(bright music) >> Hi, everyone. Welcome to theCUBE's coverage of WiDS 2022. I'm Lisa Martin, very happy to be covering this conference. I've got Vidya Setlur here with me, the director of Tableau Research. Vidya, welcome to the program. >> Thanks, Lisa. It's great to be here. >> So this is one of my favorite events. You're a keynote this year. You're going to be talking about what makes intelligent visual analytics tools really intelligent. Talk to me a little bit about some of the key takeaways that the audience is going to glean from your conversation. >> Yeah, definitely. I think we've reached a point where everybody understands that data is important, trying to understand that data is equally important. And we're also getting to that point where technology and AI is really picking up. Algorithms are getting better, computers are getting faster. And so there's a lot of dialogue and conversation around how AI can help with visual analysis to make our jobs easier, help us glean insights. So I thought it was a really timely point where we can really actually talk about it, and distilling into the specifics of how these tools can actually be intelligent beyond just the general buzz of AI. >> And that's a great point that you bring up. There's been a lot of buzz around AI for a long time. The organizations talk about it, software vendors talk about it being integrated into their technologies, but how can AI really help to make visual analytics interpretable in a way that makes sense for the data enthusiast and the business? >> Yeah, so to me, I think my point of view, which tends to be the general agreement among the research community, is AI is getting better. And there are certain types of algorithms, especially these repetitive tasks. We see this with even Instagram, right? You put a picture on Instagram, there are filters that can maybe make the image look better, some fun backgrounds. And those, generally speaking, are AI algorithms at work. So there are these simple, either fun ways or tasks that reduce friction where AI can play a role, and they tend to be really good with these repetitive tasks, right? If I had to upload a picture and constantly edit the background manually, that's a pain. So AI algorithms are really good at figuring out where people tend to do a particular task often, and that's a good place for these algorithms to come into play. But that being said, I think fundamentally speaking, there are going to be tasks where AI can't simply replace a human. Humans have a really strong visual system. We have a very highly cognitive system where we can glean insights and takeaways beyond just the pixels, or just the text. And so how do we actually design systems where algorithms augment a human, where a human can stay in the driver's seat, stay creative, but defer all these mundane or repetitive tasks that simply add friction to the computer? And that's what the keynote is about. >> And talk to me about when you're talking with organizations, where are they in terms of appetite to understand the benefits that natural language processing, AI and humans together, can have on visual analytics, and being able to interpret that data? >> Yeah. So I would say it's really moving fast. So three years ago, organizations were like AI, it's a great buzzword, we're weary because when rubber hits the road, it's really hard to take that into action. But now we're slowly seeing places where it can actually work. So organizations are really thirsty to figure out how do we actually add customer value? How do we actually build products where AI can move from a simple, cute proof of concept working in a lab to actual production? And that is where organizations are right now. And we've already seen that with various types of examples, like machine translation. You open up a Google page in Spanish, and you can hit auto translate and it will convert it into English. Now, is it perfect? Not, but is it good enough? Yes. And I think that's where AI algorithms are heading, and organizations are really trying to figure out what's in it for us, and what's in it for our customers. >> What are some of the cultural, anytime we talk about AI, we always talk about ethics. But what are some of the cultural, or the language specific challenges with respect to natural language techniques that organizations need to be aware of? >> Yeah, that's a great question, and it's a common question, and really important. So as I've said, these AI algorithms are only as good as the data that they're often trained on. And so it's really important, in addition to the cultural aspects of incorporating those into the techniques, is to really figure out what sort of biases come into play, right? So a simple example is there's sarcasm in language, and different cultures have different ways of interpreting it. There are subtleties in language, jokes. My kids have a certain type of language when they're talking with each other that I may not understand. So there's a whole complexity around cultural appropriation generations that, where language constantly evolves, as well as biases. For example, we've had conversations in the news where AI algorithms are trained on a particular data set for detecting crime. And there are hidden biases that go into play with that sort of data. So we're really, it's important to be acknowledged of where the data is, and what sorts of cultural biases come into play. But translation, simple language translation is already more or less a solved problem. But beyond the simple language translation, we also have to account for language subtleties as well. >> Right, and the subtleties can be very dramatic. When you're talking with organizations that are really looking to become data driven. Everybody talks about being data driven, and we hear it on the news all the time, it's mainstream. But what that actually really means, and how an organization actually delivers on that are two different things. When you're talking with customers that are, okay, we've got to talk about ethics. We know that there's biases and data. How do you help them get around that so that they can actually adopt that technology, and make it useful and impactful to the business? >> Yeah. So just as important as figuring out how AI algorithms can help an organization's business, it's equally important for an organization to be more data literate about the data that feeds into these algorithms. So making data as a first