>> From Sand Hill Road, in the heart of Silicon Valley, it's theCUBE, presenting the People First Network: Insights from Entrepreneurs and Tech Leaders. >> Hello everyone, I'm John Furrier with theCUBE. We are here for a special conversations part of Mayfield's 50th anniversary People First Network. This is a series of interviews from fault leaders around entrepreneurship, and insights. Manish Chandra, who's the CEO, Co-Founder and CEO of Poshmark, a very successful company. A serial entrepreneur that I've known for many, many years, going back to his early startups. Great to see you, thanks for spending the time today. >> Thanks for having me, John. And it's great, we were just talking about our early days when you were doing your podcast, and me, I was doing a social shopping company back then, was it, 2006? 2005 timeframe, a long time back. >> Pioneers have arrows on their back, as they always say in entrepreneurship, but if you look at the time when we were doing startups, over 14 years ago, social sharing, democratization; these were the buzzwords. This was the wave that we were all trying to ride. When 2008 hit, it kind of took the water down a little bit. But still the game didn't change, a rise comes Facebook, Twitter, social, multiple channels. The consumer's expectations changed a lot in that timeframe, and I want to get your thoughts because you've had two successful companies, Kaboodle and now PoshMark, with almost 40 million users, billion dollar valuation, hundreds and hundreds of employees, got like a hundred openings in your company. You're ramping up and you're scaling. But the expectations of users has changed. What are some of those dynamics in your business that you're seeing? >> I think the biggest sort of, uh, culmination or ignition point for social platforms came with the advent of mobile. And uh, early days of mobile were crude days, but you know, if you look back at the advent of Poshmark, sort of the idea of Poshmark reignited in my mind in 2010, and iPhone 4 had just come out. It was a couple of months after Instagram had started. And SnapChat had not even started yet. And what, I think, mobile platform did, especially with the high quality platform like iPhone 4 was, it made the process of content creation, consumption, and sharing so fast, and you finally had the device that could produce it, that uh, it just kept accelerating. And now, in the days of, you know, iPhone Excess Max and what have you, it's just so easy. At the same time, the speed expectation, the transparency expectation, and the velocity of expectation has gone up, and so what we've seen in Poshmark is, day one, our users were spending somewhere between 20-25 minutes in the app. And here today, we have billions of users, and they're still doing that same thing, so that level of deep immersion that you see is sort of unique to the mobile paradigm. >> I want to dig into the user expectation and the experiences that you're delivering. But before we start, take a minute to explain Poshmark; what you guys are doing as a core business, how it's evolved. >> So Poshmark, very simply, is a simple way to buy and sell fashion and other sort of style-based paradigm, we call it a social commerce platform because it really brings together users in a unique way. But it really allows anybody to build a business starting with their closet all the way to opening up a full-brand, wholesale engine on the platform. We provide all of the infrastructure, you know, shipping, payments, technology, and you have to bring in your inventory, so we don't touch inventory, but everything else we handle for you. >> So you're really helping people, enabling them to be successful with the ease of use; heavy lifting. >> Heavy lifting. >> It's kind of like Amazon. You don't need to provision anything, just kind of get started. E-Commerce in the era now of Google, Amazon, and Cloud technology, you see the rise of all the scale. How are you riding that trend, because that's a tailwind for you? And what is that doing for the user's expectations, I mean, I have four kids, I see them all online, they never use their laptops, except for homework, but they're on the mobile device, they're doing new things, this is the new expectation; what are some of those expectations? >> In our business, which is the business of fashion and style, what it means for people is, number one is, if they see something. Whether they see something on Instagram, or something on SnapChat, it needs to be instantly shoppable, right? And that obviously benefits a platform like us, which makes easy access to all of the different brands and things that are developing. At the same time, what social media's also doing is making the obsoleting of your products very fast, because once you've used it, you've, you know, posted a picture, you want to be able to not consume it again. >> You've been seen wearing the same outfit, I can't wear it twice! >> Exactly! And so we make that easy as well. And then the third thing is, uh, everyone is a content creator, everyone is a seller, everyone is sort of participating in this economy; people are hosting AirBnB guests in their home, people are selling on Poshmark, and the reason is because phone, and sort of this new mindset of collaboration and social makes it very easy for people to participate, so they want to be able to sell, but they don't want any hassle in that process. And so the new consumer expectation is instantaneous, deeply immersive, and constantly changing, and if you can't satisfy all of those things, then it becomes harder for you to scale. So you have to use technology, the physical world, and sort of the emotion all in the right mixture. >> One of the things I know that you're passionate about, and we've had this conversation, we feel the same way, certainly, at theCUBE is, role of community. And I see a lot of companies these days, whether they're saying we're doing an ICO using tokens to, um, getting a big bag of money from venture capitalists, oh yeah, our key strategy is to build a community. You can't buy a community. You've got to really win the hearts and minds and provide value, and you really can't, and build trust. Talk about the role of community for you guys, especially in the stylist world, where you have all this, where style's involved, a very robust community. How did you do it? How did you foster a community, and how did you nurture it? And how has that played out for you guys? >> So community is a foundation of Poshmark. And community's our value, not just our customer, but also what we are, and uh, community is what I'm more passionate about, even more passionate than fashion; and that was sort of, in my previous company, the thing that was really highlighted for me. And so we did it very slowly, actually. During the first year of our company, we only had a hundred users, but these hundred users were immersed. And then we went from a hundred to a thousand. Then thousand to five thousand. But very deliberately and slowly. So the end of the first 18 months of our company's life, we had maybe ten thousand users, right? And then we went from ten thousand to 300,000 in the next seven months, then we went from 300,000 to 12 million in the next two years. And today we went from 12 million to 40 million in the next few years, because, once you have sort of figured out how the community is created, it can scale very fast, but the early days if you compromise in how the community is being created, it's very powerful. For example, in the first, probably, eight or nine months in the company, I answered every single customer service email. And today, I probably interact with 80-100 customers directly everyday. Really keeping the pulse in sort of servicing. And service and love are sort of two of our core