Uh It's right on time. Um Well, welcome everyone. I'm so excited to talk about uh in uh you know, insights uh to impact leveraging data to drive growth and transformation.This is such an exciting topic because uh all of us today, I think we touch uh uh data in any form and it, it's personal life or professionally. I think we incorporate data for everything and we incorporate data into any of the apps that we are using or A I or uh all the information that we read upon chat G BT or we're using uh uh different aspects uh of this uh data is super important. So I'm, I'm glad that we have these three wonderful panelists uh who I can talk to and learn from their experience on how data has transformed their industry that they're currently working in and also their careers. Uh So I welcome um all three of you today. Uh Let me give a uh you know, introduction of each one of you and I'll go through some questions. Um And I think uh yeah, this will be exciting. So let me introduce to Laura Laura Miser Schmidt. Uh She is the president of the International Division at Godaddy and she's a member of the global leadership team. She has variety of experience in marketing, customer experience and product management roles and small and large organization. Uh She has done um uh several uh speaking events.

She integrates quantitative rigor to empathetic view of customer experience. She's an international ambassador for women and technology partnering with the tech women program, uh which we will briefly talk about today. Um And her specialty is customer experience, digital marketing, uh and brand marketing. Uh So welcome Laura.

Um And let me introduce to Deri Gole. Uh She is the analytics leader with over 15 years of experience working on technology optimization and analytics project. Uh She's an expert analyzing complex data uh using advanced statistical machine learning techniques to exploit big data and deliver actionable insights.

Uh She is currently um yeah, 0 40 in her 40 honorary and I have seen her uh linkedin profile as a Barbie uh in the data aspect of it, which I was super proud of. Uh uh you know, representing women, representing data in a big way. Uh She is featured in the Global Data Power women list of CD O magazine. Uh She's also featured in Power in a national magazine for Women, recognized as Women of the month by professional organization of women and excellence Recognize. So, uh welcome day three. Wonderful, wonderful to have you as a uh uh in the panel. Uh Now, let's move on to uh introducing our third Panelist, Brianna Rose. Uh Hi, Brianna. Uh Brianna Rose Sick is a senior managing partner at DXC Technology. Uh She has experience uh as a management consultant working with clients on digital strategy and interactive experience, uh strategy and transformation, cognitive process, transformation, advanced analytics and innovation programs. Uh She has uh worked in different aspects, different industry including uh uh sales, um uh chemical petroleum manufacturing, like uh banking and all of these domains. Uh She supported the president of IBM Canada as chief of staff from 2019 to 21. Uh She was providing day to day leadership as an advisor in the AM between the office of the president and IBM Canada. Uh She also worked in um uh different industries like I talked about.

She's a passionate advocate for advancing women in tech and sustainability, uh such amazing women in the panel. So thank you for making the time and uh talking to us today. Uh uh Let me start uh with Laura uh Laura. Uh you have rich experience in customer marketing and customer advocacy. Um Do you want to learn like more about what customer advocacy means to you? And how have you uh explored that in your space today? And how do you define metrics and our work around data in that domain?

Well, thanks to Maya, thanks for having me and thanks for hosting. We really appreciate it. So to answer your question, which is really about customer advocacy. Uh To me, so I think the marketing definition would be that a customer advocate is somebody that speaks out about your brand and that is willing to, to talk about you uh to other people. But to me, I think what really defines customer advocacy is that it means that you had such a profound impact on your customer and their life that they're willing to tell people about it. And so it, it really means more than just the act of them telling somebody, but rather the fact that you were able to make an impact. Um So a go daddy, we have about 21 million uh small business customers. So these are owners, small businesses, they run, they run shops. And so for us, we, we consider a customer advocate to be somebody who we've helped to basically build up their business or help them change their life by helping them to create a business out of some passion that they have.

