Data storytelling, cloud in focus at Tableau Conference '22

Data storytelling and cloud capabilities will upfront at this year's Tableau Conference.

Tableau, founded in 2003 and based in Seattle, acquired data storytelling vendor Narrative Science in late 2021. And when Tableau hosts its annual user conference in person for the first time since 2019, among the new capabilities it plans to introduce are those related to its acquisition of Narrative Science, according to chief product officer Francois Ajenstat.

Meanwhile, in the years since Tableau last gathered its customer base in person, as worldwide events including the COVID-19 pandemic and war in Ukraine have affected the global economy, speed-to-insight has become paramount for organizations needing to navigate fast-changing conditions, and nowhere is the speed of analytics faster than in the cloud.

Therefore, since 2019, Tableau -- like other vendors including MicroStrategy, Qlik and ThoughtSpot -- has made developing cloud-first capabilities a priority, and new ones will be on display at Tableau Conference, according to Ajenstat.

A third theme, he noted, will be business science, a concept Tableau introduced during its virtual user conference in 2021 and is essentially self-service data science.

Recently, Ajenstat took time to preview Tableau Conference.

In addition, he spoke about the excitement around holding an in-person event for the first time since 2019, Tableau's platform evolution since the last time the vendor assembled its community together, plans for the future and the major trends not only influencing Tableau's product development but also those affecting the entire analytics market.

How does it feel to be holding Tableau Conference in person for the first time since 2019 after hosting virtual events the past two years?

Francois Ajenstat

Francois Ajenstat: I've missed it, and I can't wait for the community to all be together. There's always been something special about Tableau Conference. It's more than just another technology conference -- it's a reunion. It's almost a celebration, and sometimes people describe it as a rock concert. I think everyone who has ever come to a Tableau Conference has said it's unlike anything else out there, and that's something you can't replicate in a virtual world. Being together, with the data family, with our data rock stars, is going to be amazing.

I have, over the last few months as the world has been opening up, been lucky enough to be able to travel, meet with customers and be able to do some live events like Salesforce TrailblazerDX a few weeks ago and Salesforce World Tour in Paris, and the enthusiasm and energy around Tableau has never been higher. When we get to the conference, it's going to feel so great to have that with thousands of people together.

When Tableau last held its user conference in person, it was so long ago that Salesforce had just closed on its acquisition of Tableau the week before -- how has Tableau's platform evolved in the time since the community was last together?

Ajenstat: It has evolved significantly.

If you look at how much has happened in those two-and-a-half years, first the externalities -- we got acquired, there was a pandemic, a social justice movement, a leadership crisis around the world, a supply-chain crisis, inflation, the war in Ukraine -- a lot has happened in a short amount of time all around us. But what has been constant in that time is our focus on innovation, and our focus on our mission of helping people see and understand data. So with everything that's been happening around us, we've still shipped new versions of Tableau every quarter with significant new capabilities in that time, and that's in addition to the integrations we've developed with Salesforce.

What are some highlights?

Ajenstat: The cloud, for Tableau in 2019 compared to today, is almost night and day. The cloud is now the predominant way customers deploy Tableau, and that wasn't the case pre-pandemic. We've seen that accelerated dramatically, and now Tableau's cloud version has become our flagship offering. Since 2019, we've introduced new capabilities powered by Salesforce, mainly the Einstein Discovery for Tableau that brings predictive analytics to Tableau -- that was one of the first things [from Salesforce] we brought into the fold. There are also Slack capabilities, which we had planned even before Salesforce acquired Slack, and we've introduced things like our accelerators, which are prebuilt dashboard templates that accelerate time-to-value. There are over 100 accelerators now that are integrated in the product.

There is much more for our core data family, for data analysts, for the enterprise and for new use cases that we didn't support back in 2019.

What can you divulge about new capabilities that will be unveiled at Tableau Conference?

Ajenstat: The overall framing is that this is the era for data. There is more data everywhere, and companies are becoming data companies. We've seen time and time again that data-driven companies are more successful companies than those that aren't. The fundamental challenge that we keep seeing and hearing over and over again is that data still hasn't reached most people. Whether you look at Gartner or Forrester or someone else, study after study shows that less than 30% of people have access to data. Tableau has always been about how to bring data to the people and make it easy and accessible and reach the many. The opportunity is to take analytics out of the realm of the analysts and bring it to the realm of everybody.

If you can make data approachable where people don't have to talk data and can just talk normally, all of a sudden the data literacy barriers go down and the usefulness goes up. That's one of the big pillars planned for Tableau Conference.

