Elif, a Tableau product leader, explains agentic analytics as AI agents working alongside users to turn data into insights. A Slack bot delivers daily sales briefings and answers follow-up questions using Tableau's forecasts and data. Tableau Next combines a knowledge graph with decision-making capabilities, keeping humans central to the process.
What does agentic analytics mean? Would love to hear that from your perspective with the team you're leading right now.
Yeah, so agentic analytics is a new and transformative way of doing analytics where analytics move from being a passive system and it becomes an active system where intelligent agent works with the user in a collaborative manner to turn the data into insights and to take actions. There's also one thing that I want to highlight, Ed. Last year we have been seeing a lot of conversational analytics and what we have done with Tableau Platform in the last couple months is to really go beyond the conversational analytics. It's about telling the agent your objective and the agent is understanding the context and understanding like the intent, knowing the business meaning and to be really able to kind of come up with suggestions to take action. So it's a paradigm change even for the agent analytics.
Yeah, so much has changed in such a short time. Your team's been working incredibly hard. Walk us through a real example of this agentic analytics experience? Let's make it kind of, how would this impact the viewers online right now?
Yeah, so maybe a good example is, let's say you're a sales leader and our sales leaders, they live and breathe in Slack. So I'm going to use Slack as an example. So one thing with Tableau is our platform to reach the user where they live, like where they do the work. So as a sales leader, I can just on the Slack bot, tell the Slack bot, to create a daily sales brief every day at 6, 7 AM. And the Slackbot is not only going to, by leveraging Tableau platform into NCP, find all the forecasts, you know, all of the risk, and also look at all of the conversations and threads that's happening on Slack. It has access to all of the structured, unstructured data and all of the documents. And then it's just going to give me a great brief to start my day. And then I can have further conversation to ask questions to Slackbot. It's just a great way of working. Again, coming back, the agent knows my objective, and then every day it's just there to help me.
And what differentiates, I guess, Tableau Next versus other analytical platforms that are working within Slack as well? I know your team has deep partnership with the Slack team here at Salesforce, but what's your perspective there?
Yeah, so number one, I would say just like having the context and the business meaning. I mean, for Tableau, like we have, thousands of customers running their business with Tableau today.
Yeah.
So, and Tableau has all of the business logic. This is how they are making decisions. So just being able to tap to that knowledge, and we are also building like a knowledge graph that combines that knowledge with the other data sources and the metadata that they may have in other sources. And combining that with the power of Slack and Slackbot is just a unique recipe. And as you said, like literally our software engineers are sitting together. Sitting together. And that's kind of like an advantage that nobody can beat.
I think what I love about it is, we talked about in the keynote, it's the knowledge engine, the decision engine. This is really bringing both of those together. In the conversations I'm having with individuals who have a career in analysis, there's a little bit of trepidation and fear in terms of what this means for them. What's your advice? You've been in the space for a long time. What should they do? How should they think about this?
Yeah, so like I'm having this conversation with Data Fam here as well. Like it's not about like having a fear, it's just not knowing how to work with the agent and this agentic world. And that was like number one thing as we were designing as product team, because we are Tableau, we put the user, the human at the center of everything that we do. So we build this amazing experience where like as an analyst, you can actually work with the agent, but we are providing a, spectrum of working styles. So you can still be in the control and do everything manually. But if you choose to work with the agent, your digital teammate is always there. It knows the context. And the other thing that I would like to highlight, Ed, you know, we have invented the cycle of visual analytics. Like, this is what the analysts love. Like, they have a hypothesis, they have a business question, and they find the data, they massage the data, they visualize it, they see a pattern, they go back to the data prep and then come, and then they communicate, broadcast that finding, right? And we We wanted to keep that core in this new experience, and I highly suggest everyone to get their hands on. It's amazing. Like, we took that cycle of visual analytics as our north star and rethink that, how we can help the business analyst even more in the agentic area. I'm super excited about that.
I think what I love, and we've known each other now, this is our second Tableau conference, your second Tableau conference, your energy, your excitement, how you're leading this team, and you can sense it across every part of the organization. To be a little bit more tangible, Hey, I'm dipping into Tableau Next. There's a lot of areas that I can kind of study and become better at. Where would you start if you're an analyst and you're new to maybe Salesforce, the Tableau Next experience? Where do they begin?
Yeah, use the power of the platform. And I'm keeping saying platform. It's not about like cloud, server, desktop, or NAS. It's the platform. And this platform has the business meaning with the context. We have an amazing semantic layer. That combines the PDS and the semantic layers as well. And then on top, just use the power of the MCP because I really think, Ed, like the line between BI and AI is blurring.
Yeah.
So today we have Cloud, we have Slackbot, and tomorrow there will be other AI clients. And we have Tableau Agent. We still have amazing builders and the experiences that we have in the product. So again, use the power of the platform. Just enjoy the white coding as well. It's amazing what you can do. And I really think that we are the platform for the agentic area.
What's the most interesting use case you've seen thus far in your role with, you know, the conversations you're having with customers around, around these types of use cases?
It's just amazing to see how they start using data and the insights, like, to reach to more users with the agents. I would say that our, like, a new set of users is the agents. Like, with Agentforce, I have many customers that they started their journey with Agentforce. They have sales agent, they have service agent, and those agents need Analytics skills. And that's where the Tableau platform comes in place. And we have many success stories. It's just great to see the engagement with the customers.
So this is your second Tableau Conference. If you could provide just one quick tip for the Data Fam, I'm motivated, I'm excited, this was the best conference ever, and then I got to go ahead and take action. What's your recommendation to the team that's listening in right now?
I think just again, like, learn what the platform now offers. Like, we have so much innovation on the Tableau Cloud. We have innovations on Tableau Server in Tableau Next. And Tableau Desktop is free now. Just go wild. Like, you have done this before for 20 years now. This is time to do that with Agentic Analytics.
Elif, I'm so grateful to have this conversation with you right now. You are rocking it. Keep leading the team. Thank you so much for being here with us.
Thank you so much, Ed.
Thank you. To learn more about Tableau Next and Agentic Analytics, scan the QR code on your screen or visit tableau.com/agenticanalytics.