Um So whether that be with our products, with our customer care, however, we can, we can help them to be successful, then that will help, that will help society and it will help Godaddy. So it helps both and that's what becomes what creates a customer advocate. Yeah,

that's amazing. Um Moving on, uh Brianna Rose, the next question is to you, uh you have uh you know, experience in your career with so many industries, which is awesome uh chemical natural resources, aerospace, aerospace and defense industries. How has data transformed these industries over the years?

Um Do you see some industries are catching up earlier than later? Like how have you seen those industry can evolve over the years?

So, um thanks for having me and um it's, it's an honor to be here with, with my fellow panelists. So thank you so much for this opportunity. Um Yeah, I feel very fortunate that I've worked across such a variety of industries. Um But a real life example of, you know, how data is impacting the world today. You've seen the headlines recently with chat GP T um data and its transformation abilities are becoming accessible to just about everyone. And so some industries um you know, have been working with different technology and they've started their digi digital transformation journeys, you know, previously, but there's always, it's hard to, you know, classify which industries are ahead or or behind because there's always early adopters within certain industries.

So there's, you know, people who are risk takers, they're at that bleeding edge of um technology. And so we see lots of use cases in healthcare, finance, auto um where, you know, people are leveraging their data to gain insights, they're, you know, leveraging real time data to do reporting accuracy. Um They're trying to optimize their operations or improve overall sales and customer experience kind of similar to what Laura just alluded to Um I think one of the challenges we see with some industries is there's a lot of knowledge that exists, you know, in the workers and they've been doing tasks or working with machines for a certain way for, you know, tens of years or decades in some cases.

And the processes aren't necessarily documented in systems and it's just things that they do. So in those scenarios, we see it a little bit more challenging because you're not able to map out the process or, or collect the data and therefore you're not able to, to get some of those insights. But I think now with how much more acce accessible um you know A I tools are becoming, we are gonna see, we're gonna continue to see more industries, you know, moving in that direction.

That's wonderful. That is so true. We see that happen in every industry, right? Like where we have this um you know, experience and processes that has been done for several years. We want to capture that also as part of the data input and that can vary across the industry on which phase they are in the life cycle. Uh So totally hear you on that and I also agree like it's their early adopters and the, you know, the doctors who want to do it later uh that makes such a big change. And we see that even in our uh technical devices that we picked from, right? Like we have our own choices of when we want to do it. Do we want to see if it succeeds or not? So, uh I'm sure that applies for every industry that uh thank you. Uh Brianna uh Dave. The next questions are to you kind of alluding to the same on digital transformation. I want to ask your uh experience in banking on um how uh data transformation or digital transformation has happened over the years and uh especially in the space that you are currently in. Uh how have you been involved in making some of these transformation uh uh in your uh company in your, in your team?

Yeah, thank you so much. Uh uh Sonia. First of all, uh thank you for introducing all of us. Uh uh that was really kind of you. And, and again, you know, it's the same thing for you. You are so inspiring. So I'm so glad uh that, you know, I'm with all of you ladies and your own journey, you know, if this is wonderful. So I just want to start with that, give you credit and kudos for that. Uh Just so I actually work with the credit credit union uh uh as you already, you know, shared in the introduction. And uh uh essentially credit unions are not, not much different from your bank, right? But fundamentally, the difference is uh we are a nonprofit uh financial institution and the objective is to uh serve uh the, the members and we don't really call them customers. So they are members and any profit that we we make with, it's again giving it back to the member to better interest rates and better products and services. So um uh to be very honest with you, when it comes to credit unions, uh I think uh uh if you talk about any organization and their data, maturity and data journey, they start from being data unaware to data aware or to you know, data driven and then, and finally treating data as an asset.

So uh and I think these are, are pretty much the four phases for any, any organization from a data standpoint. So uh we in 2020 in about March, uh we started, we, we established a brand new data analytics function and the way our analytics uh uh data function is enterprise data is uh we have data engineering, architecture and administration, uh Business intelligence, uh data analytics, data science and data governance, which is the over marching that governs all of it.

Uh So, yeah, so I established uh a brand new data analytics function uh started putting all the pieces together, you know, we were uh uh you know, uh hired data analysts and then eventually data scientists, we were not really ready for any predictive morning and we are still not.

