More automation, embedded analytics part of Tableau plans

Tableau has plenty planned for its analytics platform.

This week, the vendor is taking part in Dreamforce, the annual user conference hosted by Salesforce, which acquired Tableau for $15.7 billion in 2019.

On Tuesday, the opening day of Dreamforce, Salesforce unveiled Genie, a new customer data platform designed to automatically bring all of an organization's Salesforce data together in one location and surface insights so that organizations can develop better knowledge about each customer.

In concert with the launch of Genie, Salesforce unveiled an integration between Tableau and the new customer data platform that aims to enable Tableau users to smoothly connect to their Salesforce data and analyze it.

Meanwhile, on Wednesday, Tableau will take center stage when chief product officer Francois Ajenstat helps deliver the analytics vendor's keynote address, during which Ajenstat and others will speak about Tableau's focus on decision intelligence,. automation and collaboration

Beyond Dreamforce, Tableau 2022.3 is scheduled to be released soon. Tableau, founded in 2003 and based in Seattle, updates it analytics platform four times each year, and following releases in March and June, the third release is imminent, according to Ajenstat.

Francois Ajenstat

In a recent interview, Ajenstat discussed all things Tableau, including taking part in Dreamforce with full in-person attendance for just the second time since Tableau became part of Salesforce.

In addition, he spoke about the vendor's latest integration with Salesforce, what Tableau has planned for its last two platform updates of 2022, the analytics trends currently influencing the vendor's product development roadmap and the rising trends he anticipates will guide future product development plans.

First, on a personal level, what do you expect from Dreamforce as an in-person event rather than virtual?

Francois Ajenstat: Dreamforce is happening, it's in person, it's going to be big.

When I think about what I was wishing when Tableau became part of Salesforce, it was about making customer data easier to use. If you can make that customer data easier to use, it unlocks new possibilities.

It's the first big Dreamforce since the COVID-19 pandemic, and from a Tableau perspective, Tableau's acquisition by Salesforce was three years ago, and Dreamforce in 2019 was that first moment when we were all together. For me, personally, it feels great because we are going to have a real Dreamforce. It's a celebration of community, and I'm really excited about that.

One of the big things coming out of Dreamforce is the introduction of Genie, including an integration between customer data from Genie and analytics from Tableau. What makes the integration significant for users?

Ajenstat: When I think about what I was wishing when Tableau became part of Salesforce, it was about making customer data easier to use. If you can make that customer data easier to use, it unlocks new possibilities. If you can truly create that single source of truth about a customer -- which has been out of reach and been the dream -- and if we can do that within Salesforce, that is going to be exciting.

This is the difference between just adding more capabilities and a transformation.

When Tableau delivers its keynote and analytics takes center stage, what will be the message?

Ajenstat: The headline is aligned to our vision, which is how to bring analytics everywhere, for everyone. It's about continuing to democratize analytics.

The Tableau keynote has three chapters. The first chapter is about our integration with Genie, which will unify and unlock data in Genie to create a single source of truth about customers. I think it's one of the biggest chapters in terms of impact.

Once you unlock the data, the second part is all about augmented intelligence to discover patterns and predict future outcomes. In that chapter, we're going to talk about new enhancements to Einstein Discovery, how to go about decision optimization, bringing Data Stories that we have in Tableau to CRM Analytics so people can get predictive insights there. We're adding live predictions for Snowflake, so if you have your data there and your data is not in Genie, you'll still be able to get predictive insights for Einstein. Decision intelligence is that second theme.

And what will the third chapter cover?

Ajenstat: The third is all about collaboration and automation. It addresses how people work together, because at the end of the day, data is a team sport. We want to put data at the center of every conversation and every process, so there, we're going to talk about Tableau External Actions, which is something we showed at Tableau Conference. It's all about going from insight to action and being able to trigger a business process as a result of an insight. That could be escalating a case in Service Cloud. It could be creating a purchase order in SAP. We're also going to be continuing our collaboration with Slack and how you can infuse insights from Tableau and CRM Analytics.

After Dreamforce, Tableau's next platform update is due soon -- what are some of the new analytics capabilities users can expect when Tableau 2022.3 is released?

Ajenstat: Both 2022.3 and 2022.4 are around the corner. External Actions will be coming out in one of those two releases. We'll be continuing to enhance Data Stories, which we launched in March, so you can continue to write stories on more things. More accelerators, which are pre-built dashboards, are coming. We have a big push around embedded analytics so you can infuse Tableau in other applications, which is really important and brings the self-service aspect of Tableau to the embedded world. There's also a lot of work on the cloud and compliance capabilities.

As Tableau continues to add new capabilities, what are some analytics trends that are influencing development?

Ajenstat: One of the big trends we see is the continuing challenges around data literacy and adoption. With all the successes that we've had at Tableau, analyst firms still show that analytics adoption is below 30%. That continues to be a huge challenge for our customers, which is why our investments in things like Data Stories, collaboration and making decisions actionable have all been aimed at bringing insights into the flow of work to make data easy and relevant. That's a trend you can see connected to the innovation.

Another big trend is the rise of the modern data cloud. You can look at Snowflake as the prime example, but we're seeing a ton of innovation around cloud data, and we're seeing an acceleration in customers wanting to move to the cloud. It's funny to say 'cloud' today because it feels like an old trend, but from a data standpoint, it's shifting. The cloud used to be for some use cases, and now it's becoming the main use case. You can see it with Snowflake's results, and with vendors like Teradata. Google is doing really well with its cloud platform.

Any other trends you want to mention?

Ajenstat: A third trend we're watching very closely is around how IT is taking a bigger role in governance. It's not just governance being a theme, but IT teams trying to rationalize their investments and make sure they can provide governance with self-service. Now, we're seeing IT playing a larger role in that governance layer.

A last trend is the result of the pandemic. The way people work has changed, and their expectation of technology has changed. People's expectation for technology and work is different than it was three years ago, and we have to think about what that means for analytics. We can't deliver analytics the same way we did five years ago. In this world of work, we have to think about what it means to deliver relevant, contextual insights.

Beyond current analytics trends, what are some future trends that will likely influence the Tableau roadmap?

Ajenstat: One is that the idea of the digital headquarters -- the future world of work -- is making us all re-imagine what the future should be. I think we're just coming into that. Some people are trying to go back to the old world, but I think there's a fundamental change taking place that will play out over a period of time.

The other is this idea of augmentation and automation. In the BI space, we have been living in a world of augmentation over the last few years, with AI to help people discover insights. That's not going away. But I think automation is becoming a more critical capability -- do more things on my behalf, more analysis on my behalf, and bring that forward. It's like how people used to walk around beaches with metal detectors to try to discover gold. Now, the machines can automatically find where there might be gold and send a robot to sift through it, so you can then decide what to do once it's found. It's not augmentation versus automation, but seeing how they go hand in hand.

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