Retail podcast a global conversation hosted by Alex rezze Van Veen. Hello and welcome to the retail podcast. Today we're joined by Robin satara. She filled CTO at data bricks and for full disclosure, I've had the pleasure of working with Robin and yes, I think she's thoughts. Why do I think she's awesome because in my humble opinion to create better working environment better, technology outcomes, better data sets that are not subject to conscious and
unconscious bias. You need diversity, and Robin has been a champion of diversity, not only for the customers that she served, but for the companies that she works on and hence her immensely successful career in becoming top 20, women in data and Tech in 2023, 23 data IQ top women 100. And I'm sure a whole raft of other accolades that Robin has. So, without any further Ado, let me introduce you to Robin. So Robin. Good morning. How are you doing?
Good morning, Alex, how are you? Yeah, very well. Thank you. So, where in the world are you today? I happen to be in Oslo. So despite the American accent, I feel like I have been all over the world in the last few months. But yeah, my lovely hotel room here in Norway. Well, thank you for taking the time out before you start your busy schedule. One of the things we're going to do a little bit differently, normally I dive in and start talking about, you know, data brick.
What are they to fix about? What's your day job habla? What I love to do because this is all about the part of the series of Brilliant Minds, in terms of diverse thinkers, people who are glazing, or leaving a trail of of goodness behind them and empowering people as they go along. And so I'd like to do is just take a couple of minutes and take a deep dive into you as a person before we get to the corporate stuff is that. Okay, Dad. So Sounds great. Thank you.
So one of the most amazing things when I was doing my little research, is the fact that you are an Apache helicopter, electric one at Armament repairer. So early in your career, you're obviously come from a mechanical engineering background. I'm just curious to anyone who's listening, who is at the start of their career? What advice would you offer them?
Or what advice would you offer the Robin at that point in her life when she was sort of just At the beginning of the, of the ladder of starting yoga Korea. Yeah, I always have to admit, I tell people like, I started in the mud right in the Korean, DMZ repairing, Apache helicopters and hellfire missiles and 50 mm machine guns. And if I look if I look back you know, that that I won't tell you how many decades ago that was. But you know, if I look back and sort of say, do I think I would
have been where I am today. There's no way like you Just don't sit and sort of those positions and sort of say, oh, I'm gonna end up being, you know, a chief data officer or chief technology officer at one of the, you know, some of the largest technology companies in the world. And so I think if I if I had to look back and sort of say, what were the things that I wish I had known earlier in my career? I think they're sort of three lessons from my perspective.
The first one is be confident in yourself. I've always sort of been in these male-dominated. Trees are. And so typically own being the only female in the room are the only female on the flight line or the only female at the executive board table. I often, I even struggle with this, maybe sometimes today is, I often observe and listen, and I'm not as vocal, or is verbal about sharing my opinion or bringing sort of a different perspective to board. And so, I wish I had been a
little more, you know. Act and assertive earlier in my career too short of the share that that perspective because it is very different than everybody else in the room. And so when you get those varying sort of points of view and those varying experiences that's when organizations and teams and companies do their most Innovative and amazing work. And so I wish I had had more confidence in myself at the beginning.
Think the second part I wish I are the second piece of advice that I I wish somebody had given me was start early with your network and your building out sort of your ecosystem.
And I've talked about this before, but, you know, building up that that Network that it consists of, you know, people that are your cheerleaders, that are people that give great, sort of feedback, like you just did in the introduction, which is always so humbling people that are always going to sort of encourage you to continue the work that you do because it is
lonely. Sometimes I think trying to drive some of those messaging but make sure you Also have the people that are going to challenge you, that are going to sort of push, you outside of your comfort zone. And then make sure you have, you know, sponsorship because I think as I look at many of the people that have been very, very successful in their career, you can look back and see where they created somebody that was advocating on their behalf when
they weren't in the room. And I didn't create those relationships until probably the last decade or so. So if you look at my career, I stayed relatively stagnant. First per personal reasons, but the other part of that was really I didn't focus enough on building that ecosystem around me that was going to help me be successful. And then I think the third piece of advice would be grand your
self in your superpower, right? Like I remember interviewing for my purse sea level job and sort of telling the, the hiring executive I do my superpower is creating structure out of chaos. And once I could really articulated, I think in a simple way As opposed to just articulating, a bunch of things that I had accomplished or business outcomes or kpis or metric. But once I could really distill the unique value proposition that I could bring to a role.