So we are, you know, we actually move from siloed Excel spreadsheets to, you know, some SSRS reports to Power B I dashboards. And now, you know, we are talking about uh let's build a predictive model on next best product for the members and do like member retention, uh analysis and things like that member, demographic analysis and segmentation analysis and things like that, where exactly these members are, how can we cater and provide like, you know, customized products and services to them.

So, um that's really how we and then one of three from a transformation standpoint, there are three major things that we did as an organization and which I take a lot of pride in one. we are moving into cloud snowflake. So we are transitioning from on premises, data warehouse to cloud. Uh We are also uh uh developing right now uh a master data hub platform which becomes a single source of truth for all of our member, demographic data member. Demographic data is our first use case. So we cover like their name, first name, last name, their zip codes, their addresses, their SSNS and things like that. We want to have single source of growth versus having 10 different uh uh you know, information for Sonia in 10 different places. So uh that is important, right?

So, and then the third thing is uh we have uh deployed an enterprise data cataloging platform that shows the data lineage. Uh It has all the data dictionary elements, the technical definitions of those, all the business metrics and KPIS of the organization and then having standardization around that, right? So let's say if you say a checking account, then uh the question is what is an active checking account?

It should mean the exact same thing to me and to anybody else in the financial institution. So I know it took a lot of time but uh that is where we are at this point.

Yes. Wonderful, wonderful. I like how you actually face this across your journey And like this is a true transformation, right? Like where we have data in like spreadsheets and all over the place, how you bring transformation and bring it to a standardized place, make it a single source of truth and then how we move from like, you know, on premise to cloud, how you develop analytics practice. I think that's a true transformation, digital transformation journey that you are having there. And uh I'm sure you're enjoying that phase of transformation, but it it's a, it's a true uh thing. I love it. I love to hear that. Um Maybe let me ask in the same direction where you know, the data governance aspect that you talked about. Like, you know, let me ask you one more question on that. Like um there is these issues about fraud and other, you know, uh issues that continue to happen, right? How has data governance practices helped your team tackle better? Like um you know, maybe some successful practices that you have done on master data that helps, you know, uh that others can alert and follow.

I think

one of the most important thing uh in my understanding, Sonia is the data classification, uh classifying data as uh you know, restricted sensitive uh you know, there are uh and I can't remember the exact, but there are different types of uh like pi I data, right? So I uh let's say if you are a, a member of the credit union of your SSN or, or bank and important information should not be accessed to every person in the, in the in the bank or it should not be access to the vendor. So we have to handle that sensitive information very carefully. So who has access to what? So uh I'll give you a really good example for instance, when let's say when we talk about cloud, right? And let's say all of the data is sitting in cloud and let's say I have uh analyst or data analyst who uh who are actually writing their codes within the cloud environment and they have to build a report. Uh But my question is who has access to or how much a or let's say there is a business analyst who needs to have access. So what access, there should be role based access control. And that's where you know, we are using, let's say a vendor called altar which are helping us with policies on rule based accesses, not everybody has, has an access.

I'm the I'm the head of data, but even I don't have the right access because I do not need a right access in the cloud environment, right? Uh Similarly, there is a, there is a business analyst that does not need a right access will only have a read access. So those are some of the things that you know, uh uh classic of data restriction role based access, I think I feel and then you, I feel it's also important to have clearly laid down industry standard data access policy, data security, data privacy. You need to establish those standards and procedures and, and, and everybody has to follow it. That's the other part of it. That's

true. Thank you. No, that's totally true. Uh Laura uh uh maybe I'll pivot my questions to you now. Um can you explain like how have you established your data science teams in your organization or how have you structured your teams in such a way that this transformation happens?

And there's also like kind of a set center of excellence aspect, but there's also there are individual functions that, that they can operate effectively as well. Like what are your experience have been around uh in your organization?

