This episode features an interview with Randy Wigginton, Director of Platform Infrastructure Engineering at Square. Randy was the first programmer at Apple and has experience working at PayPal, eBay, Google, and Chegg. In this episode, Randy talks about what it takes to produce world-changing innovations, how to use data to fully understand your customers, insights into how to compete with tech giants, and much more.
This episode features an interview with Randy Wigginton, Director of Platform Infrastructure Engineering at Square. Randy was the first programmer at Apple and has experience working at PayPal, eBay, Google, and Chegg.
In this episode, Randy talks about what it takes to produce world-changing innovations, how to use data to fully understand your customers, insights into how to compete with tech giants, and much more.
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Ben Wilson: [00:00:00] Hello, and welcome to rise of the data cloud. This episode features and interview with Randy Wigington director of platform and infrastructure engineering at square. Randy was an early programmer at Apple and has experienced working at PayPal, eBay, Google, and check. On this episode, Randy talks about what it takes to produce world changing innovations.
How do you use data to fully understand your customers insights of how to compete with tech giants and much more? So please enjoy this interview between Randy Wigginton director of platform and infrastructure engineering at square and your host, Steve Hamm.
Steve Hamm: [00:00:42] No, it's when I think back we met each other in Las Vegas. Just before COVID. I mean, I think we also saw each other. In Scottsdale, ah, both of these with snowflake and you know, it just seems like eons ago and it was just a few months. it's just, the world has just
Randy Wigginton: [00:01:08] changed. I have a friend who says that it is not July or August.
It is like March 157 or something like that.
Steve Hamm: [00:01:16] I know. I know. It's just been, it's been an amazing thing. But, you know, one of the things I really enjoyed talking to you about when we first met was the fact that you have worked for a number of notable technology companies, Apple, eBay, PayPal, Google, all of these before square.
And you're still a young man. So I don't know how you've done this, but would you tell us a little bit about the beginning of your career? You know what? It was like to be an Apple on the ground floor.
Randy Wigginton: [00:01:49] The way I got to Apple is actually pretty interesting. I learned about programming in a summer school class fell in love and really wanting to have a computer of my own.
There were two big problems with that. One is the computers cost a fortune and we're basically the size of a refrigerator. And I was 13 and my, the parents were not about to buy me one. So I spent a lot of time at the library and calling area companies to learn about computers and to see if they would give me free time to work on a computer.
Computer timesharing was a big thing back then from all of this research, I learned about a little group that got together every couple of weeks up at Stanford. Talk about computers and how to build your own. And that group was the Homebrew computer club. Intel just released the ADHD and crazy nerds like me.
We're figuring out how to build a home computer of their own. So I conned a slightly older friend into driving me to the, these Homebrew computer club meetings a few times. I love the meetings. I mean, I felt like these were people that I totally understood. I was probably the youngest person there, but.
It was wonderful for me, but after a couple of times, my friend was like, so thoroughly bored that he refused to drive me anymore. So I stood up at a meeting and asked if there was anyone that lived near homestead high school that could give me a drive to these meetings because I was too young cab driver's license.
And the super nice guy came up to me at the break and said he just lived down the street at Villa Sarah apartments. And if I walked over there, we could carpool together. I thanked him and asked him again for his name. He says, my name is Steve, but my friends call me was, so that is how I met Steve Wozniak actually a few years before Apple even started.
When Apple officially started in January, 1977, I was their first programmer. I would get up about five in the morning. Drive to the office. I worked for a few hours then drive after school, go back to the office and work several more hours. That was the greatest thing ever.
I was 16 at that time, Apple grew really quickly, I worked on pretty much everything that company shipped for the first three to four years. Eventually one day, uh, Steve jobs came to me and asked me to work on his latest project, the Macintosh.
So I joined the Macintosh team and ended up writing the word processing program Mac. Right. That was part of the initial Macintosh launch. That was a, that was a wild experience. Yeah. I've been very fortunate.
Steve Hamm: [00:04:22] Yeah. Well, you've been at all of these incredibly innovative companies, and at a time when they were very innovative, cause you know, some companies kind of have that big, innovative burst and then they kind of settled out, but you've been there for the peaks.
Are there lessons that you've observed from, from being in the belly of the beast and all of these companies about what it takes to produce world changing innovations.
Randy Wigginton: [00:04:48] there's a number of critical ingredients that go into an innovation that, that level I love when companies say, when they're trying to recruit people, they say, Oh, we're going to change the world.
And it's like, Uh, that doesn't happen very often. And I've been super fortunate to be at several places that have changed, but ingredients. The first one is the original idea, which usually is really simple. In retrospect, for example, when Apple started launching a creating a home computer, or lots of other companies were doing that, that wasn't the magic ingredient.