I've really found opportunities on lock from that perspective. It just to Echo to two parts, the other guests are the CEO from list. She she mentioned as well. The voice in the room is such an important thing for her. As a man, you should always have no one's perfect. So, everyone's got their internal dialogues, right?
But the fact that you both have mentioned, that makes me feel that there is a some aspect there in terms of, I don't know, having seeking permission to talk or just questioning what you're going to say, especially in a male-dominated environment and her the thing that resonated me with me there is just you know, forget that don't don't limit Yourself by that type of
Oh, I shouldn't say that all. And I said this to a women, don't say that type of thing or women don't speak whatever that stereotype is, is to challenge it. So, there's two things that I see in. In terms of obviously, again, having worked with you. I know that you're a magnet in towards people, wanting to do good work with you. So obviously you must that structure out of chaos. There is some secret Source there that people drift towards that.
But the two points I just like to sort of get your A thoughts on how do you manage priorities because obviously, you sort of hinted towards you know, family, priorities. For example and how you prioritize that. And then if you do have any regrets or experiences that again, when looking back, you would wish someone would have said something to you about. You know, this prioritizing this way or, you know, I'm just curious on your thoughts on
that. Yeah, I think I've shared this before I was actually in a domestic abuse sort of relationship for the first 10 years of my career and so much of what I pivoted on those first 10 years were my family, my children, my safety, there's lots of reasons. Why, because the question I get my ass the most often was a sure career seems to really have done well over the last decade where the first, right? We didn't even see See you or hear you, this was within the workplace, right?
Because obviously we were at Microsoft at the time. So I always sort of tell people just be, you know, be cognizant of your teams and the people you're working with and people that you're trying to collaborate with you, just have no idea what's going on necessarily behind closed doors, being the patent Dynamic, sort of opened that up a little more that it was acceptable to have these other influences in these other things vying. For your time.
For me it was about being really Shirred, which sometimes I think drives my family crazy, but I am. I'm a planner. I plan everything and sort of dress. I you know, dropped it out. And so for me, it's being very, very hyper critical about where
I invest time. How do I make sure that I balance it and giving myself permission to say know that I, you know, you just don't have the bandwidth to deliver something the way that, you know, that it either should be delivered or that you want to, you know, be able to sort of deliver against it. And so it is okay to say, you know, no or no not now and and sort of giving yourself permission to balance and and shift those priorities depending on the internal or external influences.
That may be guiding those things, you haven't mentioned this. But again, having worked with your, I see, one of the, the areas and getting the what you've just said, empathy and Leaders with empathy, that ability to understand, you know, it's obviously again, something that comes across. When you're talking to not only clients but t or teams and it's great. I am so torn because I can spend another half an hour, just
unpacking all of that. Because I just think there's so much so many lessons that we don't talk about in the corporate world, that will help the future Robbins. But I am conscious. You're in a hotel about to start your day. So why don't we shift focus and look at data bricks and your day-to-day job and what you're doing. So tell us what is data bricks all about? Yeah, so data rix's.
I think it just an amazing sort of innovative company they've been around for about 10 years created by the founders of spark out of UC Berkeley. So an amazingly, brilliant group of Founders. I think as we really thought about how do we unlock the power of Big Data as it comes across organizations? And so, data breaks were actually the creators of the lake house Paradigm which is now recognized by Gardner and essentially what that means.
In says it's a way for us to tie together all those data silos that organizations struggle with. So if you think about traditional data warehouses that were typically your business insights and analytics platforms versus data Lakes, which were used for your more data science and machine learning as sort of workloads and capabilities.
They are they implications of the lake house or that they tie those things together so that you can have a single platform in a single set of Of tools to be able to drive insights and data science out of the same data assets. Whether it's structured data or unstructured data, or semi-structured data, you want to be able to move your organization from backward-looking and sort of reporting and dashboards that we're all familiar with.