values, and it is very important that's built into the system. The second thing is, the community has to be authentic. You cannot fake a community. Which means, there is conversations that will happen in the community, there is, which may be antithetical to what you think is your brand, but if you don't let that authenticity happen, then what ends up happening is the community sort of withers away, because people are not going to tolerate anything inauthentic. The third thing, as you mentioned, is trust. And so from day one, we created not just trust in the way platform was built, but also in the economics. So day one we said, hey, if you're going to be part of this platform, there's two things that you're going to pay for; one, is, as a buyer, you're going to pay for shipping, and as a seller, you're going to revenue share with us, and we're not going to charge you any other money. Nothing. And so we shared, started from day one, a 20-80 partnership with our sellers, and today, here we are six or seven years later, and we have the exact same partnership. On the buyers, we started by charging them $7 for shipping, today our shipping is $6.49, at that time our shipping was 3 pounds to 5 pounds. Everything was priority, today everything is priority. So in six to seven years, if you think of any other marketplace in the world, not just in the country, how many times have they raised their fees? How many times have they changed their paradigm, changed their shipping paradigm? For us, it was very important. In the early days, it felt, people were saying, why are you charging so heavily? I said, I don't want to charge anything different tomorrow that I'm charging today, and by the way, there's no additional fees we've ever imposed on the platform, so, we don't have any marketing fees, any promotion fees, any credit card fees, and so that trust that's created ultimately leads to a lot of loyalty. And so today, you see our consumers growing, our users growing, and every single cohort we have continues to grow in revenue more like SAAS businesses, as opposed to e-commerce businesses. And that, to me, is the power of community if you do it right. >> And that's an interesting point. There's a lot of things you said in there, I think, that are worth doubling down on. One, I just want to highlight it, if you're creating value, and you're certainly scaling, passing that down in cost savings, and reducing cost and adding value, that's a secret formula. You see, we know one company that does that really well: Amazon! And that's worked. And they recognize the value of keeping people in there engaged, and so I think that's almost a take away for anyone watching is that if you're not adding value and reducing the costs while you're scaling, you're probably doing your math right. >> Absolutely. >> The second thing I want to talk about, and get your reaction to is you know about community and slowing it down at first. That's almost counter-intuitive. The, almost the answer is put the pedal to the metal, let's get some numbers; you took a different approach. You decided to take your time. Was that to get a feeling for the community, build the trust, understand the dynamics? Talk about why you went slow at first. >> The key is that the first two, three years, you're perfecting a lot of things, right? You have to make sure things are getting right. And in the first year, it was all about getting the product right, right? Then we scaled. Then we quickly realized that that scaling was breaking everything, was breaking our shipping system, was breaking our technology's office; I actually, Mayfield, which was an early investor in Poshmark, was on the board, and I went to my board, and I said you know, I'm actually going to slow down growth by 60%. And if you can imagine a venture board hearing that from their CEO, in the early days, it's challenging. >> It's a tough conversation. >> Yes. But I think one of the things that I value about Mayfield and my early investors is their focus on partnership, at a people level, a human level, with me. And uh, trust, and so we actually cut down our marketing budget by 80%, filled out the systems, got the partnership with USPS where we created the country's first fashion shipping label called Poshpost, and built up our technology and infrastructure, built out our payment partnership with BrainTree and Paypal, and by sort of, early-to-mid 2014, we started scaling and have never stopped. And in fact, I had told my investors early on, that first two or three years of building this business will be challenging, so hopefully you are prepared to go on this journey with me; but once we build it, it will accelerate. And what you see with us is, the business continues to accelerate every quarter, and we are seeing hyper growth, six, seven years into the business, which is even faster than the growth we saw in the first few years. And part of it is that, network business, which are built around true sort of networks, continue accelerating and connects later on in the process, but if you haven't created the right foundation in the early days? They fall apart. >> I think that's a lesson that entrepreneurs can learn, because you got to go slow to go fast. In Cloud based businesses where you have network effects, if there's a crack in the foundation, it can come crumbling down. >> It can come completely crumbling down, and it did, I mean, there were times in 2013 when people were literally doing things and just, the data would get lost in other things. We had to fix many of those, the broken pieces. We had USPS come to our offices and say hey, either you pay us a multi-million dollar fine or we have the right to arrest you. We had to renegotiate our contract with them. There's a bunch of things that happen in that scaling, and you hear things like blitz scaling and stuff these days, and their great terms, but at the same time, if you don't fix what's broken, you can't build that super scalable business. >> You got to be ready to blitz scale. As you know, Reid Hoffmann's famous channel, Masters of Scale, points out, which, by the way, is a great program, but, if you're not ready, you can crash and burn big time. That's a good point. You know, I have conversations a lot with a lot of senior people, one of them Theresa Carlson, who runs Amazon Web Services Public Sector Cloud business, she talks about doing the hard work upfront. And, you know, she's using public sector, so you have to get those kind of certifications, it sounds like this is a lot of things that you had to do. How did that test your entrepreneurial spirit? I know you, and you're hard-charging, but you're pragmatic and we can see that. But taking the time to do the work can sometimes test the patience of the team and the entrepreneur themselves. What's your reaction to that? >> Um, I would say that, you know, when we started Poshmark, the mission was that can we serve a hundred million people. In the country, you know, not even around the world. In our way we have 40 million people. From day one what we saw was deep engagement in the platform, because of the level of usage we had, because of the level of, sort of, activation we had, we knew we were on to something. I'll share a small episode with you, which convinced us that we've touched a deep nerve within the community is, in May of 2012, we were barely, you know, six, seven months into our app being launched in the public space, and we had maybe five or ten thousand users. At that time, we were adjusting our shipping for the first time, and uh, literally we announced the, we had launched the product with a small discount on the shipping, we were going to take it back, and we just said, you know, we're going to take it back. We got 200 plus emails which ranged from, you know, you're