Tableau launches generative AI assistant, updates platform
The longtime analytics vendor made a Copilot for data preparation generally available with similar tools for data cataloging and dashboard development and analysis expected soon.
Tableau's first generative AI assistant is now generally available.
Tableau earlier this month launched its second platform update of 2024, which included revealing that the first two of its GenAI assistants will be generally available before the end of July and a third will be released in August.
The first of those -- Einstein Copilot for Tableau Prep -- became generally available on July 10.
The vendor first revealed plans to develop generative AI capabilities in May 2023 when it unveiled Tableau Pulse and Tableau GPT.
Pulse, an insight generator that automatically monitors data for metric changes and uses natural language to alert users, became generally available in February. Tableau GPT, meanwhile, was renamed Einstein Copilot for Tableau and moved into beta testing in April.
Now, Tableau is rolling out its Copilots. Following Einstein Copilot for Tableau Prep, Einstein Copilot for Tableau Catalog is expected to be generally available before the end of July. Einstein Copilot for Tableau Web Authoring is set to follow by the end of August.
With the launch of generative AI assistants that will enable customers to use natural language to prepare and analyze data, Tableau joins data management and analytics vendors such as AWS, Domo, Microsoft and MicroStrategy that have already made generative AI assistants generally available.
Numerous others, including Qlik, data engineering specialist DBT Labs and data preparation vendor Alteryx, have unveiled plans to develop similar assistants but have not yet moved them out of preview.
Beyond keeping pace with its rivals in releasing generative AI tools, Tableau's generative AI capabilities are largely in step with those being developed by other vendors, according to Doug Henschen, an analyst at Constellation Research. And in some ways, Tableau's generative AI capabilities, which extend to data cataloguing, go beyond what other analytics specialists are providing.
"Tableau is going [generally available] later than some of its competitors. But capabilities are pretty much in line with or more extensive than what you're seeing from others," Henschen said.
Beyond revealing that its generative AI assistants are about to be released, Tableau 2024.2 includes such features as making Pulse embeddable in applications.
Based in Seattle and a subsidiary of CRM giant Salesforce, Tableau is a longtime analytics vendor. Tableau's first 2024 platform update was highlighted by the launch of Pulse while its final 2023 update featured new embedded analytics capabilities.
Enterprises might receive these seven benefits when using generative AI.
Tableau's latest
Generative AI assistants are proliferating because of their potential to enable non-technical workers within enterprises to work with data and enable data experts to be more efficient.
Largely due to the complexity of analytics platforms, which require coding to carry out most tasks and data literacy training to interpret data, analytics growth within organizations has long been stagnant. Studies show that only about one-quarter of all employees regularly work with data.
Vendors have attempted to break through that barrier by simplifying the use of their tools with natural language processing (NLP) and low-code/no-code features. The NLP features, however, are limited by small vocabularies that require highly specific business phrasing while low-code/no-code features are limited because they only enable basic tasks.
As a result, little progress has been made toward more widespread use of analytics, which has been shown to lead to growth better than decisions made without the use of data.
Generative AI has the potential to change that. Large language models such as ChatGPT and Google Gemini have vocabularies as large as any dictionary. In addition, they can interpret intent. As a result, they enable the true natural language interactions that open data exploration and analysis for non-technical users as well as reduce time-consuming coding requirements for data experts.
Tech giants AWS, Google and Microsoft have all invested heavily in generative AI as have specialists such as Tableau and its peers. And following the better part of a year when many vendors unveiled plans to develop generative AI capabilities but did not make them generally available, now a wave of tools are hitting the market.
Those that are now generally available are having their desired effect, according to Henschen.
"In almost all cases, I'm seeing improved productivity for existing users and a marginal broadening of usability for business users," he said.
Now generally available, Einstein Copilot for Tableau Prep enables customers to describe calculations in natural language, which the tool interprets and replies to with a calculation that can be applied to a user's data to add calculated fields to their Tableau Prep flows.
Before the launch of the generative AI assistant, creating formulas for calculated fields in Tableau Prep required expertise in objects, fields, functions and limitations that could only be carried out by those with significant training.
Once released later this month, Einstein Copilot for Tableau Catalog will enable users to add descriptions for data sources, workbooks and tables with one click. A Draft for Me button instructs the tool to generate a description of a data asset, which can then be reviewed by the user to edit and then publish to help make data more easily discoverable in Tableau's data catalog.
In August, Einstein Copilot for Tableau Web Authoring will enable users to explore data in natural language directly from Tableau Cloud Web Authoring. The tool will interpret instructions to produce visualizations, formulate calculations and suggest recommended follow-up questions to enable deeper data exploration.