What is more important is the team that implements the idea. The people are always number one, people are always your most important resource. People make the difference. For example, this is why square has a very rigorous hiring process. You have to have the best people. that's the only way you can retain your edge is to always have great people.
Another critical component of it is just attention to detail. And this was, t Steve jobs, great, super power. Every feature had to work together, which created an overall result far greater than the individual features. And at, at square, we do the same thing, right? We look at every new product in terms of how it, it fits into our overall strategy to make sure everything works together.
And one thing I've noticed is that snowflake has similar approach when they introduced a new feature. It's impressive. How simple and brilliant it is. Yeah. One of my favorite examples of that snowflake is data sharing. I love it. I think it's amazing. It's a simple, yet elegant idea on how to share data between users.
The implementation of data sharing is supernatural and intuitive. The kind of seamless feature. Integration that marks a significant step forward for the industry.
Steve Hamm: [00:06:34] now you started with the device that basically attaches to a computer. Right? But now there are many facets of the business. If you could just kind of touch on the various dimensions of the business that you have now.
Randy Wigginton: [00:06:48] I mean, we're always growing and evolving. But always staying true to the vision of economic empowerment. So, I mean, we started, as you said, with the original square reader, making it for anybody to accept card payment, using their phone or tablet today, we make our own readers. We build tools to empower businesses and individuals to participate in the economy.
the first part, Is the sellers use square to reach buyers online and in person and manage their businesses and access financing. That's like square. We also have cash app, which is an amazing product growing at a ridiculous speed. And they use cash app, bam send store and invest money.
They can use it to buy stocks. They can use it to buy Bitcoin, send money instantly from person to person. And that person has it available to them instantaneously. That's pretty amazing.
Steve Hamm: [00:07:43] Well, that's really cool. So, you know, we talked about, about innovation and you talked about the fact that hiring the right people is the key, because these successful Silicon Valley companies, they don't just invent one thing.
They have to keep reinventing more things and reinventing themselves. So they have to have a culture of innovation and all these ad-ons that square has done. It's just been building out from a central vision. So it. It's really, really is a cool idea.
What is your role now and what are the most significant technology challenges that you face?
Randy Wigginton: [00:08:19] So.
As always my primary job is to support and guide the members of my group. As I mentioned earlier, great ideas are important, but the team is even more critical. People always come first at square. I manage the infrastructure group, which supports our existing legacy data centers, as well as supporting our expansion into the cloud.
We run all of our legacy services in our data center, where our main payment processing is as well as developing new services in the cloud to take advantage of new newer technologies. There. My group's mission is to support all of square enabling company to move fast. My group develops tools and frameworks in order to reduce time to market for everybody, I group also supports what we call the data life cycle.
We are responsible for all the databases used by all the products and all the servers. And. We handle that data, getting it into snowflake. And then we use that data to produce lots of reports.
Steve Hamm: [00:09:18] in a previous conversation, you know, it seems like eons ago, you told me about the stresses you faced in the pre-cloud analytics world. Tell us a little bit about that and about how the data cloud changes things.
Randy Wigginton: [00:09:32] Sure. This is actually a favorite thing to talk about because prior to snowflake, we were running an on premise data warehousing solution.
And when we first started using a system, everything was great. It was super fast and all of our users loved it because our data was really small and not many people were using it, but the users loved it so much. So they started using it more and more, and we had more and more products pouring data into the system.
Everybody thought it was such a great idea. We expanded from a few machines to a full rack, to two full racks and so on the thirst for more performance, more speed, more storage. Constantly increased. And yet our physical data centers space was limited. We had to start limiting when users could use our data warehouse, as well as killing queries that ran too long.
This led to users trying to rebar on those queries and hope they could get an answer before it was killed. Sometimes they would, sometimes they wouldn't. That's led to me having to decide which users to prioritize, which led to lots of hurt feelings and constant requests for being chosen. I mean, it was brutal for all the users.
Those that were able to get their job done had to wait because the system was overloaded and it was particularly bad for those who were not even allowed to do their job. We were just in a horrible position and how to get out of it.
Steve Hamm: [00:10:47] when was it that you started using the snowflake and what was the deciding factor in deciding to use it?
Randy Wigginton: [00:10:53] Well, I mean, we started experimenting with it in 2017. We migrated off of our, on prem warehouse and start using it fully in 2018. The reason that we went to use it is, well, I had a personal reason, which is that, you know, I was not going to be able to continue supporting what we had this company had.
All these reasons. All of our analysts were just furious at not being able to get their job done. And your look, human capital is the most expensive capital of all. We were just wasting so many people's time. So I actually convinced the company to migrate stuff like. The full migration took about eight months to move from our on-prem system on snowflake.