going to take away my entire set of clothing, and my entire business and we barely thought we were even launched, and so we knew we were servicing something very deep. That commitment to servicing the community where you are, really helping people at a deep level, allowed us to ride through these crazy ups and downs. And there was a point of time we went along the valley, even though we had the initial funding, in the mid stages of it we got over 200 rejections in the paradigm; sometimes multiple by the same investors. And so, it was definitely not a smooth ride in the middle of building this company. But that sort of passion for community and what they were experiencing kept us going. >> Let's talk about People First and venture capital. And one of the things I'm impressed on with this program we're doing with Mayfield is, and theCUBE has newer effect as well in the community, it's a people-centric culture. We lived through the social media early days when social and democratization was happening. More than ever now, you're seeing the role of people, because we're all connected. So there's rapid communications, there's frictionless, for people to yell and/or raise their hand and give accolades as well. So you have now a social dynamic with the fabric around the world. People can transact and communicate, complain, you know, applaud. This is changing everything. How is that change your outlook on life, because you have to recruit people, they want to work for a company that's people-centric, they want to work for a mission-driven company. These are the new dynamics we're starting to see in this generation; how has People First impacted your core mission? >> So for me, life is all about people. This company's all about people. We serve people, people is one of our core values. And my connection with Mayfield, which is through Navid, started back, actually, in my previous company. At the very beginning of that journey, '04/'05, uh, and we tried to partner up but the timing was never right, so when we were starting Poshmark, Navin was the first one with a term sheet, even before he'd sort of seen the business idea. And to me, that was a huge belief in me and the team I could put together. And I have the same sort of feelings about the people we bring on into the company, where uh, many of my team members here, including two of my co-founders, were involved with me in Kaboodle. One of them was a co-founder in Kaboodle. The first 20, 30, 40 people, I think, in the company, are still here seven or eight years later. They were people who are now playing very senior roles in the company, where they've gone through their ups and downs and we are always behind, two or three people left and we recruited them back into the company. So I think at the end, life, anywhere, but particularly in today's world, is so much about people and relationships. And it's the same thing we did to our community. I mean, uh, we just finished our sixth annual user conference, which was six times bigger than our first one. What was amazing was, they were so many people who were there in the first conference who had been coming to all the six conferences, and they are now like mini-celebrities in the community. And so, it's just amazing to see how a focus on people can be both rewarding at a business level, but also very gratifying at a personal level. >> It's nice to see you hit that tipping point. Congratulations on your success, it's great to see. You're a great entrepreneur. I want to ask you the question around funding, because I know, we've both been through venture capital fundings, we've been through this point building this great company you run now, and you've actually hit massive growth to a whole other level, your challenge today and going forward. This is, given it's Mayfield's 50th anniversary, you've seen a lot of changes in venture capital. A rounds used to be A rounds, now there's B and pre-C, there's all kinds of nuance, and now you have alternative funding now and global landscape you're seeing block chain and cryptocurrency, although ICO's have taken a bath because of the regulatory issue. Issues around regulation, some scams out there, actually. But venture capital's been tried and true. What's changed in venture capital the past 25 years in your view? >> I think, two things, which have happened, particularly in the last seven or eight years is there's a lot of it. And secondly, it favors the mighty more than the weak. And so, those are sort of the two big changes that have happened in the venture capital business. I think you were just mentioning is the people I used to work with, a whole range of investors, are now investing in post-growth stage funds. I mean, the same company. So everyone is sort of leveled up and leveled up and then leveled up, you know? You see venture capitalists raising two, three, four billion dollar funds; I mean, that's not venture capital, there's no way you can deploy that at the venture stage. A company is staying private much longer at different scales, which I think is probably more sort of a sign of the times. And finally, I think, it is the metrics and the scale that your business can achieve, that these are obviously very aware of, is an order of magnitude bigger than it has ever been. In fact, sort of, in some ways, unicorn, being the unicorn is uh, as sometimes as people joke, sometimes an insult. You need to be a deca-unicorn these days. So the feeling of not being enough is constant. >> And that's challenging, too, for the venture industry, because, you know, there's still the classic building blocks of entrepreneurship and venture architecture, which is, you start with an idea and you get a prototype, and certainly it's easy to get on the Cloud computing certainly, a great win for the entrepreneur; so I can see maybe some acceleration. But at the end of the day, it's still the classic blocking and tackling with building your company. >> Yes. >> Building a durable company. >> Absolutely. And you and I have both seen the '98, '99, 2000 timeframe, you know, everyone believes nothing repeats, and, you know, we certainly see, maybe not exactly the same thing, maybe it's an order of magnitude less, but there's definitely some level of exuberance we see today. But if you're building a fundamentally good business, that has robust economics, that can scale, and is based on foundational principles, with a large sort of market, I don't think that we are wrong in terms of deploying massive amounts of capital up against it. But at the same time, um, I think it also creates certain socioeconomic, as well as responsibility challenges, that I don't think we are fully facing up to, as an economy, and as a Valley. >> You've raised over a hundred million plus, so you have done some funding. A lot of funding, you have a lot of cash you've raised. When you had to go through those exercises of looking at the fundraising, 'cos, you don't want it to die on the mind, you're building a durable business, you have to go through multiple rounds of fundings. What were the key decision points for you as you started to look at this fundraising process to build your business? >> See, in the early days it was literally just about survival, I mean, there were times where I ran the business on negative balance sheets, right? So it isn't that it's been easy. I was only, I would say, the last funding round was the one that was easy, where we got multiple term sheets proactively, and the first couple of them. In between--. >> When things are scaling things are great, you know? >> In the middle of it, every single round was effectively zero to one term sheets. Every single time. We were lucky to have Mayfield as a partner, and some of our early investors like Inventus and Menlo who sort of supported us