 It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world and the world is changing with it. But is everyone spending resulting in the same ROI? This is Lisa Martin. Welcome to the CUBE's presentation of democratizing analytics across the enterprise made possible by Alteryx. In Alteryx commissioned IDC info brief entitled Four Ways to Unlock Transformative Business Outcomes from Analytics Investments found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special CUBE presentation, Jason Klein, Product Marketing Director of Alteryx will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jackie Van der Lea Grayling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global e-commerce company innovate with analytics. Let's get the show started. Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. Hello, nice to be here. Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1,500 leaders? What nuggets are in there? Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytic skills of their employees. And this widening analytic gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? Sure. Well, first there's more data than ever before. The data is changing the world and the world is changing data. Enterprise is across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data. Yet, instead, they're relying on outdated spreadsheet technology. Nine out of ten survey respondents said that less than half of their knowledge workers are active users of analytic software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everyone. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytic software, meaning they're prioritizing easy technology to accelerate analytics democratization. So are there any specific areas that the survey uncovered where most companies are falling short, like any black holes organizations need to be aware of from the outset? It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists, they're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization, top skill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software, enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, a.k.a. the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets, compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, work should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side and it's expected to spend more on analytics than other IT. What risks does this present to the overall organization if IT and the lines of business guys and gals aren't really aligned? Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey however shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance which ultimately impedes democratization and hence ROI. So Jason, where can organizations that are maybe at the outset of their analytics journey or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline and dial up the value on their investment? Well, they can learn more on our website. I also encourage them to explore the Alteryx community which has lots of best practices, not just in terms of how you do the analytics but how you stand up in Alteryx environment but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it but it should be able to align to and enhance it. And of course, as you mentioned, it's about people process and technologies. Jason, thank you so much for joining me today unpacking the IDC info brief and the great nuggets and there are lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. Thank you, it's been a pleasure. In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is gonna join me. He's gonna be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching theCUBE, the leader in tech enterprise coverage. Somehow, many have come to believe that data analytics is for the few. For the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A Titan of industry or a future Titan of industry. You could be working to change the world, your neighborhood or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations. Because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone and everything and should be everywhere. That's why we believe in analytics for all. Hey everyone, welcome back to Accelerating Analytics Maturity. I'm your host, Lisa Martin. Alan Jacobson joins me next, the Chief Data and Analytics Officer at Alteryx. Alan, it's great to have you on the program. Thanks, Lisa. So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? At your spot on, many organizations really aren't leveraging the full capability of their knowledge workers and really the first step is probably assessing where you are on the journey, whether that's you personally or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. So when people talk about data analytics, they often think, ah, this is for data science experts, like people like you. So why should people in the lines of business, like the finance folks, the marketing folks, why should they learn analytics? So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are and it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a day to scientists and try to teach them to have the knowledge of a 20-year accounting professional or a logistics expert of your company. It's much harder to do that. And really if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet. But today, do you know what you would call that marketing professional? If they didn't know anything about the internet? Probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics and automation being employed in different industries? I know Altrix is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? Yeah, there's an incredible actually commonality between domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. McLaren is one of the great partners that we work with and they use Altrix across many areas of their business, from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data all using Altrix. And if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 sports has. And I don't see a ton of difference between the optimization that they're doing to hit their budget numbers. And what I see Fortune 500 finance departments doing to optimize their budget. And so really the commonality is very high even across industries. I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1 just to know that, wow, what they're doing is so incredibly important as is what we're doing. So talk about lessons learned. What lessons can business leaders take from those organizations like McLaren who are the most analytically mature? Probably first and foremost is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree. If your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear. Organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment. And so it's not about hiring two double PhD statisticians from Oxford, it really is how widely you can bring your workforce on this journey. Can they all get 10% more capable? And that's having incredible results at businesses all over the world. And another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily, having an approachable piece of software that everyone can use is really a key. So faster, able to move faster, hire ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. Absolutely, the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company. They showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. And that's key these days is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I gotta ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? So in many ways, it really is that easy. I have a 14 and 16-year-old kid. Both of them have learned all tricks, they're all tricks certified, and it was quite easy. It took them about 20 hours and they were off to the races. But there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happened to know as a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to