Yeah. So we, so at go daddy, we have some central data science teams, both that run sort of our core functionality rights. We've got the uh one of our big challenges is matching domain names to searches. And so people are searching for names. Do they find the right name? So we have an entire data science team around that we have an entire data science team that's responsible for helping each of our business units. But I think in addition to that the transformation we've made is we sort of said that every single employee needs to be a data scientist in some way, right? Meaning that they need to find insights, they need to think about their business in terms of the insights that they can drive from customers and then use that. And so we've seen successes, not just with our business, but also in our hr department and in our pr department even uses data. Um And so that's been a great part of our transformation as we've built out the company.

That's wonderful. Thank you. Uh Let me shift gears a little bit. Um I want to, you know, kind of get um inputs on women career as well and understand like how, you know, being part of the women tech, which is such a wonderful organization. I always aspire and get uh uh to become a great leader. And I also get inspired from leaders like you. Uh So Brian, now my next question is to you, uh consulting is an exciting career, right? Like it, it gives you exposure to wonderful places and it exposures to different industries. Um II I wanted to ask like, what challenges do you see for women and what are some of the initiatives that you have led, that sees success for encouraging women to be in this industry and continue to have that path of personal and professional life together.

All right. So, um I was actually just telling Laura I'm planning on getting married later this year and um it's an exciting time, but as I talked to a lot of my, you know, women peers who are at this phase in our lives as consultants who, you know, travel quite a lot to client sites. I'm at a conference right now. Um, you know, there is a bit of a concern at this point in our lives about being a mother. Um, you know, in the future and having a successful consulting career, you know, taking more on. And I do see a lot of firms, you know, taking action to address some of these concerns proactively, which is great to see. But I think there's still so much more to be done and, um it's great to have these panels and these opportunities um to talk about things like this. Um But some of the things that I've seen are, you know, really strong sponsorship and uh championship programs and mentorship programs to really reassure women that there is a place for them in the business, you know, whatever path they go down to be mothers or to not be mothers.

You know, there is a future for them. Um and their career aspirations are still valid. Um I think thoughtful or change or role movement opportunities are, you know, something that organizations can leverage, you know, to help women as they balance more and um tech or reentry programs, you know, for people coming back into the, into the workforce are important.

Um Not every program is gonna make sense for every woman. So I think that you have to speak to people and there's got to be some sort of understanding and you know, exploring different levers to help um to help them and, and to be flexible with what the approaches are. Um So, you know, those are some of the things I've been involved in and I'm really proud of, but I, I do think, you know, there's much more to be done and it, and the best way to, to keep the progress going is by talking about it.

Yes. Yes, that is so true. Uh I am a mother for, you know, two young kids and I can see them like always pop up at my meetings and you know, be part of the meeting sometime. So we should continue to encourage everyone that this is normal, this is gonna happen. And I think COVID helped a lot of it to normalize such of the situations and uh it helped like, hey, this is OK, even we feel, OK, we don't feel like out of place or apologize 100 times for it. But I think these initiatives definitely continue to help and make all of us, you know, feel normal in all of our life stages and continue to have a successful career. So, uh thank you, Brianna.

I do and I do want to, first of all, congratulations Brian. I'm so happy for you and super excited. Thank you. Yes. Look at that beautiful smile. So uh I do want to like, I, you know what Sonia, I think uh they make movies on Wonder Woman. I think we all are the Wonder Woman. Like uh we don't wear those costumes, but we, we truly are like uh whether, you know, I have a daughter myself and I have a little one. So my point is whether you have kids, you don't have kids, whether you're man, not married. But let's, let's give it to all of us, right? We are like wearing multiple hats and then we still show up for a panel with a smile. Yes.

Right. Yes, definitely. Thank you. Thanks Dave. She for that. Um uh My next question is to uh Laura, I want to talk about um you know, more on how uh you are leading initiative is and go daddy as well as you know, yourself on some of the initiatives that serve local communities. Um You know, uh like tell me about initiative. I know that you're part of venture forward initiative that I have briefly, you know, seen uh tell, tell us more about that and how people can actually benefit from it if they are interested or how have, how has that transformed other uh people uh across the globe?