Tableau is going GA later than some of its competitors. But capabilities are pretty much in line with or more extensive than what you're seeing from others.
Doug HenschenAnalyst, Constellation Research
Given the reduction in coding the Copilots enable, Tableau's generative AI assistants will "absolutely" serve their intended purpose of making experts more efficient and enabling more people withing organizations to work with data, according to Mike Leone, an analyst at TechTarget's Enterprise Strategy Group.
"Whether for an expert or someone just getting started, the goal of Einstein Copilot is to boost efficiency and productivity," he said.
For example, data experts can now streamline complex data modeling and predictive analysis or automate routine data prep tasks. Generalists can engage with user-friendly interfaces to visualize and analyze.
Of particular benefit is that Tableau is planning to provide generative AI assistants for different parts of its overall platform, Leone continued.
"One of the pieces I like about Einstein Copilot is the unique value it can provide in clear delineation stages of the data and AI lifecycle with Prep, Catalog and Web Authoring," he said. "And it enables Tableau to continue expanding into other areas based on customer feedback and adoption."
Henschen, meanwhile, noted that the generative AI assistants for Tableau Web Authoring and Tableau Prep are relatively similar to the generative AI assistants being introduced by other analytics vendors.
However, adding a generative AI assistant for data cataloguing represents some differentiation among analytics specialists.
"Einstein Copilot for Tableau Catalog is unique to Tableau among analytics and BI vendors" Henschen said. "But it's similar to GenAI implementations being done by a few data catalog vendors."
In addition to the generative AI assistants, Tableau's latest platform update includes the following:
Embedding for Pulse, a web component that enables developers to embed Pulse in the work applications where business users do their work so they don't have to toggle between those applications and the Tableau environment to get generative AI-powered insights.
Multi-Fact relationships, a feature that lets users relate disparate datasets that have shared dimensions such as time or geography to perform multi-fact analysis. It includes guidance and tips to help users work with underlying data models.
Viz Extensions, a tool that enables customers to develop their own data visualization type and add it to their visualization library.
The addition of Tableau to Apple devices, including two Mac options.
Subrange Extract Refreshes, a tool that allows users to refresh data for small subsets within a larger dataset to reduce the cost of keeping relevant data current.
Data Connect to help data engineers and administrators move on-premises or private cloud data into Tableau Cloud using Tableau Bridge.
Among the non-Copilot capabilities, making Pulse embeddable is perhaps the most significant, according to Henschen. Most generative AI capabilities still require customers to use them in a vendor's environment, he noted. Extending them to work applications will make them more effective.
"I'm excited to see the new Embedding for Pulse option being introduced in the 2024.2 update," Henschen said. "The ability to embed Pulse insights within the day-to-day applications promises to open up new possibilities for making insights actionable for business users."
Also noteworthy is multi-fact relationships, according to Leone.
By enabling users to relate datasets that have shared dimensions, they can use larger volumes of data to inform applications, including traditional AI and generative AI models that require large amounts of high quality data to minimize AI hallucinations and be accurate.
"Multi-fact relationships are a fascinating area where Tableau is really just getting started," Leone said. "As businesses seek to build trust in GenAI and reduce hallucinations, providing ways to improve accuracy, insights, and context goes a long way."
A price to pay
While Tableau has now launched its first generative AI assistant and two more will be made generally available in a matter of weeks, the vendor has not yet revealed prices for using the Copilots and other related features.
The generative AI assistants are only available through a bundle named Tableau+, which the vendor calls a premium Tableau Cloud offering. It was introduced in a blog post in June.
Beyond the generative AI assistants, Tableau+ includes Data Connect, advanced management capabilities, simplified data governance and data discovery features, and integration with Salesforce Data Cloud, among other features.
Generative AI requires significant compute power and is costly, Henschen noted. As a result, it's not surprising that Tableau customers will have to pay extra to use the generative AI assistants.
Microsoft, like Tableau, hasn't yet made public the cost of using its Power BI Copilot, while AWS charges extra for Amazon Q capabilities in QuickSight, Henschen continued. Some others, meanwhile, are offering generative AI capabilities for free -- for now -- to try to attract new users.
"Customers will want to understand the cost implications of adding these new capabilities," Henschen said. "The reality is that GenAI is compute-intensive. I have no doubt that customers will have to pay for these capabilities sooner or later in one way or another. At this point, cost picture and, certainly, the cost versus value picture with GenAI features just isn't clear. ... Time will tell."
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
