 Welcome back to SuperCloud 22. This is an open community event and it's dedicated to tracking the future of cloud in the 2020s. SuperCloud is a term that we use to describe an architectural abstraction layer that hides the underlying complexities of the individual cloud primitives and APIs and creates a common experience for developers and users irrespective of where data is physically stored or on which cloud platform it lives. We're now going to explore the nuances of going to market in a world where data architectures span on premises across multiple clouds and are increasingly stretching out to the edge. Paula Hansen is the president and chief revenue officer at Altrix. And the reason we asked her to join us for SuperCloud 22 is because first of all, Altrix is a company that is building a form of super cloud in our view. If you have data in a bunch of different places and you need to pull in different data sets together, maybe I want to filter it or blend it or cleanse it, shape it, enrich it with other data, analyze it, report it out to your colleagues. Altrix allows you to do that and automate that, that life cycle. And in our view is working to break down the data silos across clouds, hence SuperCloud. Now the other reason we invited Paula to the program is because she's a rock star female in tech and since day one at theCUBE we've celebrated great women in tech and in this case a woman of data Paula Hansen. Welcome to the program. Thank you Dave, I am absolutely thrilled to be here. Okay, we're going to focus on customers, their challenges and going to market in this cross-cloud, multi-cloud, SuperCloud world. First Paula, what's changing in your view in the way that customers are innovating with data in the 2020s? Well, I think we've all learned very clearly over these last two years that the global pandemic has altered life and business as we know it and now we're in an interesting time from a macroeconomic perspective as well. And so what we've seen is that every company in every industry has had to pivot and think about how they meet redefined customer expectations and an ever-evolving competitive landscape. There really isn't an industry that wasn't reshaped in some way over the last couple of years. And we've been fortunate to work with companies in all industries that have adapted to this ever-changing environment by leveraging all tricks to help accelerate their digital transformations. Companies know that they need to unlock the full potential of their data to be able to move quickly, to pivot and to respond to their customers' needs as well as manage their businesses most efficiently. So I think nothing tells that story better than sharing a customer example with you, Dave. We love to share stories of our very innovative customers. And so the one that I'll share with you today in regards to this is Delta Airlines who we're all very familiar with. And of course Delta's goal is to always keep their airplanes in the air, flying passengers and getting people to their destinations efficiently. So they focus on the maintenance of their aircraft as a necessary part of running their business and they need to manage their maintenance stops and the maintenance of their aircrafts very efficiently and effectively. So we work with them, they leverage our platform to automate all the processes for their aircraft maintenance centers. And so they've built out a fully automated reporting system on our platform, leveraging tons of data. And this gives their service managers and their aircraft technicians foresight into what's happening with their scheduling and their maintenance processes. So this ensures that they've got the right technicians in the service center when the aircrafts land and that everything across that process is fully in place. And previously because of data silos and just complexity of data, this process would have taken them many, many hours in each independent service center. And now leveraging Altrix and the power of analytics and bringing all the data together, those centers can do this process in just minutes and get their planes back in the air efficiently and delivering on their promises to their customers. So that's just one of many examples that we have in terms of the way that Altrix analytics automation helps customers in this new age and helping to really unlock the power of their data. You know, Paul, that's an interesting example because in a previous world, I worked with some airlines and people maybe don't realize this, but aircraft maintenance is the mission critical application for carriers. It's not the booking system because, you know, we've also been there before, we show you there's a problem when you're booking or sometimes, you know, it's unfortunate, but people, you know, they get debucked. But the aircraft maintenance is the one that matters the most and that keeps, you know, planes in the air. So we hear all the time you just mentioned it about data silos and how problematic they are. So specifically, how are you seeing customers thinking about busting the data silos? Yeah, that's right. It's a big topic right now because companies realize that business processes that they run their business with is very cross-functional in nature and requires data across every department in the enterprise and you can't keep data locked in one department. So if you think of business processes like pay to procure or quote to cash, these are business processes that companies in every industry run their business and that requires them to get data from multiple departments and bring all of that data together seamlessly to make the best business decisions that they can make. So what our platform does is and is really well known for is being very easy for users number one and then number