And now I now Stoweflake powers all the decision making at square. We have daily reports on all aspects of the business. Every product owner is a snowflake. See how well their product and their features are performing. And they can see updates every day. I mean, it was. It was the best decision I've made.
Steve Hamm: [00:11:57] Now I understand that you're using stuff like for a lot of different applications, but specifically you're doing some powerful stuff with marketing. Can you delve into that a little bit? Give us some of the gritty details.
Randy Wigginton: [00:12:10] Mmm. Sure. So for marketing, we, um, have a process where we attempt to match names and address for our printed us mail campaigns.
Cause actually mailing physical letters to people is still a huge thing and it's actually very expensive and it's very painful. It used to be a huge project where basically. We would get a list from a third party, SFTP to a server, loaded into our database, do our best to match it against our own data, generate a Delta, download that data as FTP back.
I mean, it's on and on due to the size of the data and overall processing, this process kept breaking and always needed babysitting. We would do our best to run it once per quarter. And we all dreaded when we would have to do that because when we have to clear other users to make room for this job, but now using data sharing and bulk data load and unload, we do it all through snowflake.
It doesn't require any engineers to help and it runs weekly. I mean, that's incredible going from quarterly to being able to run something weekly and. That is a quantum leap and ability and what you're able to do.
Steve Hamm: [00:13:24] No, you're really able to accelerate your business. Help me understand though, who's sharing data with whom
Randy Wigginton: [00:13:32] we have a number of data vendors, sharing data with us that we use to ascertain how good our addresses are.
from the data shared with us were able to learn. Which users are more likely to sign up for square. A, we have a bunch of machine learning algorithms that run across that data. And then as last step, we actually securely share data with the print house who doesn't have to load a separate list or do any sort of server manipulation or anything like that.
They just go directly into snowflake select from the table and. That powers, their print process.
Steve Hamm: [00:14:09] Yeah. That's a great example. Now this is an example of, you know, of. Finding customers, you know, reaching out to customers and landing new customers, but obviously the way the company is set up, you have this cluster of services that are all, you know, any individual customer might use all of them.
So how do you use data to get a 360 degree view of the customer?
Randy Wigginton: [00:14:34] Oh, and that's one of the great. The greatest things about what we have, which is that our analysts are able to probe into the data constantly. And we're able to get unique insights on each seller and able to communicate with each seller, taking into account their unique circumstances, which services they use, which products they subscribe to.
It's also really great when we're up announcing new updates that. We'll particularly assist some sellers. It's great for our customer success group, because when a seller calls in, they can look and see instantly which products they're subscribed to, which also tells them which ones they might benefit more if they subscribe to something else.
You know, for example, CRM, I mean, it is just changed everything.
Steve Hamm: [00:15:23] You have your own CRM application, correct?
Randy Wigginton: [00:15:26] Yes. Yes. Okay.
Steve Hamm: [00:15:28] That's interesting. So how do you compete against, you know, like Salesforce and people like that?
Randy Wigginton: [00:15:33] Oh, I would say we're not really competing against Salesforce. what square is building is more of an ecosystem.
Right? So if you have a bunch of customers that have come to your business, you already have. You know their name and contact information. There's no reason to enter it into a separate system in order to market to them. So what we do is we try and make the marketing to your existing customers or even potential customers.
Super easy. We're not in direct competition with Salesforce. That's
Steve Hamm: [00:16:08] for certain. It's interesting. When I think about snowflake, I mean, they, they compete with some of the most powerful and dynamic and innovative kind of companies in the world. You know, Amazon, Microsoft, Google, just for starters. What's what do you think is the key for technology?
Somebody for the younger ones, the ones that are coming up. I mean, Snowflake's no longer a startup, but. What's the key to competing with these giants in your view
Randy Wigginton: [00:16:37] to never lose your customer focus, to always be obsessive about helping people to have a, a crazy attention to detail and always hire great people those are always the winning. Ingredients
Steve Hamm: [00:16:54] goes right back to Apple.
Randy Wigginton: [00:16:55] Doesn't it? It does
Steve Hamm: [00:16:58] still what they're doing. Lessons. Yeah, some good lessons learned early. That's great. Yeah. Now a lot of your customers, you know, are retailers, restaurants, you know, bars, all of the small businesses that have been hit perhaps hardest by COVID. What, what are you seeing? I mean, are they, are you able to provide any additional help to them or, or are you able to get any additional insights that you can use that.
You know, at some point feedback to them and to their benefit.