through each of these pieces of the journey. Mayfield as an anchor point. But it was really, really hard. And part of it is that, what we were doing was challenging, so many things still are, that even to process our cohort data is hard. Do you think of it as used, do you think of it as buying, do you think of it as selling, what is it? It looks like a bird, but it moves like a plane, you know? What is it? It's Superman or Superwoman, right? So that being a challenge, uh, only in the last round did we have the freedom, we could raise no money, some money, all of the money, and um, most of the focus for us, for that capital, was really to have the deep pockets that would be required for global expansion. We had actually scaled the business, at that point in time, that we didn't need too much money for domestic expansion. And in fact, not only have we not touched any money from that round, we have not touched any money from the previous round, so far; most of the money from the previous round. And so, again, part of it is you need muscle to compete in a bigger world, but at the same time, if you build a fundamentally sound business, then over time you can scale with or without money. >> And you got SAAS, sellers and service, and network effects booming and great community. That's a great tailwind for you guys, for sure. >> It is a phenomenal tailwind, and in fact, um, I was just in my management team meeting this morning, and I said, you know, we are growing, but we can grow even faster at this point, because the level of network effect we are seeing in the community is an extraordinary effect, where there's sort of second order; our community is opening up Instagram accounts to promote Poshmark to sort of go out to YouTube, so there's sort of this wild, organic movement that's happening across the country, which is just bringing out a whole different level of growth that we've ever seen. >> Yeah, there's a whole new dynamic it seems. It's interesting, I'm seeing, and not a lot of people writing stories about it are documenting it, but Masters of Scale has a whole different perspective, but no one's really talking about something that you guys are touching upon, and we're seeing it in our business. Creating an environment that has network effects, and community, and good content in this case, product for your end. Um, creates a flywheel. And what's interesting is, in this new era of people who can create value, with the ability to capture it, is really a unique formula, and I think this is the new kind of management discussion. Certainly lower prices, increased value, that's an Amazon effect. That's a, lacking the words, good example, well-documented, you do that, you're good, you're doing it, but now you have the ability for people to create value. Who can then capture it. This is almost a whole 'nother big wave. Your reaction? >> I think the power of people today is at a very unique level, right? And it can go in the negative direction, but when you harness it from a positive perspective, it's phenomenal. And to me, you know, we've started added a fifth core value recently, is that at the end, the true happiness comes from service of others, right? And if you service everyone, in our job, you're servicing our community, who's then servicing other people, and that creates an amazing sort of paradigm. And if you remove the conversation of money, because it's taken care of, it's built into the platform, then it just keeps sort of circulating. And I think that's something that people underestimate. And one of the things that you, you know, you see is that, for example, open source software, right? You start by focusing on community and then it becomes all about money, and then you forget about the community and you see many of the larger open source companies slow down, because they forget the fact that what brought them there was the community. And to me, I think--. >> If they get greedy, the project's fail. >> Exactly, exactly. And so, the hardest thing at scale to balance is how do you make sure that you're still focused on the community? >> Great stuff! Final question for you. You know, these days, with venture capital, the question always is, where's the value at? Talk about your experiences with Mayfield, and what differentiates a value add versus a value subtract investor? When should an entrepreneur feel it? What's the tell signs of someone's got a value add, and partner is not? >> I think, I think Mayfield is so aligned in so many ways with our core values, which is focus on people and focus on service, that it's just been an amazing partnership with them. You know, even in our lowest moments, I knew that we would get funded; I didn't know how it is, because I knew that Navid and Mayfield would figure out a way, so I never sort of worried about the capital after I brought in Navid and saw him in action for a year and a half. And if you're a venture capitalist, you need to provide capital! And forget about any of the services, many VCs fail that one task, which is to provide capital when you most need it, right? But beyond that, it's been a great resource. I mean, I met my co-founder through Mayfield. Tracy and I were first introduced via Mayfield. Many of our recruiting of the top executives have come from Mayfield, but they're always available as a sounding board across the pieces, so I do think that they take their service paradigm to a whole new level. >> And they support you, too, right? The support's there? >> Support and they have an HR partner who's helped, I think, with some of the recruiting issues, hiring the recruiting partnerships, et cetera. PR, other areas as we needed it. Somebody that you could call on, too, even if it was just talking about searching for a general counsel, and Mayfield has been great, even in that. Help, at this late stage of a company, so it's fantastic. >> It's a great network; people, value, paying it forward. Manish, thanks for coming on, sharing your insights, here as part of theCUBE's 50th People Network with Mayfield. Thanks for sharing your experience. >> Thanks for having me! It's been a pleasure and joy to see you after so many years as well! >> This is theCUBE here on Sand Hill Road at Mayfield for their 50th Anniversary as a Venture Capital Firm, sharing insights and ideas from entrepreneurs, and tech executives. I'm John Furrier, thanks for watching! (electronic music)

[Music] welcome everyone to thecube's presentation of the aws startup showcase data as code this is season two episode two of our ongoing series covering exciting startups in the aws ecosystem to talk about data and analytics i'm your host lisa martin i have a cube alumni here with me socket sarah the ceo and founder of nexla he's here to talk about a future of automated data engineering socket welcome back great to see you lisa thank you for having me pleasure to be here again let's dig into nexla's mission ready to use data in the hands of every user what does that mean that means that you know every organization what what are they trying to do with data they want to make use of data they want to make decisions from data they want to make data a part of their business right the challenge is that every function in an organization today needs to leverage data whether it is finance whether it is hr whether it is marketing sales or product the problem for companies is that for each of these users into each of these teams the data is not ready for them to use as it is there is a lot that goes on before the data can be in their hands and it's in the tools that they like to work with and that's where a lot of data engineering happens today i would say that is by far one of the biggest bottlenecks today for companies in accelerating their business and being you know truly data-driven