it's a critical capability to get past that adoption barrier."

In addition to Data Stories, Tableau introduced Tableau Cloud, which is a rebranding of Tableau Online that will be the vendor's flagship analytics platform going forward, rather than its enterprise version for on-premises users, according to Ajenstat.

"The cloud is now the predominant way people are deploying Tableau," he said. "The growth in cloud data is changing the dynamics [of analytics], and we want to emphasize that as not just another version of Tableau, but as the premier experience for Tableau. It's enterprise-ready and fast to value, and that's what customers are looking for right now."

New self-service data science capabilities are a third highlight of what Tableau revealed at the start of its user conference.

Tableau introduced the concept of business science during its virtual user conference in November 2021, and defines business science as the use of AI and machine learning to give business users data science capabilities such as predictive modeling.

Business science is the result of Tableau's integration with Salesforce's Einstein Discovery. Salesforce acquired Tableau in 2019.

Previously, Tableau unveiled Model Builder and Scenario Planning, neither of which is yet generally available. And on Tuesday, Tableau introduced tools for Salesforce CRM Analytics -- the CRM giant's sales analytics platform -- titled Text Clustering and Bias Detection, which are also still in the development stage.

Text Clustering uses machine learning models to extract keywords from text fields to reveal hidden insights, while Bias Detection automatically finds and removes machine learning biases so that users don't need to retrain entire models after discovering biases.

"[Data science] is an area poised for a different approach," Ajenstat said. "We believe that with all the turbulence in the world, it's not enough to just look backward at what happened. Getting better at predictions about what might happen and using machines to guide those predictions is something customers need right now."

He added that given the turbulence of the past few years -- including the pandemic, repeated supply chain disruptions, rising inflation and a war in Eastern Europe -- customers have been asking Tableau for more self-service data science capabilities.

Henschen, meanwhile, noted that the addition of more business science features represents a further progression of Tableau's assimilation into Salesforce. But with the tools not yet available, it isn't yet known quite what their capabilities will be.

In particular, Model Builder -- a tool to help teams build and deploy predictive models within Tableau workflows using Einstein Discovery -- has the potential to advance what Tableau users can do with predictive analytics within Tableau.

"On the business science front, the integration of Einstein capabilities continues," Henschen said. "Einstein Model Builder existed in the context of various Salesforce decision points, so I'll be curious to see how Model Builder has been generalized for the broad Tableau community. Predictive models and model accuracy depend so much on context of the decision-making and related data."