When we think about data to how do we now unlock the power of things like generative AI, which we're all talking about over the last several months. And how do you do that against all of the data assets that Exist within your organization.
So it's an amazing platform that helps organizations tie all of that together with one tool the so that your data Engineers, your data, scientists, your data analyst, you know, you can sort of spread their capabilities with the limited data talents that exist in the ecosystem today.
So, super exciting times, particularly with this quick evolution of large language models that we all see between chat gbt you know Dolly has come out to show an example of how you can can do it without large datasets and relatively cheaply. So yeah, some great conversations that I'm having in my role which as one of the four feet field ctOS globally, I have a great opportunity to talk to hundreds and hundreds of customers on sort of, what are they doing with their data?
How are they thinking about the evolution and the revolution that generative AI presents as they think about unlocking more of those citizen? You know, citizen experiences across the Going to station where you and I both know having had experience. That's where the real Innovation comes from is those that sit within the business. And so yeah, super exciting times.
I think, as we think about that, how do we leverage this amazing technology to unlock the power of our of our talent within our
companies? One of the things that that I that I saw that you talked about, and I mentioned earlier, it's about when companies are trying to get data sets to be sort of of unbiased and, you know, in their Engineers that are they don't end up in this sort of echo chamber of people thinking the same just out of interest from all the customers that you've seen apart from recruiting diverse engineers and, you know, trying to build it from the ground up, how do
you is there any way to avoid that? Because that, you know, I've seen horrible examples of when it goes wrong, but I've not seen it in the Enterprise well, because I guess, no one wants that. Are that in that way? But we've seen, you know, we've seen many examples of when the bias is built in and you end up getting really horrible outcomes, just curious, How do you avoid that? Is there a way to avoid that?
Yeah, interestingly I saw I was at Garden or the gardener London event earlier this week and we were having this exact conversation about you know, an inability to correct historical data sets necessarily. So I don't know if anybody's ever read that book. Invisible women by Caroline criado Perez but it's a great example of how we just aren't
even aware. So if you think about things like medical testing or typically done on the, you know, a standard nerd 30 year old male that weighs 160 pounds. Yeah. And and so now how do you translate that into women? So it's not like you can go back and hurt. You know fabricate? 50 years of medical data that are going to accommodate for that or like the seat belt and a car, right? So for a woman like me, that's only five for the seat belt, cuts, into my neck. And why?
Because the seat belt and an automobile was designed for the average male. And so, I think for me, it really Not necessarily about going back and correcting, all of these data sets. But how do we make sure that the creation of net new data sides? Because if you think about the rate of data creation, right? The veracity and velocity, that data is being created. Today, we have an opportunity to influence. What is the data that were
collecting? And are we, are we trying to minimize and mitigate the biases, you know, in the construct of how we're collecting data going forward, but the other thing absolutely does come down to. Do you have If a diverse set of perspectives across the table and if it isn't within your data team because you can't find the talent, which we could have a whole, I think our conversation
on, how do you mitigate that? I think, you know, making sure that you're opening feet for feedback from diverse perspectives and creating an inclusive environment for everybody to have a voice at the table to express their, you know, their lived experience, their cultural perspective. Their sexual preference. The, you know, sort of perspectives, that gender perspective, there's all these
diverse perspectives. And so making sure that as you're creating these models and ecosystems and platforms, are you taking into account all of those different voices? And if it's not within your direct team this is where that collaboration comes in super helpful. Are you soliciting out of the business? Are you soliciting from your customers?
Are you soliciting from across? Ross, your supply chain, all of these different ways that you could bring in all these opposing, sort of perspectives to really make sure that you're aware of in the historical data. What? Biases exist. How do you prevent that from going forward? And is there a way that you can mitigate the biases in your in your system today to make sure that you don't continue to propagate that historical biases that exist in the system's understood just moving on.