so talk to me about what makes nexla unique when you're in customer conversations as every company these days in every industry has to be a data company what do you tell them about what differentiates you yeah one of the biggest challenges out there is that the variety of data that companies work with is growing tremendously you know every sas application you use becomes a data source every type of database every type of user event anything can be a source of data now it is a tremendous engineering challenge for companies to make the data usable and the biggest challenge there is people companies just cannot have enough people to write that code to make the data engineering happen and where we come in with a very unique value is how to start thinking about making this whole process much faster much more automated at the end of the day lisa time to value and time to results is by far the number one thing on top of mind for customers time to value is critical we're all thin on patients these days whether we're in our consumerizer our business lives but being able to get access to data to make intelligent decisions whether it's on something that you're going to buy or a product or service you're going to deliver is really critical give me a snapshot of some of the users of nexla yeah the users of nexla are actually across different industries one of the main one of the interesting things is that the data challenges whether you are in financial services whether you are in retail e-commerce whether you are in healthcare they are very similar is basically getting connected to all these data systems and having the data now what people do with the data is very specific to their industry so for example within the e-commerce world or retail world itself you know companies from the likes of bed bath beyond and forever 21 and poshmark which are retailers or e-commerce companies they use nexla today to bring a lot of data in uh so do delivery companies like dodash and instacart and you know so do for example logistics providers like you know narwhal or customer loyalty and customer data companies like yacht pro so across the board for example just in retail we cover a whole bunch of companies got it now let's dig into you're here to talk about the future of automated data engineering talk to me about data engineering what is it let's define it and crack it open yeah um data engineering is i would say by far one of the hottest areas of work today the one of the hardest people to hire if you're looking for one data engineering is basically um all the code you know the process and the people that is basically connecting to their system so just to give a very practical example right for um for somebody in e-commerce let's say a take-off case of door dash right it's extremely important for them to have data as to which stores have what products what is available is this something they can list for people to go and buy is this something that they can therefore deliver right this is data that changes all the time now imagine them getting data from hundreds of different merchants across the board so it is the task of data engineering to then consume that data from all these different places different formats different apis different systems and then somehow unify all the data so that it can be used by the applications that they are building so data engineering in this case becomes taking data from different places and making it useful again back to what i was talking about ready to use data it is a lot of code it's a lot of people not just that it is something that runs every single day so it means it has monitoring it has reliability um it has performance it has every aspect of engineering as we know going into it you mentioned it's a hot topic which it is but it's also really challenging to accomplish how does nexla help enable that yeah data engineering is quite interesting in that one it is difficult to implement you know the the necessary sort of pieces but it is also very repetitive at some level right i mean when you connect to say 10 systems and get data from them you know that's not the end of it you have 10 more and 10 more and 10 more and then at some point you have thousands of such you know data connectivity and data flows happening it's hard to maintain them right as well so the way nexla gets into the whole picture is looking at what can we understand about data what can we observe about the data systems what can be done from that and then start to automate certain pieces of data engineering so that we are helping those teams just accelerate a lot faster and it i would say comes down to more people being able to do these tasks rather than only very very specialized people more people being able to do the tasks more users kind of democratization of data really there can you talk to us in more detail about how naxa is automating data engineering yeah i think um you know i think this is best shared through a visual so let me walk you through that a little bit as to how we automated engineering right so if we think about data engineering three of the most core components are many parts to it but three of the most core components of that are integrating with data systems preparing and transforming data and then monitoring that right so automating data engineering happens in you know three different ways first of all connecting connecting to data is is basically about the gateway to data the ability to read and write data from different systems this is where the data journey starts but it is extremely complex because people have to write code to connect to different systems one part that we have automated is generating these connectors so that you don't have to write code for that also making them bi-directional is extremely valuable because now you can read and write from any system the second part is that the gateway the connector has read the data but how do you represent it to the user so anybody can understand it and that's where the concept of data product comes in so we also look at auto generating data products these become the common language and entity that people can understand and work with and then the third part is taking all this automation and bringing the human in the loop no automation is perfect and therefore bringing the human in the loop means that somebody who is an expert in data who can look at it and understand it can now do things which only data systems experts were able to do before so bringing in that user of data directly into the into the picture is one important part but let's not forget data challenges are very diverse and very complex so the same system also becomes accessible to the engineers who are experts in that and now both of these can work together while an engineer will come through apis and sdk and command interfaces a data user comes in through a nice no code user interface and all of these things coming together are what is accelerating back to that time to value that really everybody cares about so if i'm in marketing and i'm a data user i'm able to have a collaborative workflow with the data engineer yeah yeah for the first time that is actually possible and everybody's focuses on their expertise and their know-how so you know um somebody who for example in financial services really understands portfolio and transactions and different type of asset classes they have the data in front of them the engineers who understand the underlying real-time data feeds and those they are still involved in the loop but now they are not doing that back and forth you know as the user of data i'm not going to the engineer saying hey can you do this for me can you get the data here and that back and forth is not only time taking it's frustrating and the number one hold back