if you wanna keep up with your profession. The big four accounting firms have trained over 100,000 people in Altrix. Just one firm has trained over 100,000. You can't be an accountant or an auditor at some of these places without knowing Altrix. And so the hard part really in the end isn't the technology and learning analytics and data science. The harder part is this change management. Change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E-enabled, that's the challenge. That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers? If you might be talking with someone who might be early in their analytics journey but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? That's a great question. So people entering into the workforce today, many of them are starting to have these skills. Altrix is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying, free take one. We put on hackathons and analytic days and it can be great fun. We have a great time with many of the customers that we work with helping them do this, helping them go on the journey. And the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that are really make great impact to society as a whole. Isn't that so fantastic to see the difference that that can make? It sounds like you guys are doing a great job of democratizing access to Ultrix to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Ultrix customers that really show data breakthroughs by the lines of business using the technology? Yeah, absolutely. So, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life-saving equipment, defensive equipment like armor plated vests. And they were needing to optimize their supply chain like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they used Ultrix to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint, they cut over a half a million dollars of inventory in the first year. But more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet. And they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report. And obviously running 140 legacy models that had to be done in a certain order and linked. Incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Ultrix and learn Ultrix. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% runtime performance. And so again, a huge improvement. I can imagine it probably had better quality as well because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the years that they will have on their business. Yeah, potentially millions, five millions of dollars. This is what we see again and again, company after company, government agency after government agency is how analytics are really transforming the way work is being done. That was the word that came to mind when you were describing all three customer examples, the transformation, this is transformative, the ability to leverage Ultrix to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcomes you mentioned, those are substantial metrics-based business outcomes. So the ROI and leveraging a technology like Ultrix seems to be right there sitting in front of you. That's right, and to be honest, it's not only important for these businesses, it's important for the knowledge workers themselves. I mean, we hear it from people that they discover Ultrix, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytics and analytic and automate processes actually matches the needs of the employees. And they too want to learn these skills and become more advanced in their capabilities. Huge value there for the business, for the employees themselves to expand their skillset to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you wanna point the audience to go to learn more about how they can get started? Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who wanna experience Ultrix, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment as we talked about at the beginning and see where you are on the journey and just reach out. We'd love to work with you and in your organization to see how we can help you accelerate your journey on analytics and automation. Alan, it was pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. Thank you so much. In a moment, Paula Hansen, who is the president and chief revenue officer of Ultrix and Jackie Van der Lea Grayling, who's the global head of tax technology at eBay, will join me. You're watching theCUBE, the leader in high-tech enterprise coverage. 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. Make that 2.3. Sector times out the wazoo. Way too much of this. Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Ultrix. Ultrix, analytics automation. Hey everyone, welcome back to the program. Lisa Martin here. I've got two guests joining me. Please welcome back to theCUBE Paula Hansen, the chief revenue officer and president at Ultrix and Jackie Van der Lea Grayling joins us as well, the global head of tax technology at eBay. They're gonna share with you how Ultrix is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the program. Thank you Lisa, great to be here. Yeah, Paula, we're gonna start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics as they talked about at the forefront of software investments, how's Ultrix helping its customers to develop roadmaps for success with analytics? Well, thank you Lisa. It absolutely is about our customers success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. Excellent, sounds like a very strategic program. We're gonna unpack that. Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jackie did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? So I think the main thing for us is when we started out was, is that our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we have to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. Starting with people is really critical. Jackie, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? So I think, you know, eBay is a very data-driven company. We have a lot of data. I think we are 27 years around this year. So we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to commit to them to move forward. The other thing is that, you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no, we're not independent. You couldn't move forward. You were dependent on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. And finally, we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks because you always have, not always, but most of the times you have support from the top in our case we have. But in the end of the day, it's our people that need to actually really embrace it and making that accessible for them. I would say it's definitely not for, say, a roadblock, but they could put some blocks you wanna be able to move. It's really all about putting people first. Question for both of you and Paula will start with you and then Jackie will go to you. I think the message in this program that the audience is watching with us is very clear analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data-driven. Paula? Yes, well, we leverage our platform across all of our business functions here at Altrix. And just like Jackie explained at eBay Finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a key sponsor for using our own technology. We use Altrix for forecasting all of our key performance metrics, for business planning across our audit function to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter. So it's really remain across our business and at the end of the day, it comes to how do you train users? How do you engage users to lean in to this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other to problem solve and along the way maybe earn badges depending on the capabilities and trainings that they take and just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it and as Jackie mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. That