Yeah, I could answer it sort of in two ways. One is sort of the go daddy view and then one is my own view. Um I would say from the goad perspective, what we've done is, you know, we, again, I've mentioned before, we have this mission of helping small businesses be successful. And what we realize is we have all of this data that tells us when small businesses are successful and sort of where they're successful, we have data about when people are starting businesses. And so we've been able to leverage that data through something we call venture forward.

And the idea is that we actually partner with local communities and share with them the the aggregated data about how their community is doing for small business to then help encourage them how to get better or how to change. Um So, for example, we worked with uh the community of Gilbert Arizona and we found out they had basically 17 small business starts for every 100 people, which is unheard of. I mean, most places around the US, you would, that number would be 3 to 4 starts per 100. Um And so we realized there was this huge community of small business owners in, in Gilbert. And so we were able to work with that, that local government to actually make programs and, and grants for small businesses in that area. Um We've since expanded the programs, we worked with the State of Nevada. We work with, uh Palm Beach sort of all around. Uh, lots of different places we work with there. So that's from the professional perspective or from the go daddy perspective. Uh Personally, the other place I've really leaned in on is women in tech. Uh, so something you and I talked about, uh what we met earlier was that I, I work um with a, a program called Tech Women and we bring women from about 20 I think it's 21 different countries in Africa, the Middle East and Asia uh to the US for four weeks to get an experience where they get an internship um in technology.

And I, I find that that, that experience is so eye opening for them, not because of what they learn, but because of the example that they see and it makes you realize how important that example is. So, you know, most of these women that come are just, they'll blow you away with how good they are at technology and technical careers. Um There are a lot of data sciences, scientists that come for this program. Uh But, but you also see that they see that, hey, I'm a mother of three. and they see sort of how do I manage that and what is it like to be a mom that's working? And so that's been a great personal uh thing that I've really enjoyed.

That's so wonderful. That's such a great initiative, inspiring other women uh and also across the globe, uh you know, uh motivating people to stay in tech, which uh uh which, you know, is life changing in many ways. I mean, we assume that, oh, this is just normal for us, like, but I'm sure like people who would visit, like, feel so transformational about things that are happening. Yeah. Right.

You sort of have that. They, they say the impostor syndrome, right? You have the impostor syndrome of these people that are coming over like, what am I gonna teach them? What are they gonna learn from me that they could possibly be helpful? Uh But then you realize that it's really them seeing that example and getting the understanding of who you are and how you work and that, that it can be done. Yes,

so true. Um Thank you for that. Uh They, the next question is for you. Uh I wanted to uh you know, uh ask your advice for folks who do not have a statistics engineering automatically and uh uh who wish to get into data science field, right? Data science A I and machine learning have picked up pace so fast in the last couple of years. Um I think we all are in the phase of like, oh, I don't have that degree but I'm, you know, such an expert at this. But what advice do you have uh for people who are getting into that industry and they're super passionate but that they don't have these standardized degrees uh in general.

Yeah, I think you asked the right person the question because I myself did not have any degree in engineering or computer science. So I came from a non um math, non background. In fact, it uh it was hard for me to even uh pass my, my 10th grade. Uh my uh especially my math. So, but long story short, uh uh I think uh uh the moment you realize you want to bring your career in a certain field, I think the only thing at that point matters is your, your passion, your termination and your hard work to it. Um No amount of or uh irrespective of the number of degrees you, you know, you have or the certifications, which obviously, I have huge respect. I eventually obviously did uh uh get my, my certification and degree in data science. But what I'm trying to say that before that I think uh I was coming from a curious mind and uh and there was this passion to learn and understand uh about analytics about uh you know, uh statistics and it all arose from there. And then uh I learned more on the job versus reading books and doing trainings. I think you learn so much when you are actually trying to solve a real problem. Which is on job, right? Versus just doing some case studies and things like that.