right yeah that and that's time that nobody has to waste as we know for many reasons talk to me about when you look into your crystal ball which i'm sure you have one what is the future of of data engineering from nexus perspective you talked about the automation what's the future hold i think the future of data engineering becomes that we up level this at a point where um companies don't have to be slowed down for it um i think a lot of tooling is already happening the way to think about this is that here in 2022 if we think that our data challenges are you know like x they will be a thousand x in five years right i mean this complexity is just increasing very rapidly so we think that this becomes one of those fundamental layers you know and you know as i was saying maybe the last time this is like the road you know you don't feel it you just move on it you do your job you build your products deliver your services as a company this just works for you um and that's where i think the future is and that's where i think the future should be we all need to work towards that we're not there yet not there yet a lot of a lot of potential a lot of opportunity and a lot of momentum speaking of momentum i want to talk about data mesh that is a topic of a lot of excitement a lot of discussion let's unpack that yeah i think uh you know the idea that data should be democratized that people should get access to the data and it's all coming back to that sort of basic concept of scale companies can scale only when more people can do the relevant jobs without depending on each other right so the idea of data democratization has been there for a long time but you know recently in the last couple of years the concept of data mesh was introduced by zamak digani and thoughtworks and that has really caught the attention of people and the imagination of leadership as well the idea that data should be available as a product you know that democratization can happen what is the entity of the democratization that's data presented as a product that people can use and collaborate is extremely powerful um i think a lot of companies are gravitating towards that and that's why it's exciting this is promising a future that is you know possible so second speaking of data products we talked a little bit about this last time but can you really help us understand see smell touch feel what a data product is and give us that context yeah absolutely i think uh best to orient ourselves with the general thinking of how we consider something as a product right a product is something that we find ready to use for example this table that i'm using right now made out of raw materials wood metal screws somebody designed it somebody produced it and i'm using it right now when we think about data products we think about data as the raw material so for example a spreadsheet an api a database query those are the raw raw materials what is a data product is something that further enriches and enhances that entity to be much more usable ready to use right um let me illustrate that with a little bit of a visual actually and that might help okay um the idea of the data product and this is how a data product looks like in next lab for a user to write as you see the concept of a data product is something that first of all it's a logical entity this simply means that it's not a new copy of data just like containers or logical compute units you know these data products are logical entities but they represent data in the same consistent fashion regardless of where the data comes from what format it is in they provide the user the idea of what the structure of data is what the sample data looks like what the characteristics of data are it allows people to have some documentation around it what does the data mean what do these attributes you know mean and how to interpret them how to validate that data something that users often know in an industry how is my data looking like well this value can never be negative because it's a price for example right um then the ability to take these data products that you know we automate by generating as i was mentioning earlier automatically creating these data products taking these data products to create new data products now that's something that's very unique about data you could take data off about an order for a from a company and say well the order data has an order id and a user id but i need to look up shipping address so i can combine user and order data to get that information in one place so you know creating new data products giving people access hey i've designed a data product i think you'll find it useful you can go use that as it is you don't have to go from scratch so all of those things together make a data product something that people can find ready to use again and this is this is also usable by the again that example where i'm in marketing uh or i'm in sales this is available to me as a general user as a general user in the tool of your choice so you can say oh no i am most familiar with using data in a spreadsheet i would like it there or i prefer my data in a tableau or a looker to visualize it and you can have it there so these data products give multiple interfaces for the end user to make use of it got it i like it you're meeting the user where they are with relevant data that helps them understand so much more contextually i'm curious when you're in customer conversations customers that come to you saying saka we need to build the data mesh how is nexl relevant they're how what is your conversation like yeah when people want to build a data mesh they're really looking for how their organization will scale into the future uh there are multiple components to building a data mesh there's a tooling part of it the technology portion there are people and processes right i mean unless you train people in certain processes and say hey when you build a data product you know make sure you have taken care of privacy or compliance to certain rules or who do you give access to is something you have to follow some rules about so we provide the technology component of it and then the people and process is something that companies you know then as they adopt and do that right so the concept of data product becomes core to building the data mesh having governance on it uh having all this be self-serve it's an essential part of that so that's where we come into the picture as a as a technology component to the whole story and working to deliver on that mission to getting data in the hands of every user you mentioned i want to dig into in the last few minutes here that we have uh the target audience you mentioned a few by name big names customers that nexla has you i heard retail i heard e-commerce i think i heard logistics but talk to me about the target customer for nexla any verticals in particular or any company's sizes in particular as well yeah you know the one of the top three banks in the country is a big user of nexla as part of their data stack uh we actually sit as part of their enterprise-wide ai platform providing data to their data scientists um we're not allowed to share their name unfortunately but um you know there are multiple other companies in asset management area for example they work with a lot of data in markets portfolio and so on um the leading medical devices companies using nexla data scientists there are using data coming in real time or streaming for medical devices to train and um and combine that with other data to do sort of clinical trial related research that they do um we have you know the companies for example linkedin is an excellent customer linkedin is by far the largest social network um their marketing team leverages nexla to bring data from different type of