The News:
Salesforce introduced on May 9 at its Tableau Conference the next generation of Tableau, the company’s data analytics and visualization solution, which is now powered by Einstein generative AI technology. According to the company, using Tableau GPT and Tableau Pulse, analysts and business users can automate data analysis, anticipate user needs, and automatically generate actionable insights simply by asking questions using conversational manner.
By using Generative AI to access Tableau content, smarter data experiences for analysts, consumers, administrators, and developers can be provided more efficiently across the organization. Through Tableau Pulse, which is powered by Tableau GPT, insights can be surfaced in both natural language and visual formats, and these insights can be integrated into collaboration tools such as Slack, enabling users to act on them in their usual flow of work. Furthermore, the company announced that Salesforce Data Cloud for Tableau capabilities will bring customer data directly into Tableau, unifying it in a single view for fast insights.
See the complete press release from Salesforce here.
Salesforce Introduces Generative AI-Enabled Version of Tableau
Analyst Take:
The latest version of Tableau has been infused with generative AI technology, and has been implemented to make it easier for all types of users to interact with data, regardless of their experience or expertise working with the software. Users can surface insights in a conversational way by simply asking questions within the console, and the data can be analyzed and presented without requiring significant experience or skill using Tableau.
For CX platforms and related applications that are designed to help organizations better understand and interact with their customers, generative AI has become a must-have capability. But the use of generative AI to fully unlock the power of data analysis and visualizations within Tableau may be a real game-changer that yields significant benefits very quickly.
An “Easy Button” for Accessing Data via Generative AI
Essentially, this new release seems to be an “easy button” that enables data laypersons to access and manipulate complex data without needing to go through extensive training on how to manipulate data within Tableau. The generative AI-powered conversational interface is also useful in accessing visuals that provide insights as to why certain events are occurring, based on trends in the data, alongside suggested solutions to address these issues. Often, the “why” is the key to unlocking true insights about interactions, customer groups, and general trends impacting a business.
Another capability that was announced that should make it easier to access data is Salesforce’s VizQL Data Service. VizQL Data Service is a layer that will sit on top of published data sources and existing models and allows developers to build composable data products with a simple programming interface, thereby removing the complexity of query construction and data modeling.
Democratizing Access to Data
From a workflow perspective, it is good to see that Tableau GPT supports integrations with collaboration tools such as Slack and email. The value of visualization tools revolves around the ability to ingest data, analyze it, and then share it with others, who may want to then find their own insights. Salesforce says that Data Cloud unifies the entire repository of a company’s customer data across channels and interactions into single, real-time customer profiles, and supports zero-copy data sharing, which means that users can virtualize Data Cloud data in other databases, making it instantly available to anyone.
Another tool that should help organizations democratize access to data and analytics is Instant Analytics, a new capability in Data Cloud for Tableau that allows users can analyze and visualize any Data Cloud data live inside Tableau and query millions of records with a single click.
Ultimately, benerative AI is likely to become embedded in many of the software and systems used for CX, sales, service, and support, because it makes it easier for agents and customers to interact using conversational language. The interesting thing about this use case for generative AI is that it allows workers to interact with data more easily, an often-overlooked challenge that many organizations face.
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
