Tableau GPT

The Six Five team discusses Tableau GPT.

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Patrick Moorhead: Tableau GPT, Tableau owned by Salesforce.

Daniel Newman: I always feel like we could have consolidated this to Slack and Tableau into one, but I guess, each deserves their own moment here.

Patrick Moorhead: No, this is exactly what they would’ve wanted, right? Different brands, different sub-companies, different CEOs, right?

Daniel Newman: Yeah, I’m just saying though.

Patrick Moorhead: I got you, bro.

Daniel Newman: So I’m going to make this kind of brief here. So Tableau on the other end… So Slack is more that user interface every day. Well, Tableau is kind of that decision driving engine of a company. If you’re a CEO, Tableau is that visualization, that dashboard insights that you would need to run your company, run your business unit, run your sales team in a very concise way. So I guess, the company is now – just like we’ve been talking about with Microsoft – looking across their portfolio and all the different products. So sales, the data with Tableau, Slack with chat, and they’re basically looking to say, how do we make GPT and OpenAI capabilities enable companies to make better decisions? And the bottom line is that, that is the number one is that over 80% of IT leaders believe that generative AI’s biggest opportunity is to make help organizations make better use of data.

I’ll file that under duh, kind of obvious. But at the same time, what what’s going on is companies have these vast data ecosystems and how do you utilize that technology in something like a GPT, something like a generative to say we’re going to pull from all the data sources in a very comprehensive way using natural language to query, to get visualization of what you need to know in a really short order. That’s really what Tableau GPT is going to enable. It’s going to enable faster decision, more personalized analytics. It’s going to basically give more capabilities for decision makers to get the dashboard they want. So if you’re building Tableau, historically, you needed kind of a developer or at least someone that understood low code to a good extent to develop a dashboard for you. But when you wanted to basically get any inquiry or insight that was not part of your dashboard, it was really hard.

So think about being able to query your business analytics system the way we are querying a Bard or ChatGPT or Bing with generative to say, “Hey, I want to know how many refrigerators we sold in the UK between January and March of this year.” So while you may have had a dashboard that was full year to date, you just wanted to see three months and then you wanted to see it by a salesperson. Or then you wanted to see it by a region or by a certain retailer store or, or, or…the ability to use NLP natural language generative to get those dashboards updated in real time is huge for executive decision making. It goes back to what I said about Benioff saying you’re going to have Einstein in the boardroom.

This is that kind of insight with analytics, with data visualization that becomes the genius in the boardroom that can instantaneously get you those numbers. If you ask anyone on our team at Futurum, I ask these kinds of questions all the time. How much did we sell year to date to this customer versus how much have we sold this year to date? These are things that are buried in your CRM. It’s never been impossible to get, Pat, it’s just been really a big pain in the rear end to be able to pull it up and it ends up taking time from someone that could be doing something else and now they can be doing this.

Patrick Moorhead: That was a great breakdown, Dan. So a couple of things here. This Tableau GPT is based on Einstein GPT technology as you would expect. A little bit confusing, having different names across different products. My guess is, or my hope is that if you have customers that are using the entire Salesforce Suite, I don’t think you want different. You don’t want Slack GPT, Tableau GPT, Einstein GPT. I don’t like that move, but that’s branding. And I think it got us to talk about, like we’ve talked about Salesforce flavors of GPT three times now. So mission accomplished, marketing folks. One thing that I wanted to point out too is this is not pulling data from the internet. This is not pulling data that has been trained publicly, this is information coming directly from your enterprise.

So anything that’s in Salesforce Customer 360, it gets access to that. Any place that you had previously pointed Tableau to pull this in, it will work across all of those platforms. And I said on Slack GPT, this was kind of what it was made for. If you look at what GPT is adding to it, it’s making Tableau better. When Tableau first came out, essentially it was intelligently through analytics technologies, being able to… You could script different queries to make it easier. It did have the ability to ask questions, but what came back based on analytics and machine learning wasn’t all the best. So this is supersizing it, I haven’t used this, I’ve seen some videos on it, but should lead to better answers more quickly. And at the end of the day, that’s what a tool like Tableau is made for, is to pull in the best data when you need it and keep people like Daniel Newman, if you have to work for him, very happy.

Daniel Newman: Sorry about that.

Patrick Moorhead: Nothing at all. I mean, whether you’re Daniel Newman or a PC company that wants to know how many notebooks and the revenue acceleration and profitability in Malaysia in the third quarter, you should get that information as opposed to having to go out to an analyst who has a giant spreadsheet, has to put together some data and pull it in. So I like it, very consistent with some of the data plays that we’ve seen from the other folks, whether it’s BI or some stuff from Oracle.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.


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