systems together as well um you know so are companies in education space like nerdy is a public company that uses nexla for you know student enrollment education data as they collaborate with school districts for example um you know there are companies across the board in marketing live brand you know for example uses nexla so we are um we are you know from who uses nexla is today mostly mid to large to very large enterprises today leverage nexla as a very critical component and often mission critical data for which they leverage us do you see that changing anytime soon as every company these days has to be a data company we expect that as consumers whether it's my grocery store um or my local coffee shop that they've got to use data to deliver me that personalized experience do you see the target audience kind of shifting down to more into mid-market smb space for next level oh yeah absolutely look we started the journey of the company with the thinking that the most complex data challenges exist in the large enterprise and if we can make it no code self-serve easy to use for them we can bring the same high-end technology to everybody and this is exactly why we recently launched in the amazon marketplace so anybody can go there get access to nexla and start to use it and you will see more and more of that happen where we will be bringing even some free versions of our product available so you're absolutely right every company needs to leverage data and i think people are getting much better at it you know especially in the last couple of years i've seen that teams have become much more sophisticated yes even if you are a coffee shop and you're running campaigns you know getting people yelp reviews and so on this data that you can use and understand better your demographic your customer and run your business better so one day yes we will absolutely be in the hands of every single person here a lot more opportunity to delight a lot more consumers and customers socket thank you so much for joining me on the program during the startup showcase you did a great job of helping us understand the future of automated data engineering we appreciate your insights thank you so much lisa it's a pleasure talking to you likewise for soccer sarah i'm lisa martin you're watching thecube's coverage of the aws startup showcase season two episode two stick around more great content coming up from the cube the leader in hybrid tech event coverage [Music]

>>Hey everyone. Welcome to this cube conversation featuring next law. I'm your host, Lisa Martin. And today we are joined by Sukkot Sarab CEO and founder of next, next LA Sukkot. Great to have you on the program, >>Lisa, thank you so much for having me here really excited about this. >>Tell us a little bit about next level. What is it that you guys do? >>Yeah. Um, you know, we are in the world of data and one of the biggest challenges that we face, um, as an industry is there is so much data, so much variety. How do we really get it into the hands of people who use data? And, um, the users of data are all across. You know, they shouldn't have to be engineers. They are across the board in different functions. So next, last purpose and mission has always been ready to use data in the hands of the users. So, um, what misled us today is makes it possible for users across the board, whether those are data scientists, whether those are data analysts, whether those are people in various business functions to get the data that they need in the tools that they work with. So, um, we make that possible in a very, no code way, um, for users to get access to the data. Um, and very uniquely actually do that by automating a lot of the data engineering process. We'll talk more about that, but it's an exciting space to be in. >>It is an exciting space to be in. And of course that the volumes of data could just continue to explode and there's, that will not be slowing down anytime. Soon, as we know in businesses, one of the things we saw in the last two years was businesses pivoting so many times and really needing, going from survival mode to thriving mode, but the ability to harness the power and the insights and data is critical for businesses to be successful these days as consumers. We just expect that if it's our business life or personal life, whoever we're interacting with is going to know what we want, and we're going to be able to display that to us quickly. We think about data match. It's a relatively new concept, right? Talk to me about data mesh and what differentiates next left from your competition. >>Yeah. Um, so data mesh is essentially, I would say in the lineage of the concept of democratizing data, the idea has always been that data should get to the users. Now for a long time, these users were dependent on it and engineering to get the data to them. So what the data mesh is doing is it's bringing a framework by which users of data. We call them data, the domains, the different functions that use data. They can have the data to use themselves. They can manage things on their own. And I think that is allowing for a framework in which teams can truly scale. I mean, that bottleneck of depending on engineering to do everything for you is just not going work. And I think in the last two years, even more so we saw that as companies tried to move fast, it started to break down. And I think there is a lot of momentum around this concept of data mesh. For this reason, people are finding that this concept is what can help them scale >>And how does next SLA deliver that single tool so that you can really democratize data and give people with varying levels of technical fluency, the access that they need. I can imagine finance folks with ERP data marketing folks with CRM data. How do you do that with a single tool? >>Yeah. So, um, I think the key thing about getting data in the hands of users, as we think about data democratization has been that, how does it actually happen? How do you give people access to the data? You know, simply giving them passwords to systems is not enough right now the data mesh concept comes with the understanding that there should be an entity, which we call it a data, product data, you know, a data product becomes that sort of common entity that becomes something that people can get access to. They can use, they can collaborate on. Now, what is a data product becomes an important question, of course, and how do we get a data product? So our next step comes in in a very key way is we automatically generate these data products. So again, going back to the thinking that look there, there is not going to be enough engineers to write code for everything. What we are able to do is to say that we can actually, you know, connect to data systems, look to the data, understand it, and package it up as a product, as a data product. And that data product is a core element of the damage. I'm happy to share what a data product is, if it helps people understand and of, >>Yeah. Let's double click into that a little bit. I was noticing on your website about next sets and I wanted to know what that is and how does it reimagine data, product creation. >>Yeah. Um, so let me just break down a little bit about what is the data product in the first place, right. I mean, as consumers, we use products all the time, you know, I'm, I'm, my laptop is here on our desk and that is a product. It is a product made from raw materials, like wood and metal and screws, right. And somebody designed the product, somebody built it and I'm using it. So if we think of the same parallel in the world of data, then API APIs and files and database tables, those are the raw materials. Um, if somebody takes that and packages that up into something that other people can use easily, that is the