 Colibra is a company that was founded in 2008, right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now historically data governance and data quality initiatives, they were back office functions and they were largely confined to regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become. And the value proposition for data quality and trust, it evolved from primarily a compliance-driven issue to becoming a linchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper-specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. And it resulted in a lot of frustration with data initiatives from most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today, for example, there's quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like DataMesh and the idea of data as a product. They're gaining traction as a way to better serve the data needs of decentralized business users. You hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that. But also, how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. In other words, while it's enticing to experiment and run fast and loose with data initiatives, kind of like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated and intelligence. Governance and data lineage is still fundamental to ensuring trust as data, it moves like water through an organization. No one is going to use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification as data flows through an organization. The continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. Hello and welcome to theCUBE's coverage of data citizens made possible by Calibra, a leader in so-called data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Vellante and I'm one of the hosts of our program, which is running in parallel to data citizens. You know, at theCUBE, we like to say we extract the signal from the noise and over the next couple of days, we're going to feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives, Felix Van Damaler, who is the co-founder and CEO of Calibra will join us, along with one of the other founders of Calibra, Stan Christians, who's going to join my colleague, Lisa Martin. I'm going to also sit down with Laura Sellers. She's the chief product officer at Calibra. We'll talk about some of the announcements and innovations they're making at the event and then we'll dig in further to data quality with Kirk Hasselback. He's the vice president of data quality at Calibra. He's an amazingly smart dude who founded OwlDQ, a company that he sold to Calibra last year. Many companies, they didn't make it through the Hadoop era. You know, they missed the industry waves and they became Driftwood. Calibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. Last year, the Cube covered data citizens, Calibra's customer event and the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hadoop movement, we had data lakes that sparked the ascendancies of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of AI, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives and we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights from data, trust the data and begin to use that data in new ways, fueling data products, monetization and insights. Data citizens 2022 is back and we're pleased to have Felix Vandemala who is the founder and CEO of Calibra. He's on theCUBE, we're excited to have you, Felix. Good to see you again. Likewise, Dave, thanks for having me again. You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Calibra has been up to over the past year and what's changed since Data Citizens 2021 and we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers, they're struggling with things like supply chains, uncertain economic trends and we're not just snapping back to the 2010s, that's clear. And that's really true as well in the world of data. So what's different in your mind in the data landscape of the 2020s from the previous decade and what challenges does that bring for your customers? Yeah, absolutely. And I think you said it well, Dave, and the intro, that rising complexity and fragmentation in the broader data landscape that hasn't gotten any better over the last couple of years. And when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kind of more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under with respect to data as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance has only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. So it's become much more acute. And to your earlier point, we do live in a different world and the past couple of years, we could probably just kind of brute force it, right? We could focus on the top line. There was enough kind of investments to be had. I think nowadays organizations are focused or are in a very different environment where there's much more focus on cost control, productivity, efficiency, how do we truly get the value from that data? So again, I think it's just another incentive for organizations to now truly look at data and to scale with data, not just from a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? You said that the people and process, how do we do that at scale? And that's only becoming much more important and we do believe that the economic environment that we find ourselves in today is gonna be a catalyst for organization to really take that more seriously, if you will, than they maybe have in the past. You know, I don't know when you guys founded Calibra, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your mission and what are you doing to address these challenges? Yeah, absolutely. We started Calibra in 2008. So in some sense in the last kind of financial crisis, and that was really the start of Calibra where we found product market fit working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the financial crisis. And kind of here we are again in a very different environment, of course, 15 years, almost 15 years later, but data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again be able to provide everyone. And that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is only becoming more important, more relevant. And we definitely have a lot more work ahead of us because we're still relatively early in that journey. Well, that's interesting because in my observation, it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, Kaliber has had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your