Little bit in terms of obviously you must meet with so many Executives, you know around the world from from and different Industries. I know obviously from retail to finance to manufacturing what's on people's mind right now. And then I don't know if this is part of it but one of the things the that I read or heard this morning was that, how much code? Low code, no code, you know, 60 or 70% of future applications over the next couple of years. Years will be written by citizen
developers, right. Which I used to think was, you know, a little bit of maybe marketing from from people who would sell that stuff. But now with the the tools rapidly enabling people to be able to do that. And it so I don't know if that's one of the things but I'm just curious. What have you heard us as the themes from the execs that your meeting? Yeah. So right now, the big buzz is around generative AI, right? And sort of how are we going to
integrate that? Into our into our ecosystems. So, for example, at Gardner we gave a keynote that was really talking about, where do we see the revolution of AI, impacting Industries and organizations the most? And there's a there's a few sort of low-hanging fruit because everybody everybody sort of worried we don't want to repeat a Samsung we don't want to put our IP out on the internet,
right? We want to make sure that we're protecting our proprietary information particularly because I have that you know that masters of Law and intellectual property. I'm getting a lot of questions about how do we leverage generative AI in a way that still protecting our assets? But in a way that we don't miss the opportunity to really revolutionize the way that we do
business. So organizations today are really talking about what are the things that they can start to do with generative AI, which I think will ultimately replace low code and no code. If you start thinking about prompt natural language, sort of currying and prompt engineering, those things are going to make low code, no code almost obsolete. Elite because now you really are unlocking the power of your citizen capabilities. And so there's a few thing 11 is around that techniques that
enable moment, right? Of organizations. So some of the conversations I've been having about, you know, how are you thinking about setting up sand boxes within your environment to test on? But the other thing is encourage your talent across the entire business to start doing things like prompt engineering. I think, for me, I've done it. Build out my weekly menu or give me a recommendation for a workout before. The next marathon that I'm training for, right? There's lots of things that you
could do in your personal life. I leveraging this technology just to learn how to get better at prompt engineering and natural language query. And so I think that's going to unlock a whole next generation of talent that doesn't necessarily have to come from the python or the sequel, sort
of backgrounds. And so encourage that in your organization, encourage your team, If you don't have an internal ecosystem setup yet to support it, think about doing the sandbox environments that are protecting your data and setting up the boundaries and the ethical sort of responsibility things that you want the organization to think about, but also encourage people to do it in their, in their real
lives. Because those things, you know, have a lot of impact in just preparing people for this next wave of not having to have a hard coding background. The other thing is, sorry. We Carry On, Anna. Yeah. The other thing is really also focusing on what are those internal things?
So, I think one of the big things organizations struggle with his Knowledge Management. We've all seen it where we've searched a billion share points or write a million confluent Pages trying to find things like HR, you know, the employee policy or how do I, you know, how do I take time off? How do I find my payroll? Those types of things. You can easily create within your organization minimal impact, other than I think it's Maximum Impact on the impact.
It has on all of your employees to start seeing. Wow I can now query and are just a regular question, you know and it searches the entire internal ecosystem. So things all like your back office. So your HR your Finance, there's lots and lots of opportunity for low-hanging fruit for you to tackle. Those use cases to use generative AI in a controlled sort of way. And I do think we're also seeing lots of Mission in the engineering team.
So how do we how do we really sort of tackle you know using the copilot types of scenarios? I think you and I both probably attended build this week or at least listen to the recordings later and all of the integration of those types of Technologies. I think we'll continue to see a real sort of propagation and increase of those capabilities and lots of Technology platforms, which then helped you, you know, really focus on the people and process site of of this Mission that we're see.
So, one of the things I that I one of the questions that someone asked me once is a lie. Why you focus so much on diversity, right? You're a guy. Why are you trying to, you know, what, what's your angle, and what am I humble beliefs that, I genuinely believe as, when we get to parity in the workplace, it actually. And you mentioned this earlier on, it actually brings the goodness across all diversity, diverse elements, whether that's
religion race. Gender whatever that is but you need to anchor on one and within the Enterprise world I find that sometimes it's very scattered gun in its approach to diversity. So you're trying to please everyone and end up pleasing. No one. And again, I'd be curious on your thoughts Robin in terms of when you look at all the experiences and leaders that you spoken to about diversity and creating a better environment. How do you do that? What are those areas?