concept of the data product. Now, what, how is it different from data? Well, you take the core data and you put things around it. Like, what is the distribution of data? >>What is the structure of it? You know, what are the validations that make it work, how to better manage that, who has access to it when you take that raw material and put all of those other structures, it that's when it sort of becomes a data product. And the next step concept in next door is essentially a manifestation of that. It is the concept that these data products do not need to be new copies of data, which is a huge pain by the way. But instead they can be these logical entities. So if I can take us back to the world of compute, where we understand the concept of containers, no, these containers are basically a logical NPP that gives us access to the computation resources. Think of next set as a very similar thing, a logical entity that gives us access to the data resources. And, um, this is something that, you know, we have been able to innovate and automate in such a way that today, when people think of the data mesh and they want to build that, they see us as a component in that whole framework. So data mesh is a much broader framework, but we are sort of the building block for that, through this concept >>Building block. Got it. Talk to me about where your customer conversations are happening. Are they within chief data officer chief information officer? Is it within the C-suite as data is every company these days has to be a data company. >>Oh yeah. Very much in the C-suite. Right. So again, this changes a little bit industry by industry because every industry is organized differently. Um, for example, you know, we have some amazing customer international services there. The conversation often is this the chief data officer or the chief analytics officer. And the key thing that the C suite is thinking is how does this work in the future? How do you know the scale of data challenges are, is the growth of that is so fast. How do we handle things to three years, five years from now? And that's where the strategic conversation is. And that's where things like data mesh become extremely important for companies where we talked to them about, you know, how our technology sort of enables that, right? Um, across other industries, the functions may vary. And one of the things which is very interesting with data, um, compared to other technologies is that it touches almost every aspect of business. It's not limited to engineering. It is your person in HR who is doing HR analytics, source candidates, and profiles are reviewing and all that stuff to finance, to operations, every aspect of business does touch data. So this has to be done in a language and a mechanism that's much more approachable. >>It's gotta be horizontal for all of those different types of users, right. To be able to understand so that ultimately not only did they get access to the data, but they can pull out those insights faster than their competition, whether it's to develop new revenue, streams, new products, new services, you know, the, the person on the other end or the companies on the other end are expecting that real-time interaction. >>Yeah. Yeah. But that's >>No longer a nice to have >>No longer likes to have. And to clarify, right. I mean, the use of data is in multiple ways, right? So analytics is a big use of data, which is how is my business doing and running. Um, we have customers like, um, you know, um, Marchex and Poshmark and bed bath beyond and so on. We'll use us heavily to bring data for the analytics use cases as our companies, for example, like a door dash or Instacart, but that data feeds operational purposes, operational purposes, meaning, understanding the availability of inventory or products across different stores. Not that data has functioned to say, well, if I know what products are available, then I can list them. Then I can go pick them up. And that's not a analytics use case alone. It has a, um, you know, it has an operational use case, right? Um, similarly we see that in audit tracking, we have customers, for example, like Narvar that use us to connect to different shipping tracking system. So the applications of data are in analytics. There are certainly also in operations, which is core business. And they're also, of course, in data science. There's no question that the extension of analytics from looking back on how business is doing to data science, which is, you know, what should we be doing and how should we be more intelligent? So it's across the board, >>Across the board, horizontal, all industries really need to do this, but one of the things that pop into my mind as you were walking through that example was the supply chain challenges that we're all experiencing right now. How can next help organizations mitigate some of the challenges that are going on? >>I think what happens is, you know, technologies like ours, which are the data layer are at a fundamental foundational level. One of the things about next slide is that we are able to bring a data into a much more real time usage. So where in companies, but traditionally moving data on a much more sort of periodic basis. We are our plumbing under the hood. We are completely in real time, which means that we are allowing companies to now get access to that data in a faster way where possible. So again, this is not something that can be fixed overnight, but the role that data can play in is better visibility. Um, and better visibility means those business decisions are being made earlier at the right time. It's more insight. And hopefully that eventually leads to sort of, um, much more efficient, actual on the ground, some movement of products and so on. >>Yeah. That visibility is absolutely critical regardless of the global climate. Right. Talk to me last question here, since we're almost out of time, give me a little bit about your AWS partnership and then talk to me about what's next for next time. >>Um, you know, as, as a technology provider, we ended up, um, running a lot of our own infrastructure on AWS as do many of our customers. And, uh, we have been an AWS partner for multiple years, but very decently, we actually made our product available on AWS marketplace, which means that the access to our technology has become so much easier for companies. Now, uh, next law has started its journey focusing on mid to large enterprises and some of the most complex use cases out there from some of the biggest banks to some of the biggest companies in marketing to some of the core companies in retail, logistics and so on. Now what is happening is that the powerful nature of our product and the ease of use that we have given that need is coming further and further earlier in the life cycle of companies, right? So today new companies are starting up, which said, which are saying that we need to make that sort of investment in data infrastructure earlier. You know, and that's why we have seen even some very small, early startups starting to use next level to come to us for our technology. So we are very much partnered up with AWS because AWS covers the whole gamut from companies that were started yesterday to extremely large enterprises, um, and bring our technology accessible to them. >>Excellent. Well, thank you so much for joining me. It sounds like a tremendous amount of momentum and opportunity at Nexa. We appreciate your insights and best of luck to you. We look forward to hearing more. >>Thank you, Lisa. It's a pleasure talking to it's an exciting space. So time flies, when we talked about that, >>Doesn't it, it really does for sockets sound room. I'm Lisa Martin. You're watching the queue, leave it here for more coverage and a leader in live tech hybrid events.