Uh My, my honest advice would be uh if you really want to be like a data analyst, uh then, you know, start like researching, you know, like maybe enroll in some certification and there is so much free in, you know, information on Google. Like you don't even have to spend money. If you, if you're not really worried about any uh award or any, any stamping, then, you know, go ahead and there's so much information freely available. So read through it, do some analysis, maybe enroll in some certification program.

And then uh once you know, you find a job, I can tell you you will learn more on the job uh versus what you uh go through books. I'll share one fun fact with, with, you know, all of you. So I obviously was raised and born and brought up in India and I barely passed mathematics in 10th grade. And then my, that's when my mom said that this is it for you, don't you ever try to do anything related to math and science? And, and I was like, yes, you're right. I don't think this is my area anyways. Long story short, I took uh I did my undergrad and Business administration never wanted to look at math. Uh got math, I had to move to the US. And the only thing that I knew because the only thing that I did in India was sales. So the only thing I knew was sales. But when I came here, I realized my English was extremely interesting and people will not understand what I'm saying. So um it's just that uh I was like, it would be unfair for me to become a salesperson with this interesting English. So I will leave up to your judgment. How interesting it was. It is still very interesting. I'm telling you. So, uh anyways, I started preparing for like my six Sigma Green Belt certification and that's where my interest in statistics uh really triggered and I really enjoyed and then eventually became a six Sigma black belt and master black belt.

What's, what's really funny is that I could not pass math and decided and I said bye bye to mathematics at that time, but scored a perfect 800 on my gr quant when I took GR when I wanted to do, got into a master's program also. But unfortunately phd program but could not pursue it due to some health issues. And then, and uh the funniest of all became an adjunct professor for stats at the University of Houston. And the first thing I the I always tell every semester when I would teach, I would tell my students uh I, you know, you have to excuse my English because English is my third language. But guess what? I'm not here to teach English. I'm here to teach you analytics. But guess what? I also failed mathematics, but you are in safe hands.

That's wonderful. That's wonderful. Uh Thank you for sharing that. And I think a lot of us had great smiles because it probably resonated with us as well in some part of our lives. So thank you for that. Um We have a few more minutes. I think about eight minutes before we close. Um I want to open up for questions if anybody have questions. Uh please raise your hands. I don't see anything in the chat. Um But I would love to hear from anyone. I saw one raise hands. Uh probably like, you know, maybe and we just started but I would love ask if anyone has questions. Yes, I see. Um Marie Gilliam. Do you like to ask question? Do you wanna unmute yourself and ask the question, please?

I think I had to cook the button to allow her to unmute. So she got now.

Yeah, I unmuted help. Maybe she needs to unmute herself or if you're unable to, then you can just, you know, copy paste or, you know, ask you a question on the chat and I can read it out as well

while we're waiting. I can give one more anecdote about the whole women in tech situation, which is that Echo Daddy. When we did our uh salary pa parity data, we looked at like how our women paid the same as men. We were one of the first companies to pull that data. We were all so excited because the data showed that men and women were paid similarly. Um We then asked why, why are women and men paid similarly? And that's where we started to look at the data in a different way and realized that the reason why women and men were paid the same was because women were being promoted at a lower rate than men. And so they were going higher up in their salary band. And so it changed completely how we looked at the problem and it, it, it caused us to then switch to how do we actually help women get promoted. And so we started implementing automated uh messages to managers. So any time an employee on their team, man or woman had been in a role for too long or longer than, than the normal, we would send them a note to say, hey, this person has been enrolled for a while and that alone improved the, the promotion rate of women because it made people think, right, should I promote this person or not?

And if they had a decision to make, and so it completely changed it. I thought it was a good antidote given the discussion that Brianna you were having about women in tech and sort of how we think about uh the situation for women.

Yes. No, that's such a great um example. And, and I'm glad like a lot of these, a lot of the companies now are investing in this and looking upon the data and trying to take action. So uh that's so great. We have one question from Anna and her question is, how do you ladies stay up to date with new technologies?