That organizations Enterprises need to think about. Yeah, I think the big one is, it's not just enough to have the representation around the table, you have to create an environment that's being inclusive and giving people a voice, right? So as we talked about really early in our conversation, how do you make sure that that we as sort of current leaders at the table are creating the right environment that people have the opportunity to speak up and give
feedback a true collaboration? Doesn't necessarily mean that you just have the representation but you have to think about the inclusivity of creating the at that environment, where if a person doesn't feel comfortable speaking at the table, are you proactively going out and seeking their opinion in a different environment or in a different sort of way? What I found throughout the course of my career, particularly over the last decade or so?
Is that not everybody receives or gives information the same way? And so the truly create equity and equality across the table. You really have to think about meeting people where they are creating the environments that is collaborative that gives them the way to give and receive an impact and influence and commentary in a way that's comfortable for them. And so whether you solicit outside of the big open Forum that, not everybody is
comfortable in speaking. And how do you aggregate that information to feed it back into the Team to make sure that you have this sort of agile feedback loop that's creating that next evolution of collaboration across the organization. I think it everybody can do that. If you see somebody at the table who's not speaking, don't call them out on the spot. They may not feel comfortable but absolutely walk up to them after the meeting and have a
one-on-one conversation there. Would they might be more comfortable and opening up and sharing their opinion. And I think that's something that all of us can do is really, you know, make sure that Creating a trusted sort of safe environment that everybody feels that they can share their feedback. Their experiences, their concerns, their ideas in a way that that truly unlocks sort of innovation across an organization.
Yeah. Well, you need good leaders and I think that's, that's the, that's the, the challenge that because I do think sometimes, when you go a layer up in some companies, there is group think everyone does come from the same background, everyone. Is from the same gender or race class and so, therefore, it just, you know.
Yeah, it's sometimes the across the masses, interestingly enough, I was listening to and from most people do listen to The Diary of a CEO and they were discussing burn out what burnout is and this concept that actually whether or not burnout is a real thing or not, but it's when employees or workers feel that the task that they've been given they have no control or power over is when Then filburn out, right as opposed to empowering them to do that and I think understanding them you
know, them in their whole sense is really important. Okay. Looking in terms of closing and looking to the Future, where do you see the future? Obviously, I'm not going to ask you about data bricks in the IPO. Don't worry when we're going to break any rules, their SEC filings or anything, not there. There is an IPO on Hearts. But where do You see the future? What's what's on the horizon you mentioned generative, AI, you know, looking two or three years down the line?
What are your thoughts? Oh, my goodness, two or three years? I think I would love to stick with that all the next three to six months. I think as far as fast this technology as a movie, I think generative AI is definitely going to be the one. So if you are in any role, I think you can definitely take advantage of. How do you learn that new skill, set, people always ask me. Many jobs, is this going to replace what roles are going to go away? How do I think is my role at risk?
Right? I think I even saw a study from ey like what's the next evolution of consultative types of businesses, right? And where is that going to go? Now that chat GPT and similar models, can create a, you know, a data strategy with just a few well-worded prompts. How do we think about the evolution of functions and so everyone should be Talking about how do you learn the capability to do this natural language? Sort of queries? How do you think about prompt engineering?
How do you integrate it you know into your into your current roles? That's not sharing IP, I'm not recommending that. Anybody put IP our proprietary information into those systems, but if you don't have the capability to do it for work, do it, do it in your personal life, learning a skill, learn that capability because that absolutely is the way. Have the world that we see over the next three to six months, it's going to impact.
I think everybody's roles in some capacity and so making sure that you're practicing those things as much as possible. I know that technology isn't available to everyone and so, if you can't get access to the technology really think about other ways that you can create ecosystems. So, if you're a teacher, can you create, you know, engagements in the classroom that allow us? For that type of natural language sort of interactions with other students.
Can you create sort of the pseudo environments because while it's not strict, we know that not everybody has access to the technology or capability. So let's really think about the Next Generation coming up. What are the things that we can do today? That's going to help them be prepared for the jobs of the future. And I think this is part of that part of that ecosystem, that we see going forward, don't want a wonderful way to end the podcast. Astro Robin, thank you so much.
It's been an absolute pleasure. Thank you for your honesty, your your humility, and thank you for all the great work that you're doing in promoting, you know, a true inclusive and diverse environment within the fields of data and AI. Thank you so much, Alex, I appreciate the opportunity.