This is what we've been working on for years, trying to make it easier and more approachable. Last fall, we talked about Slack-first analytics and putting analytics where people work, which is an incredible way of breaking barriers, but visualizations -- even though people can see data more effectively -- are still intimidating for a lot of people. So the challenge is to make data speak the language of people and be natural. This is where our acquisition of Narrative Science comes in. It converts the visual into understandable human text -- it's natural -- and that's a really important thing. If you can make data approachable where people don't have to talk data and can just talk normally, all of a sudden the data literacy barriers go down and the usefulness goes up. That's one of the big pillars planned for Tableau Conference.

What are some others?

Ajenstat: A second is this pattern we saw over and over that data was for the few, and Tableau helped make it accessible to the many. But what we see now is that pattern repeating with [augmented intelligence] and data science where those tools are for data scientists -- you need to know code and it's complex and it's expensive and it's time-consuming. The challenge for us now is to do with data science what we did with data, which is democratize it and bring it to more people -- make it easy, interactive and visual. That's a big topic for us. At Tableau Conference last year we introduced the concept of business science, and now we're adding capabilities.

And a third is time-to-value, and this is where Tableau's cloud version and accelerators come in. People don't want to manage infrastructure. They want instant analytics. They want their analytics to be available, scalable and secure right away because time is now so critical, especially with everything going on around us. Tableau's cloud version is on instantly, and with the accelerators there's value in minutes instead of days or months. And they're secure so IT departments can get the governance they need and the users get the empowerment they desire.

Looking beyond this year's conference, what does Tableau have planned for product development?

Ajenstat: First is the continuation of the idea of democratization. We're trying to democratize analytics and make it easier for more people, and we're trying to democratize data science and make that easier. We're also trying to democratize data management and make it accessible to business users -- that was a theme over the last few years and we've seen lots of success in that area. You'll see us emphasize making analytics fast and making it accessible -- that's a huge theme.

A second theme, which people won't see as a major theme at Tableau Conference but was a theme at Salesforce TrailblazerDX, is that in order to reach the majority of people, rather than make them go to the data, we need to bring the data to them. We need to infuse the data where they work, and make it actionable. The whole idea of embedded analytics is one you'll see Tableau enable more and more. When people think about embedded analytics, they think about embedding visuals in applications, but what we're going to be trying to do is embed insights and answers so people can get their questions answered anywhere.

When we spoke before Tableau Conference in fall 2021 you said Tableau's integration with Salesforce was still in its 'early innings' -- where would you say the integration is now?

Ajenstat: I think we're still pretty early.

Since the last conference, a number of things have come to fruition. One is the accelerators, which are out-of-the-box accelerators that are turnkey. For example, if you have Salesforce Net Zero Cloud, there are accelerators for Nonprofit Cloud and Service Cloud, and if you get one of those, that Salesforce data comes alive. We've added the action framework so users can orchestrate workflows though Salesforce Flow -- that's brand new and was announced at TrailblazerDX. And we're continuing to integrate more with CRM Analytics so there's a full continuum from inside the workflow in Salesforce to full exploration.

Finally, looking beyond just Tableau to the analytics market at large, what are some trends driving innovation?

Ajenstat: I'll break down and look at it through two lenses, one a technology lens and the second more of a macro business lens.

Ok, let's start with the technology lens -- what are some technological trends?

From a technology perspective, there's a new data ecosystem that's being built. When you think about Snowflake or emerging data vendors like Starburst, Dremio or Databricks ushering in a new data landscape along with new tools like DBT Labs and Astronomer, there's a new data ecosystem that's out there. It's exciting because it's transforming how companies are deploying data. And what Tableau will continue to do is bring that [ecosystem] to the people. A lot of the new tools are very technical, but as the data landscape is being reshaped, it's also reshaping the analytics ecosystem, and that works well with [vendors that enable] choice and possibility.

In addition, though AI is no longer groundbreaking, it's still early. It's still very immature, and it hasn't really gotten broad adoption. I think we're in what I'd call the trough of disillusionment with AI if you think about a graph, and I think we're about to get this leapfrog applicability where it will soon be available everywhere and it will start spreading and getting wider adoption. A third thing is that although cloud doesn't seem like a new concept, cloud is changing a lot of the dynamics about how people expect software to always on, always available and always secure. There's a sea change that's happening where not only software is SaaS, but the infrastructure you plug into is becoming more composable -- it's more of a mesh or fabric -- as a result of being cloud.

And what is a macro business trend?

Ajenstat: With everything going on in the world, we need to help people lower costs and be more agile. Think about the supply chain crisis. You need agility more than ever. Through the pandemic, growth has been a focus, but there also needs to be a focus on cost savings, efficiencies and scale. That's becoming way more important. In addition, ethical AI is really critical because there is a broadening set of concerns about how data is being used, such as compliance and privacy concerns around the world that are hyper-relevant to the data space.

Editor's note: This Q&A has been edited for clarity and conciseness.