two, being really great at getting access to data quickly and easily from all those data silos really regardless of where it is. We talk about being everywhere and when we say that we mean whether it's on-prem in your legacy applications and databases or whether it's in the cloud with of course all the multiple cloud platforms and modern cloud data warehouses, regardless of where it is, we have the ability to bring that data together across hundreds of different data sources, bring it together to help drive insights and ultimately help our customers make better decisions, take action and deliver on the business outcomes that they all are trying to drive within their respective industries. And what's- Go ahead. Please carry on. Well, I was just gonna say that what I do think has really sort of a tipping point in the last six months in particular is that executives themselves are really demanding of their organizations this democratization of data and the breaking down of the silos and empowering all of the employees across their enterprise regardless of how sophisticated they are with analytics to participate in the analytic opportunity. So we've seen some really cool things of late where executives, CEOs, key financial officers, chief data officers are sponsoring events within their organizations to break down these silos and encourage their employees to come together on this democratization opportunity of democratization of data and analytics. And there's a shortage of data scientists on top of this. So there's no way that you're gonna be able to hire enough data scientists to make sense of all this data running around your enterprise. So we believe with our platform we empower people regardless of their skillset. And so we see executives sponsoring these hackathons within their environments to bring together people to brainstorm and ideate on use cases to share examples of how they leverage our platform and leverage the data within their organization to make better decisions. And it's really, it's really quite cool. Companies like Stanley Black and Decker, Ingersoll Rand, IngeKate PLC, these are all companies that the executive team has sponsored these hackathon events and seen really powerful things come out of it. As an example, Ingersoll Rand sponsored their Altrix hackathon with all of their data workers across various different functions where the data exists. And they focused on both top line revenue use cases as well as bottom line efficiency cases. And one of the outcomes was a use case that helped with their distribution center in North America and bringing all the data together across their various applications to reduce the amount of over-ordering and under-ordering of parts and more effectively manage their inventory within that distribution center. So really cool to see this is now an executive level, board level conversation. Very cool. I mean, the hackathon really bringing people together for collaboration. A couple of things that you said I want to comment on. I mean, again, one of the reasons why we invited you guys to come on is when you think about on-prem data anybody who follows theCUBE and my breaking analysis program knows we're big fans of Jamak to Ghani's concept of data mesh and data mesh is supposed to be inclusive. It doesn't matter if it's an S3 bucket or Oracle database or data warehouse or data lake. That's just a note on the data mesh. So it should be inclusive and super cloud should include on-prem data to the extent that you can make that experience consistent. We have a lot of technical sessions here at super cloud 22. We're focusing now and go to market and the ecosystem and we live in a world of multiple partners, exploding ecosystems and a lot of times it's co-opetition. So Paula, when you joined Altrix you brought a proven go to market discipline to the company alignment with the customer, playbooks, best practice of sales, et cetera. And we've seen the results. I mean, it's a big reason why, you know, Mark Anderson and the board promoted you to president just after 10 months. Summarize how you approached the situation at Altrix when you joined last spring. Yeah, I think first we were really intentional about what part of the market, what type of enterprises get the most benefit from the innovation that we deliver. And it's really clear that it's large enterprises, right? That the more complex a company is, most likely the more data they have and oftentimes the more decentralized that data is. And they're also really all trying to figure out how to remain competitive by leveraging that data. So the first thing we did was, you know, be very intentional that we're focused on the enterprise and building out all of the capability required to be able to serve the enterprise. Of course, essential to all of that is having a platform capability because enterprises require that. So with Suresh Fatal, our chief product officer he's been fantastic in building out an end-to-end analytic platform that serves a wide range of analytic capabilities to a wide range of users. And then of course has this, you know, flexibility to operate both on-prem and in the cloud, which is really important because we see, we see this hybrid environment and this multi-cloud environment being something that is important to our customers. The second thing that I was really focused on was understanding how do you have those conversations with customers when they all are in maybe different types of backgrounds? So the way that you work with a business analyst in the office of finance or supply chain or sales and marketing is different than the way that you serve a data scientist or a data engineer in IT. The way that you talk to a business owner who wants, you know, not to really understand the workflow level of data, but