confidence is key. Jackie, talk about some of the ways that you're empowering folks without that technical expertise to really be data-driven. I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is in a different place in their journey. You have folks that's already really advanced who has done this every day and then you have really some folks that this is brand new and or maybe somewhere in between and it's about how you put everybody in their different phases to get to the initial destination and I say initial because I believe the journey is never really complete. What we have done is that we decided to invest in a group of concepts and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we had and we told people, listen, we're gonna teach you this tool, it's super easy and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So in these are people that don't have a background. They are not engineers, they're not data scientists and we ended up with the 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before and then you have to resolve and then it just went from there because people had a group of concepts. They knew that it worked and they overcame that initial barrier of change and that's where we are seeing things really, really picking up now. That's fantastic and the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes that the cultural barriers is key there. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula will start with you. Absolutely and Jackie says it so well which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Altrix to help address this skillset gap on a global level is through a program that we call SPARCT which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program has really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SPARCT. We started last May but we currently have over 850 educational institutions globally engaged across 47 countries. And we're gonna continue to invest here because there's so much opportunity for people, for society and for enterprises when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. So SPARCT has made a really big impact in such a short time period. It's gonna be fun to watch the progress of that. Jackie, let's go over to you now talk about some of the things that eBay is doing to empower the next generation of data workers. So we definitely wanted to make sure that we kept that momentum from the hackathon but we don't lose that excitement, right? So we just launched a program called eBay Masterminds. And what it basically is it's an inclusive innovation initiative where we firmly believe that innovation is for all upskilling for all analytics for all. So it doesn't matter your background doesn't matter which function you are in come and participate in this where we really focus on innovation introducing new technologies and upskilling of people. We are apart from that we also said well we should just keep it to inside eBay we have to share this innovation with the community. So we are actually working on developing an analytics high school program which we hope to file it by the end of this year where we will actually have high schoolers come in and teach them data essentials the soft skills around analytics but also how to use Alteryx and we're working with actually we're working with Spark and they're helping us develop that program and we really hope that it's a safe by the end of the year have a pilot and then also make sure so we roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. Analytics for all. Sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially kind of going down the stop and getting people when they're younger interested and understanding how they can be empowered with data across any industry. Paula let's go back to you. You were recently on the cubes super cloud event just a couple of weeks ago and you talked about the challenges the companies are facing as they're navigating what is by default a multi cloud world. How does the Alteryx analytics cloud platform enable CIOs to democratize analytics across their organization? Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked there was two million data scientists in the world so that's woefully under represented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs with business leaders is that they're integrating data analysis and the skill set of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Alteryx analytics cloud is to empower all of those people in every job function regardless of their skill set. As Jackie pointed out from people that would are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx analytics cloud and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze and report out so that we can break down data silos across the enterprise and drive real business outcomes as a result of unlocking the potential of data. As well as really lessening that skills gap as you were saying there's only two million data scientists you don't need to be a data scientist. That's the beauty of what Alteryx is enabling and eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you're most excited about as analytics truly gets democratized across eBay? When we start about getting excited about things when it comes to analytics, I can go on all day but I'll keep it short and sweet for you. I do think we are on the topic full of data scientists and I really feel that that is your next step for us anyways is that how do we get folks to not see data scientists as this big thing like a rocket scientist? It's something completely different and it's something that is in everybody in a certain extent. So the game partner with Alteryx who just released the AI ML solution allowing folks to not have a data scientist program but actually bold models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses quite a few and right now through our masterminds program we're actually running a four months program for all skill levels teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off and I really believe that that is our next step. I wanna give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things and one of the people in our team who doesn't have a data scientist background at all was able to develop a solution where there is a checkout feedback checkout functionality on the eBay site where sellers or buyers can verbatim add information and she built a model to be able to determine what relates to tax specific, what is the type of problem and even predict how that problem can be solved before we as a human even step in. And now instead of us or somebody going to verbatim try to figure out what's going on there we can focus on fixing the error versus actually just reading through things and not adding anybody. And it's a beautiful tool and I'm very impressed when we saw the demo and they've been developing that further. That sounds fantastic. And I think just the one word that keeps coming to mind and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies I want to thank you so much for joining me on the program today and talking about how Altrux and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. Thank you so much. As you heard over the course of our program organizations where more people are using analytics who have deeper capabilities in each of the four E's that's everyone, everything, everywhere and easy analytics. Those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics, not only focused on key aspects of their job but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on theCUBE.net, you can find all of the news from today on siliconangle.com and of course altrux.com. We also want to thank Altrux for making this program possible and for sponsoring theCUBE. For all of my guests, I'm Lisa Martin. I want to thank you for watching and bye for now.