current momentum? Yeah, absolutely. Again, there's a lot of tailwinds organizations are only maturing the data practices. And we've seen it kind of transform or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders, and every single vertical. So it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the markets with some of the cloud partners like Google, Amazon, Snowflake, Databricks, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners, and of course our customers to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging AI, machine learning, again, to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architectures, they've become mission critical, they've become real-time, and so monitoring, observing those data pipelines continuously has become absolutely critical. So we're really excited about that as well. And on the organizational side, I'm sure you've heard the term around kind of data mesh, something that's gaining a lot of momentum rightfully so. It's really the type of governance that we always believed in, federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale the data organizations, and so that aligns really well with our vision, and from a product perspective, we've seen a lot of momentum with our customers there as well. Yeah, a couple of things there. I mean, the acquisition of ALDQ, Kirk Hasselbeck and their team, it's interesting, the whole data quality used to be this back office function and really confined to highly regulated industries. It's come to the front office. It's top of mind for chief data officers. Data mesh, you mentioned, you guys are a connective tissue for all these different nodes on the data mesh. That's key, and of course, we see you at all the shows. You're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the products. We're going to go deeper into products later on at Data Citizens 22, but we know you're debuting some new innovations, whether it's the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. Yeah, absolutely. We're super excited. A ton of innovation. And we think about the big theme. And like I said, we're still relatively early in this journey towards kind of that mission of data intelligence, that really bold and compelling mission. Either customers are just starting on that journey. We want to make it as easy as possible for the organization to actually get started because we know that's important that they do. And for our organization, and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then how do we make sure that as clear becomes this kind of mission critical enterprise platform from a security performance, architecture, scale, supportability that we're truly able to deliver that kind of enterprise mission critical platform. And so that's the big theme from an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights, one is around data marketplace. Again, a lot of our customers have plans in that direction. How do we make it easy? How do we make available a true kind of shopping experience so that anybody in the organization can in a very easy search first way, find the right data product, find the right data set that they can then consume usage analytics. How do we help organizations drive adoption, tell them where they're working really well and where they have opportunities, homepages again to make things easy for people, for anyone in the organization to kind of get started with Kulibia. You mentioned workflow designer. Again, we have a very powerful enterprise platform, one of our key differentiators as the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So really customers can take it to the next level. There's a lot more new product around Kulibia Protects, which in partnership with Snowflake, which has been a strategic investor in Kulibia, focused on how do we make access governance easier? How are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as a much more effective rate. Really excited about that product. There's more around data quality. Again, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud, there's been a big part of our strategy. So we launched our data quality cloud product, as well as making use of those native compute capabilities in platforms like Snowflake, Databricks, Google, Amazon and others. And so we're bettering a capability that we call push down. So we're actually pushing down the compute around data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations that we talk about being able to connect to every source, integrations are absolutely critical. And we're really excited to deliver new integrations with Snowflake, Azure and Google cloud storage as well. So there's a lot coming out. The team has been at work really hard and we're really, really excited about what we're bringing to market. Yeah, a lot going on there. I wonder if you could give us your closing thoughts. I mean, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles, you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been so hard. So how do you see sort of the future and you'll give us your closing thoughts, please. Yeah, absolutely. And I think we're really at a pivotal moment. I think you said it well, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We're still early making it as easy as we can. It's kind of our mission. And so I'm really excited to see what we're gonna, how the market's gonna evolve on the next few quarters and years. I think the trend is clearly there. We talked about data mesh, this kind of federated approach focused on data products is just another signal that we believe that a lot of organizations are now at the time they understand and need to go beyond just the technology. I really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in, much more focus on control, much more focus on productivity efficiency. And now is the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. Yeah, it's a new era. The next 10 years of data won't be like the last as I always say, Felix, thanks so much and good luck in San Diego. I know you're gonna crush it out there. Thank you, Dave. Yeah, it's a great spot for an in-person event. And of course the content post event is going to be available at Kalibera.com and you can of course catch the cube coverage at thecube.net and all the news at siliconangle.com. This is Dave Vellante for theCUBE, your leader in enterprise and emerging tech coverage.