class citizen, and figuring out are there hidden biases? Is the data comprehensive enough? Acknowledging where there are limitations in the data and being completely transparent about that. And sharing that with customers, I think, is really key. And coming back to humans being in the driver's seat. If these experiences are designed where humans are, in fact, in the driver's seat, as a human, they can intervene and correct and repair the system if they do see certain types of oddities that come into play with these algorithms. >> Going to ask you in our final few minutes here, I know that you have a PhD in computer graphics from Northwestern, is it? >> Yep. >> Northwestern. >> Go Wildcats, yep. >> Were you always interested in STEM and data? Talk to me a little bit about your background. >> Yeah. I grew up in a family full of academics and female academics. And now, yes, I have boys, including my dog. Everybody's male, but I have a really strong vested interest in supporting women in STEM. And I actually would go further and say, STEAM. I think arts and science are both equally important. In fact, I would say that on our research team, there's a good representation of minorities and women. And data analysis and visual analysis, in particular, is a field that is very conducive for women in the field, because women tend to be naturally meticulous. They're very good at distilling what they're seeing. So I would argue that there are a host of disciplines in this space that make it equally exciting and conducive for women to jump in. >> I'm glad that you said that. That's actually quite exciting, and that's a real positive thing that's going on in the industry, and what you're seeing. So I'm looking forward to your keynote, and I'm sure the audience is as well. Vidya, it was a pleasure to have you on the program talking about intelligent visual analytics tools, and the opportunities that they bring to organizations. Thanks for your time. >> Thanks, Lisa. >> For Vidya Setlur, I'm Lisa Martin. You're watching theCUBE's coverage of WiDS conference 2022. Stick around, more great content coming up next. (bright music)

(upbeat electro music) >> Hi and welcome to another CUBE Conversation. This one from BMC Helix's Immersion Days, Santa Clara Marriott in Santa Clara, California. I'm Peter Burris. As we think about what organizations have to do over the next few years, imagine a world in which technology's being applied to generating revenue where customer experience is dependent upon technology, where your overall operational fabric and framework and likelihood of staying in business is tied to how well your technology plant works. That's where we're going and bringing an IT capability that's capable of supporting and sustaining those demands on business is an absolutely essential thing for businesses of all side. Fundamental, we have to think about how digital services that's delivering those new sources of revenue, new experiences and operations management which is ensuring that the predictability and certainty of how operations work is at the heart of many of the changes within IT today. Got a great guest to talk about that. Vidya Srinivasan is the Product Strategy and Marketing Executive at BMC Software. Vidya, welcome back to the CUBE. >> Pleasure to be here. >> So I said a lot upfront but lets start by getting the simple update. Where is BMC Helix today? >> Yeah, so Peter you were there for our first launch last year. I think about a year and a half ago. So since then obviously we've come a long way. We've onboarded a lot of customers, existing customers as well as new logos. So we are at a point where our customers are happy with Helix. They want to see more. They're working with us to roll out chat bots, really implementing a lot of our AI automation technologies. And as you heard today, eighteen months in, we now have Helix kind of expanded into the ITOM world. So we are actually bringing together the conversions of ITSM and ITOM with our Helix platform. So now officially, Helix is able to support a lot of the IT operations management functions that include monitoring , that include remediation, that include capacity and cost optimization. So it's really bringing together the two worlds of IT. That's really a foundation for a lot of our IT organizations. So we are very happy to announce it today at the Immersion Day Events and we are looking forward to a great update probably in the next six months. Back with you. >> Well one of the many challenges that an IT organization faces is that the nature of the assess that they're trying to generate returns on or changing away from hardware up into often software defining for structure and software and data as well. And that's one of the catalysts for why this ITOM/ITSM conversions is starting to happen. So we have had these people in silos. What kind of tensions is that generating as businesses try to deploy and utilize their IT in new and expressive and innovative ways? >> Yeah that's a great question. When we talk about the foundation of anything to do with IT, right, is knowing what you have. And as people heard in the keynote today, it's turning your unknowns to knowns, right? A big part of the challenge with IT is not knowing what you have. So discovery, as you said, is one of the foundational solutions we have within the Helix Suite that helps customers discover what they have whether it's as assets, it could be software, especially in a software world. So really understanding what you have and then being able to proactively and predictively monitor those assets, knowing what vulnerabilities you have, being able to automatically remediate those, and ultimately it's delivering the ultimate service experience to the end customer. So that's where Helix as a whole with Discover, Monitor, Service, Re Media and Optimize gives you the whole good handle on what you have and be able to ultimately provide the service of the future that we all as consumers in our day to day lives expect, we'll start expecting in our work lives. >> Well there has historically been some tension between the ITOM people and the ITSM people. They've been very strong siloed, each intent on optimizing their own capabilities. That has undermined business in many respects and certainly undermined the IT mission because a lot of people look at IT as being the problem in large measure because they have been throwing information back over the fence and sometimes