Tableau analytics platform upgrades driven by user needs

LAS VEGAS -- Tableau revealed a host of additions and upgrades to the Tableau analytics platform in the days both before and during Tableau Conference 2019.

Less than a week before its annual user conference, the vendor released Tableau 2019.4, a scheduled update of the Tableau analytics platform. And during the conference, Tableau unveiled not only new products and updates to existing ones, but also an enhanced partnership with Amazon Web Services to help users move to the cloud and a new partner network.

Many of the additions to the Tableau analytics platform have to do with data management, an area Tableau only recently began to explore. Among them are Tableau Catalog and Prep Conductor.

Others, meanwhile, are centered on augmented analytics, including Ask Data and Explain Data.

All of these enhancements to the Tableau analytics platform come in the wake of the news last June that Tableau was acquired by Salesforce, a deal that closed on Aug. 1 but was held up until just last week by a regulatory review in the United Kingdom looking at what effect the combination of the two companies would have on competition.

In a two-part Q&A, Andrew Beers, Tableau's chief technology officer, discussed the new and enhanced products in the Tableau analytics platform as well as how Tableau and Salesforce will work together.

Part I focuses on data management and AI products in the Tableau analytics platform, while Part II centers on the relationship between Salesforce and Tableau.

Data management has been a theme of new products and upgrades to the Tableau analytics platform -- what led Tableau in that direction?

Andrew Beers

Andrew Beers: We've been about self-service analysis for a long time. Early themes out of the Tableau product line were putting the right tools in the hands of the people that were in the business that had the data and had the questions, and didn't need someone standing between them and getting the answers to those questions. As that started to become really successful, then you had what happens in every self-service culture -- dealing with all of this content that's out there, all of this data that's out there. We helped by introducing a prep product. But then you had people that were generating dashboards, generating data sets, and then we said, 'To stick to our belief in self-service we've got to do something in the data management space, so what would a user-facing prep solution look like, an operationalization solution look like, a catalog solution look like?' And that's what started our thinking about all these various capabilities.

Along those lines, what's the roadmap for the next few years?

Beers: We always have things that are in the works. We are at the beginning of several efforts -- Tableau Prep is a baby product that's a year and a half old. Conductor is just a couple of releases old. You're going to see a lot of upgrades to those products and along those themes -- how do you make prep easier and more approachable, how do you give your business the insight into the data and how it is being used, and how do you manage it? That's tooling we haven't built out that far yet. Once you have all of this knowledge and you've given people insights, which is a key ingredient in governance along with how to manage it in a self-service way, you'll start to see the Catalog product grow into ideas like that.

Are these products something customers asked for, or are they products Tableau decided to develop on its own?

Beers: It's always a combination. From the beginning we've listened to what our customers are saying. Sometimes they're saying, 'I want something that looks like this,' but often they're telling us, 'Here is the kind of problem we're facing, and here are the challenges we're facing in our organization,' and when you start to hear similar stories enough you generalize that the customers really need something in this space. And this is really how all of our product invention happens. It's by listening to the intent behind what the customer is saying and then inventing the products or the new capabilities that will take the customer in a direction we think they need to go.

Shifting from data management to augmented intelligence, that's been a theme of another set of products. Where did the motivation come from to infuse more natural language processing and machine learning into the Tableau analytics platform?

Beers: It's a similar story here, just listening to customers and hearing them wanting to take the insights that their more analyst-style users got from Tableau to a larger part of the organization, which always leads you down the path of trying to figure out how to add more intelligence into the product. That's not new for Tableau. In the beginning we said, 'We want to build this tool for everyone,' but if I'm building it for everyone I can't assume that you know SQL, that you know color design, that you know how to tell a good story, so we had to build all those in there and then let users depart from that. With these smart things, it's how can I extend that to letting people get different kinds of value from their question. We have a researcher in the NLP space who was seeing these signals a while ago and she started prototyping some of these ideas about how to bring natural language questioning into an analytical workspace, and that really inspired us to look deeply at the space and led us to think about acquisitions..

What's the roadmap for Tableau's AI capabilities?

With the way tech has been developing around things like AI and machine learning, there are just all kinds of new techniques that are available to us that weren't mainstream enough 10 years ago to be pulling into the product.

Beers: You're going to see these AI and machine learning-style capabilities really in every layer of the product stack we have. We showed two [at the conference] -- Ask Data and Explain Data -- that are very much targeted at the analyst, but you'll see it integrated into the data prep products. We've got some smarts in there already. We've added Recommendations, which is how to take the wisdom of the crowd, of the people that are at your business, to help you find things that you wouldn't normally find or help you do operations that you yourself haven't done yet but that your community around have done. You're going to see that all over the product in little ways to make it easier to use and to expand the kinds of people that can do those operations.

As a technology officer, how fun is this kind of stuff for you?

Beers: It's really exciting. It's all kinds of fun things that we can do. I've always loved the mission of the company, how people see and understand data, because we can do this for decades. There's so much interesting work ahead of us. As someone who's focused on the technology, the problems are just super interesting, and I think with the way tech has been developing around things like AI and machine learning, there are just all kinds of new techniques that are available to us that weren't mainstream enough 10 years ago to be pulling into the product.