I, I'm happy to start. So um I go to conferences quite a lot. I'm at a conference right now um where, you know, it's lots of, you know, big news announcements, lots of different um courses or I guess programs you can do throughout the day to learn about different things that are going on. Um I, I subscribe to a few different newsletters working, you know, as a si uh provider, we have tons of resources internally to brush up on our skills or, you know, look up different things or get certifications. I also um like Dev Shrem, you know, mentioned sometimes go on Udemy or, or Coursera or just, just different things to, to poke around and see what's going on. Um So that's what I do personally. There's tons of content out there. Um And so, you know, it, it's, to me, I view it as my duty to myself to be relevant in my industry and to, to spend time to just keep myself up to date.

Yeah, totally agree. Uh The investment in time on ourselves I think is definitely uh

yeah. And so we have a lot about utilizing technology as much as you can and utilizing new technologies. Um At Go Daddy, we call it, eat your own dog food, meaning like, try your own stuff. You build a product, you go try it and then you try the competitors products and then you try other stuff and then that helps you learn quite a bit. Yeah,

totally. So we have three more minutes and I have one more question here uh from Natasha. Uh What advice do you have for a woman just starting in her career? How can she make herself stand out? I would like to go.

I think uh it's a good idea to have a mentor and uh maybe have uh you know, one or two mentors uh in the same field that you are aspiring to start your career. And then maybe you find out somebody on linkedin and, and uh and connect with somebody who's genuinely interested in spending, actually not spending, investing their time into uh not helping you, but uh you know, into kind of guiding you because you really don't need any help.

Uh You need somebody's guidance and some encouragement and empowerment because everybody starts from somewhere, you know, so somebody who's genuinely interested in investing their time, if you can find somebody like that, that's wonderful. And that's exactly who you should connect with.

Uh um The other thing is that uh uh I mean, uh to be honest with you, I would say that when you start your career and I can tell you just based on the mistakes that I had made. Don't worry too much about how big of a compensation you have. Trust me. I know uh, money is enticing to everybody and at the end of the day you all, everybody wants to make good money. Right. Why not? Right. Um Who doesn't want the Louis Vuittons and Chanels? But I'm bored of them. But anyways I don't want any more. Uh But my point jokes apart, uh don't fall in the trap of how big of a compensation you have. I think you should fall in the trap of how much can you learn? How much can you, you know, how much can you absorb from everybody around you uh in your team or you know, your leaders or people in, in that area that I'll give you an example, for instance, even today, you know, I love to sit with my data engineering uh uh head and understand from him.

And I'm just curious, I'm just, I just because I'm not an expert, I have to be honest with you. OK? I am the leader of data, but I'm not an engineering expert. Let's be very honest here. So I want to, to see what he's doing and how he's doing. And not because I'm micromanaging just from a curiosity mindset. I want to learn. I, I like to, you know, learn about uh if a predictive model has been built by one of my data scientists. I'm just curious. It's all, it's all coming from curiosity. There is so much we can learn from people above us and also uh people you know, uh below us. So I think, and then also, you know, your uh your peers, so you should keep your eyes and ears open for all of that. So I think curiosity, the uh the desire to learn and um not uh and then most importantly, volunteer your time. Uh you know, if somebody is working on something and you can also volunteer some time and on their project, go ahead and do it, don't expect anything in return, but just go ahead and spend that time. You might not know that could be your next career. So, and also, you know, it, I believe in the 7030 ratio, spend 70% of your time doing your existing job and spend 30% of your time preparing for your next job. That's just my sense I could be wrong.

But that's how I

know. That's a great advice. I think uh it's super important for us to uh stay in touch with the technologies with the interview process itself and take the, you know, be on par with our skills, not just technically but also our soft skills and our, you know, uh our uh interview skills and all of that. So I totally agree with that. Well, this was great talking to you all. Thank you for making the time and uh making this so interactive, sharing your experience and uh you know, making this a joyful conversation. I appreciate the time. Thanks, Laura Brianna Bare. Uh And the questions as well, they were uh really exciting questions from uh the audience as well. Um Thank you, have a great week and have a good rest of the conference. Thank you. Thank you.