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Tableau CEO on AI moves to ease analytics adoption

Tableau’s head honcho Ryan Aytay talks up Tableau’s efforts to bring more consumerisation and personalisation capabilities to data analytics through the use of AI

When Salesforce veteran Ryan Aytay became CEO of Tableau about a year ago, he was tasked to lead an organisation that was growing faster than his parent company.

With data being the foundation of artificial intelligence (AI), which has been all the rage over the past 18 months, Tableau could grow even faster through more integrations with Salesforce.

Tableau is already on that trajectory, tapping Salesforce’s Einstein Copilot to help with data exploration and analytics, as well as the Salesforce Data Cloud to provide customers with a single source of truth from multiple data sources.

In an interview with Computer Weekly in Singapore, Aytay, who was Salesforce’s chief business officer, talks up what’s next for Tableau amid the generative AI (GenAI) wave, and what his team is doing to bring more consumerisation and personalisation capabilities to data analytics.

Talk to me about some of the recent developments at Tableau and where things are heading.

Ryan Aytay: From a business perspective, Salesforce continues to grow and its revenue is on track to reach roughly $38bn. Tableau contributes a big percentage of that with data and analytics continuing to be critical. Since we were acquired by Salesforce, we’ve more than doubled the business.

When Tableau was founded, it was more about moving people away from creating reports and dashboards towards self-service analytics, which was Tableau’s claim to fame. Today, whether it’s our Tableau embedded product, Tableau Pulse, or Tableau AI, which is powered by Salesforce’s Einstein Copilot, or Tableau Cloud, we’re trying to bring more consumerisation and personalisation capabilities to both Tableau and Salesforce customers.

While Tableau has always been about serving analysts and data professionals, we believe that it will be more about serving everyone within an organisation. The Tableau mission was always about helping people understand data in a way that an analyst could.

We all need data to do our jobs, but not all of us are analysts and we’re not building complex data visualisations. That’s why we started shipping tools like Pulse, which delivers data and insights to your email or wherever you work, in real-time. We started with cloud, but we’re going to bring that technology to our server and on-premise business too.

I think where we’re going with Tableau is to continue to solve problems for customers. The number one problem is how do we address the very fragmented data landscape that customers have? I just met with a very large customer here and they talked about having more than 750 different data warehouses. How do we help them solve that? We can do that now with the Salesforce Data Cloud, which is connected to Tableau and allows us to scale and leverage some of the capabilities we’ve announced recently.

For example, through our zero copy data alliance, you can harmonise your data with the Data Cloud. From there, we’ll move into providing trusted data insights, so the second pillar of what we’re building is a semantic layer that’s headless in some sense. It allows you to have a common business language for business users and analysts.

Pulse, for example, is included when you move to Tableau Cloud, so we're not trying to nickel-and-dime our customers. Our strategy is to make the product better and useful, so that you can adopt it across your business
Ryan Aytay, Tableau

The last pillar is the marketplace. When you build these great dashboards and do all the data preparation work, why can’t you put them in a marketplace internally in your company for others to access? No one has done this and we’re going to launch that at Dreamforce later in September.

That’s where we’re going with what I’d call the next wave of Tableau. All of that technology is built into the Salesforce core architecture and leverages the metadata in Salesforce. If you’re a Salesforce customer, you’ll get even more benefit from it, but Tableau will always be open and flexible for non-Salesforce customers as well.

For a while now, we’ve had predictive AI capabilities that generate predictions from the data we have. How do you see GenAI taking data analytics to the next level?

Aytay: No one knows has an answer to where things go from here. But if you look at history, we wouldn’t be having this conversation in March 2023. Things have changed in just about a year – we announced Pulse in May 2023 and shipped it in February 2024. And now, we’ve over 3,000 customers using it to glean data insights. Then, there’s Tableau AI, which helps you to not only build visualisations faster, but also perform calculations on your data and prep your data more quickly.

I think every improvement to GPT and Gemini influences consumer AI, but how we relate those improvements to business is every vendor’s challenge. How do we make sure it’s safe and trusted? How do we continue to augment data and analytics and make it easier for our customers to adopt? People worry about jobs going away, but the opportunity is that they can do a lot more with a lot less cost.

We’re fortunate that we’ve got this AI revolution and as we’re building the next generation of Tableau, it’s all coming together. There’s a big opportunity in conversational analytics in the future, where we could bring Slack and Tableau closer together, so I can mention a data source in Slack and ask questions about the data.

But we need to always remember that our customers need to be safeguarded and that’s why I think our approach to AI is slightly different, which is we want to make sure it’s trusted. You’re not sending your data outward. Your company data is not our product. You shouldn’t let your company data go into a LLM [large language model]. We want to mask it and make sure it’s safe so that you can trust it. I think it’s a nuanced environment, but we have to continue to keep learning every single day.

Where do you see the next big leap in helping data analysts with tasks like data preparation which currently takes up the majority of their time?

Aytay: You can already do this with our platform, but it’s probably not well known enough. Besides being able to use Tableau to look at structured data, you can also use it to look at unstructured data.

