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.