at each other. So in your experience, now Helix has been out there for a year and a half. In your experience, how are ITOM and ITSM groups starting to work better together? Utilizing tooling that's not built for just one but is actually built for the idea, the promise of a greater more converged set of functions? >> Yeah so I think the tug of ITSM and ITOM organizations continue to exist and the convergence starts happening when the organization starts starting to mature in their life cycles. So let's take a simple example of a ticket. You as an end user open a service request, it goes to a service desk, somebody picks it up, and ultimately if that ticket is associated with an asset or a service that's running somewhere and the actual Cloud instance or something is broken, that's a perfect example of an end user, an agent in an ITSM scenario and an IT operations person having to all work together to make the customer happy. So that is a typical scenario in every organization and every organization has multiple service desks and multiple lines of business, not just IT issues. So making sure that through our solutions, making sure that we can minimize the existence of IT silos is a big part of what Helix brings to the table. And as we rule out the capabilities, whether you call them Discover, you know, the five capabilities that we outlined or whatever you might be referring to within the organization. It is important to make sure that the ultimate platform that brings them together is seamlessly integrated, whether it's all on one physical platform or through integration strategies across other tools in the industry, but that's kind of the intent of bringing together these two worlds. >> But at least the data is working together. >> Exactly. >> So I want to highlight one of the things you said and why it's so important we start thinking about this differently. You noted the idea of a user, an ITSM or a Service Management professional and then someone who's on the operations side doing configurations or provisioning of resources. When that person that started that off, who generated that ticket, is an employee we have certain degree of control over how fast we can service them. When we start talking about that user being a customer, now we're really talking about service experience. We're really talking about the brand. We're really talking about revenue. How is the emergence of a new class of users, being customers and increasingly using things like Robotic Process Automation, other forms of software, that are generating these kinds of requirements, altering the demand for some of these advanced tools? >> Yeah there's quite a bit of things you touched in that question so from an end user standpoint, automation comes in various forms and obviously from an end user standpoint it's this channel of preference and that's where leveraging technologies like chat bots from an end user experience standpoint, being able to use your phone, it could be your tablet, whatever it might be or your voice assistance through your phone, all of those are things that customers are expecting because you know, that's how I communicate on a day to day basis so it's nothing new. On the RPA and the automation side on the back end of things there's definitely this notion of augmented, I know a lot of our speakers spoke about this earlier, this notion of augmented intelligence that we all need to kind of embrace in order for us to deliver that end user experience and end user doesn't have to be B2B. It can be B2E, B2C, whatever it might be. At some point at least in this world we are kind of getting to a point where it doesn't matter whether it's a B2B, B2C, or B2E. It's everybody is an end user and there is no delineation in terms of the experience that anybody expects. So that's kind of what we expect to transcend into the back office whether it's IT service desk or if it's the IT operation's persona. Being able to discover or scan things from your chat bot, from your tablet, instead of having a honking machine that you normally think of when you think of a knock. So those are all things I think are sort of going to be erased in terms of what we think of IT ops. as we look into the next three to five years. So that's the experience that I think, it's not just limited to an end user but across the IT organization. What does that experience look like for all the various personas to coexist and collaborate within the construct of an enterprise. >> So, you again, have been out with customers. Either taking remedy customers and bringing them to Helix or brand new customers and bringing them to Helix. What are some of the patterns of success that you're starting to see? Where does it tend to start? What kinds of outcomes are they achieving? Where do you see your happiest customers being? >> I think it's spectrum of customers right, so it's a range. There are customers who are at an early stage in terms of just thinking about how to move to Cloud so those customers are simply thinking about okay I've been using your OnPrem Solution Remedy for a while and we are at a point where we need to move it to in to a SaaS model. So there are customers who are just looking to lift and shift and move to a SaaS model. There are other customers who, it's a no-brainer, they started with us in a SaaS model and then now they're looking to leverage more of the NextGen experience, so they are looking at chat bots, they're looking at RPA bots and working with us on that. And then there are customers who are just looking to integrate with us on different fronts. They might be using other tools and then they're looking at leveraging our integration capabilities or whatever it might be so there's a variety of different customers in different stages but obviously a big part of this shift we are seeing that's common across these is the move to SaaS and the fact that they don't want to worry about running their operations as much as they want to reinvent and innovative and grow. So that's the common theme that we're seeing across the variety of customers that we're helping today. >> Vidya Srinivasan, Product Strategy, Marketing Executive, BMC Software, once again thanks for being on the CUBE. >> Thank you very much for having me. >> And from the BMC Helix Immersion Days at Santa Clara Marriott in Santa Clara, California, I'm Peter Burris. Once again this has been a CUBE Conversation. Until next time. (upbeat electro music)