The benefit of being part of Salesforce is that we now have this deep integration with Salesforce Data Cloud which can pull data from any source, not just Salesforce data. We can look at unstructured data and visualise it, which is very unique in the market.

The ability to look at different text files from different sources and being able to form some kind output is very powerful. That’s one example of how we can help customers to do a lot more with the data they have.

We are open, flexible and we need to show up where our customers want us to be. Not many companies are telling you that they're going bring AI technology on-premise, but we're going to do it because our customers are asking for it
Ryan Aytay, Tableau

There’s also a big opportunity in providing a single source of truth. If you want to change the way you interact with customers, you need to have an understanding of all the data that sits outside of your CRM [customer relationship management] system. We’re also going to see more embedded use cases and that’s why Pulse is probably the most exciting thing I’ve ever been part of at Salesforce.

You talked about the integrations with Slack and Salesforce, but how are you prioritising product development and looking after Tableau customers that might not be Salesforce customers?

Aytay: Tableau has many customers that are not yet using Salesforce and that’s okay. They use Tableau for very different purposes. Maybe it’s a command centre at a bank that’s focused on financial metrics or a company doing people analytics. And so, Tableau has to be flexible, meaning we have different ways to deploy – on-premise, cloud and embedded. Other vendors may force you to move to certain things. Maybe you’re using a BI [business intelligence] tool, but all of a sudden you’re in their cloud platform because you’re forced to move in that direction. We’re not doing that.

We will integrate with Salesforce, Slack, Microsoft Teams, and all the hyperscalers. We are open, flexible and we need to show up where our customers want us to be. Not many companies are telling you that they’re going bring AI technology on-premise, but we’re going to do it because our customers are asking for it. When I think about prioritisation, it’s about what customers want. We’ve got many customers and these trips I make are for us to listen to what’s on their mind.

The other thing is also where and how fast the market is moving. I’d say in the current world, it’s exciting, but you also don’t know what’s around the corner. Our teams need to be very focused on listening, and partner with other companies like OpenAI and Google to know what’s happening.

Could you talk about your pricing strategy? One of the key findings from our research was that just 10% of organisations were willing to pay over a 10% premium for a product with GenAI capabilities. What are your thoughts around pricing Tableau’s GenAI capabilities so that they are accessible to customers?

Aytay: We want to make sure that we’re helping our customers get return on investment [ROI] for whatever it is they’re trying to analyse. Pulse, for example, is included when you move to Tableau Cloud, so we’re not trying to nickel-and-dime our customers. Our strategy is to make the product better and useful, so that you can adopt it across your business. We also have a usage-based model with our embedded product for companies such as banks that want to deploy Tableau for certain clients.

If there’s some situation where we have to have a different pricing model because that’s how the market looks at it, then we’ll consider that. I’d rather have a bundled strategy though, so customers can take advantage of all our technology. But our strategy hasn’t been to charge an extra $20 per user per month. We could, but we don’t think that’s the way customers want to use it.

When people use the product, they learn and experiment. With Tableau Public, which is all about our community, there are 9.5 million visualisations and four million authors. You can find visualisation templates and download them for free.

I spoke to someone at the University of Indonesia which is using Tableau and they want to do more. Once you’re in an enterprise and you’ve got an enterprise site licence, we’ll monetise that, of course, because it adds value to the customer, but we’re not going to nickel-and-dime.

Let’s talk about what you’re seeing in the Asia-Pacific region. From your conversations with customers here, what’s your sense of their readiness to leverage Tableau’s AI capabilities? There’s a general view that many companies are still in the early stages of data analytics and not quite ready to harness the full potential of AI.

Aytay: Globally, everyone wants to talk about AI, but there are varying levels of success. There’s a lot of experimentation and a lot of companies are selling their version of AI and it hasn’t worked. What we are trying to do is make sure that what we ship is delivering ROI.

In this region, we see a lot of energy in countries like Indonesia, where many people are trying to learn data skills, and of course, your data strategy is going to power your AI strategy over time. The younger generation is hungry to learn and companies are trying to find those people.

From a macro perspective, I don’t hear about the headwinds in this region that I’ve heard in other geographies. There’s less focus on the need to reduce costs and it’s more of how they want to grow and that this is an opportunity they need to seize right now. There’s definitely an appetite to go fast here, which is exciting.

That’s also why we’re investing in the region where we’ve recently announced Tableau on Hyperforce in Indonesia and Singapore. Most people want to move to cloud, but if we can provide the data residency and Salesforce’s level of security, reliability and elasticity, that helps people go along with us in a better way.

Read more about AI in APAC

  • DBS Bank’s AI Industrialisation Programme has been instrumental is industrialising the use of data and AI across its business, resulting in over S$370m of incremental economic benefits.
  • Alibaba’s SeaLLMs are built to address the linguistic diversity and nuances in Southeast Asia, enabling businesses to deploy localised chatbots and translation applications.
  • Malaysian startup Aerodyne is running its drone platform on AWS to expand its footprint globally and support a variety of use cases, from agriculture seeding to cellular tower maintenance.
  • The Australian government is experimenting with AI use cases in a safe environment while it figures out ways to harness the technology to benefit citizens and businesses.

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