wants to understand the insights of data. That's a different conversation. When you want to have a conversation of analytics for all or democratization of analytics at the executive level with a chief data officer or a CIO, that's a whole different conversation. And so we've built very specific sales plays to be able to have those conversations, bring the relevant information to the relevant person so that we're really making sure that we explain the value proposition of the platform, fully understand their world, their language and can work with them to deliver the value to them. And then the third thing that we did was really heavily invest in our partnerships. And you referenced this day, right? It's a broad ecosystem out there. And we know that we have to integrate into that broad data ecosystem and be a good partner to serve our customers. So we've invested both in technology integration as well as go to market strategies with cloud data warehouse companies like Snowflake and Databricks or RPA companies like UiPath and Blue Prism as well as a wide range of other application and all of the cloud platforms because that's what our customers expect from us. So that's been a really important sort of third pillar of our strategy and making sure that from a go to market perspective, we understand where we fit in the ecosystem and how we collectively deliver on value to our joint customers. So that's super helpful. I mean, what I'm taking away from this is you didn't come to it with a generic playbook. Frank Slutman always talks about situational leadership. You assess the situation and applied that. And a great example of partners is Snowflake and Databricks is sort of opposites but trying to solve similar problems. So you've got to be inclusive of all that. So we're trying to sort of squint through this, Paul, and say, okay, are there nuances and best practices beyond some of the things that you just described that are unique to what we call super cloud? Are there observations you can make with respect to what's different in this post-isolation economy, specifically in managing remote employees and of course remote partners working with these complex ecosystems and the rise of this multi-cloud world. Is it different or is it same wine, new bottle? Well, I think it's both common from the on-prem or pre-cloud world, but there's also some differences as well. So what's common is that companies still expect innovation from us and still want us to be able to serve a wide range of skill sets. So our belief is that regardless of the skill set that you have, you can participate in the analytics opportunity for your company and unlocking the potential of your data. So we've been very focused since our inception to build out a platform that really serves this wide range of capabilities across the enterprise space. What's perhaps changed more or continues to evolve in this cloud world is just the flexibility that's required. You have to be everywhere. You have to be able to serve users wherever they are and be able to live in a multi-cloud or super cloud world. So when I think of cloud, I think it just unlocks a whole bigger opportunity for Altrix and for companies that want to become analytic leaders because now you have users all over the globe, many of them looking for web-based analytic solutions and of course these enterprises are all in various places on their journey to cloud and they want a partner and a platform that operates in all of those environments, which is what we do at Altrix. So I think it's an exciting time. I think that it's still very early in the analytic market and what companies are going to do to leverage their data to drive their transformation and we're really excited to be a part of it. So last question is I said up front, we always like to celebrate women in tech. How'd you get into tech? I mean, you've got a background, you've got somewhat of a technical background, being technical sales and then of course rose up throughout your career and now have a leadership position. I called you a woman of data. How'd you get into it? Where'd you find the love of data? Give us the background and help us inspire some of the young women out there. Oh, well, but I'm super passionate about inspiring young women and thinking about the future next generation of women that can participate in technology and in data specifically. I grew up loving math and science. I went to school and got an electrical engineering degree, but my passion around technology hasn't been just around technology for technology sake. My passion around technology is what can it enable? What can it do? What are the outcomes that technology makes possible? And that's why data is so attractive because data makes amazing things possible, right? We shared, I shared some of those examples with you earlier, but not only can we have effect with data in businesses and enterprise, but governments globally now are realizing that the ability for data to really have broad societal impact. And so I think that that speaks to women many times, right? Is that what does technology enable? What are the outcomes? What are the stories and examples that we can all share and be inspired by and feel good and inspired to be a part of a broader opportunity that technology and data specifically enables. So that's what drives me in those of the conversations that I have with the women that I speak with in all ages, all the way down to K through 12 to inspire them to have a career in technology. Awesome, you know, the more people in STEM, the better and the more women in our industry, the better. Paula Hansen, thanks so much for coming in the program. Appreciate it. Thank you, Dave. Okay, keep it right there for more coverage from SuperCloud 22, you're watching theCUBE.