Randy Wigginton: [00:17:33] Absolutely. This has been a, an enormous success, a story that when this hit, we actually prepared for everything to dry up. Right? Cause it looked like this country was shutting down and everything was stopping. And what that forced us to realize is that we had the ability to put all of these restaurants and stores.
Online very, very quickly. And even to help them arrange to get a delivery or pickup. So that's what we did. And so many stores and restaurants are thankful to square for pivoting so quickly, enabling them to get online with e-commerce literally in just a matter of hours and start doing pickup like later that day.
So that's been a huge success story.
Steve Hamm: [00:18:28] It's a very interesting thought because you know, these local restaurants, these local shops, they don't, they didn't need online. They didn't need e-commerce because their, their market was local, but suddenly they needed something that they had never needed before and they needed it immediately.
So I think it's really cool that you guys were able to respond so quickly. I mean, in my town, I live in a. You know, small city, 130,000 people, you know, the life of the town was these beautiful restaurants. You know, some of the little shops, all of these were owned by individuals or families and things like that.
And just, you know, anything that can be done. To save these people and their dreams and all the work they've done, I think is just, it's almost like God's work. So I really applaud you guys for, for doing that. Yeah. Yeah, no, you know, I, I have one more question for you, which is, I'm going to ask you to put on your visionary hat and look ahead.
Five years or so whatever's a convenient time. How do you think business use of cloud data analytics is gonna advance over the next five?
Randy Wigginton: [00:19:36] Oh, I think it's going to completely change the landscape of, of data. I think data sharing is just the start. I think as companies learn to operate more together and leverage data from each other, It's going to benefit the consumer in ways that we can't even imagine.
I mean, it's just the speed of how things are advancing is just insane. It's really, really hard to predict. I think that there is so much machine learning and AI techniques that can be applied to cloud analytics. We are just in the early days of what can be accomplished. There is so much more,
Steve Hamm: [00:20:17] Hey, somebody asked me recently, Basically is most of what's in AI these days, machine learning, are there other technologies, other artificial intelligence technologies that are really being used to deal with data.
Randy Wigginton: [00:20:34] There are, there are definitely other AI technologies that are coming along. You know, we have, we acquired a company DESA that created what we call deep fake technology, you know, where they could make a conversation sound like it was coming from anyone, right. That's not machine learning. That's clearly AI.
And we are using those learnings to try and improve fraud because. I can foresee a day when someone is going to call up the bank and pretend they are me, and we need to be able to detect that.
Steve Hamm: [00:21:11] So that's voice recognition then
Randy Wigginton: [00:21:13] as voice recognition, voice generation.
Steve Hamm: [00:21:15] Yeah. I mean when I think about the future of AI, I mean, I think once again, there are, there are wonders when you think about all the new capabilities there also, you know, ever since computing, and certainly since the advent of, of AI domains and disciplines, you know, there's always a concern, you know, they're going to take our jobs, these kinds of things.
How do you see kind of people and AI coexisting in
Randy Wigginton: [00:21:42] the world? I think that AI is eventually going to be our greatest friend and a greatest advocate because see the machines have no reason to help one person over another talk about, you know, lack of racism, lack of ageism, genderism, sexism, any of those things, machines are completely.
You know, impartial across all those things. I don't, I don't see them taking our jobs. I see them giving us new opportunities, new jobs to do. I'm actually very bullish on the prospects for the human race.
Steve Hamm: [00:22:19] No, I'm very happy to hear that in the midst of this crisis, it's sometimes easy to get depressed her.
Randy Wigginton: [00:22:26] It sure is.
Steve Hamm: [00:22:28] I'm like you I'm, I'm a technology optimist. I think we really. We need technology innovations to really achieve the kind of progress that society needs to achieve. You'll look at it now. It's it's healthcare it's, you know, it's income and wealth inequity. I mean, somehow that has to be addressed too.
And I do think that the technology has a role in that area as well.
Yeah. Randy has been, yeah. Great talking to you today. Thanks so much for your time. Your stories get better every time I hear them. And, uh, yeah, and I love what you said about innovation and how the, kind of the, the lessons that you learned, Apple are still the lessons that the great companies practice and that square practices.
I think that's. Really important for, for people to take to heart. Also, I thought your insights about, you know, using the data for marketing, about sharing data, about the three 60 view of your customer, and certainly about how. Square has been helping it. Small businesses survive this Cobra. I think that's really inspiring.
So thank you so much. It's great talking to you again, and I hope to maybe we'll meet again in person.
Randy Wigginton: [00:23:45] I hope we do that.
Ben Wilson: [00:23:47] Does it for this episode of rise of the data cloud. Thank you for listening. This episode is brought to you by snowflake to see how you can get secure and easy access to any data with near infinite scalability.