Adel Nehme, the host of DataFramed, the DataCamp podcast, recently interviewed Mai AlOwaish, Chief Data Officer at Gulf Bank, who outlines how a people and data-first approach can unlock the value of digital transformation for organizations across industries.
Adel Nehme: Hello everyone. This is Adel, data science educator and evangelist at DataCamp. Something we've always spoken about on DataFramed is how organizations are adapting their culture, skills, technology, processes and more to a rapidly changing and increasingly digitized world. One thing I always hope to achieve with this podcast is to help others understand how they can change their own organizations and make them more data-driven through others experiences, and there's no better experience to share than Mai AlOwaish.
Adel Nehme: Mai AlOwaish is the chief data officer at Gulf Bank. She is a seasoned information systems and data analytics expert with 18 years of experience between Kuwait and the United States, where she spearheaded a variety of data analytics in e-commerce initiatives and enabled digital transformations for financial institutions, retailers, airlines, and more. In her current position, Mai leads the data analytics practice in Gulf Bank and oversees the data strategy and implementation of data science and analytics use cases.
Adel Nehme: Mai has orchestrated the data ambassadors program to start a data-driven culture and enable business users to self-serve with analytics across the organization. Throughout the episode, we speak about Mai's background, the CDO role and how it's evolving, the cultural and people dimensions of data and digital transformation, the data ambassador program at Gulf Bank, how to increase diversity inclusion in data science, and more. Now let's dive right in.
Adel Nehme: Mai, it's great to have you on the show and I'm excited about our discussion today. You have a very wide range of experiences across industries, such as retail, consulting, e-commerce, banking, across a wide range of locations. You're currently the chief data officer of Gulf Bank, one of the largest retail banks in Kuwait. I'd love to hear your journey, how it has culminated in your current role and how you view the role of the chief data officer evolving ever since you joined the industry.
Mai AlOwaish: Thank you Adel. It's a pleasure to be here. Honestly, my journey has been an e-commerce and ending up in data. And I always tell my team members that I've just kind of followed the trend where it went. The beginning of my journey started with banking, of course, and I was focused on online banking and kind of the digital transformations in the early 2000s. So back then, having an online banking or phone banking was the concept of digital transformation, and in a way, we didn't realize the data aspect of it. It was more about technology.
Mai AlOwaish: And now digital transformation is about data and that's kind of slowly how I went from doing digital banking, and then I focused on working with Google partners in the past 10 years with data and analytics solution. I always say the past 10 years were pure data analytics. The prior 10 years to that were purely banking. And now my role is kind of involves everything that I did in the past 20 years, where I'm mixing all of the digital banking with the data analytics to establish the data analytics office here.
Adel Nehme: That's really great. And in terms of the CDO role there's been consistent evolution on that front. How do you view the CDO today and especially when it comes to large scale data transformation projects?
Mai AlOwaish: I think it's, some people think of the data officer role as somebody who just does the data analytics, and in my way, I think it's more about knowing that we have data as an asset and that every single department realize that the data that they touch is contributing to the overall organization's objectives.
Mai AlOwaish: So one of the key things I see that data officers really have to do is really teach up the organization, to learn about data, know that every single person in the organization touches data. There is no organization right now without somebody sitting at a computer, either crunching a report or reading a report. And that's what I see, that's the chief data officer role is to make sure that they are aware of their kind of role as a person who's dealing with data and they are a stakeholder in the data.
Adel Nehme: Now, you mentioned your experience in digital transformation in the early 2000s. Of course, digital transformation is still major today, has been a priority for financial services and banking institutions for the past decade. This has been only accelerated by the COVID-19 pandemic. Given last year's acceleration, I'd love to hear your thoughts on the state of digital transformation in banking today, and the type of value banks are able to unlock with it.
Mai AlOwaish: I think what the pandemic did is kind of just, like you said, accelerated the digital transformation. It was a high need. Digital transformation started a while ago before that. Maybe they were given a priority but not as much as the urgency that the pandemic added. One thing that we saw out of this digital transformation is we received a huge influx of data, and I've seen it not only in banks, even in the past few years, when I worked with e-commerce.
Mai AlOwaish: Once the pandemic hits, all of these customers coming into retail store, like the brick and mortar stores, they were coming online, leaving digital footprints everywhere on our website, giving us easy behaviors to see, and starting for us, we started throwing personas about the customers that we know. And it just added a lot of value to the data sets that we already had, but we did not know who is doing what, especially for those walking in the stores and doing.
Mai AlOwaish: And the same thing applies to the bank. Many people love going their branch and doing that experience. I think once they started doing those stuff digital, they stuck to the digital channel, and now for us, it's easier to roll up that data. It's easy for us to draw the customer experience, draw the customer journey, because we have it in a digital format already. In a way, it's become much easier for us on the data and digital side to analyze and in a much faster way, instead of waiting for the customer to come in and ask them to fill a survey or ask them for their experience. It's already coming in the format that we were wishing that it comes in few years ago, and I think there's a lot of value to unlock in that. And as everything, when we collect data, it's usually the first few months where we're trying to collect more data, but then we wait for more data to find trends and draw some models and all of that stuff.
Mai AlOwaish: We already have a year in right now or more, and we're going to build on that ongoing, because as I said, people are staying with the digital, even though things are opening up, some people are comfortable now doing their transaction digitally more than coming into the branch or coming to the store, and I think that's where we're seeing that some businesses thought that they'll lose that digital footprint, but it didn't go away. It's still there. It's still strong. And although people still come to the branch, but they still do stuff online, and that means we're able to build more and more with data going forward.
Digital Transformation Versus Data Transformation
Adel Nehme: So as Gulf Bank's chief data officer, you're at the forefront of digital transformation initiatives, so I'd love to hear your thoughts on how intertwined digital transformation and data transformation are, and where do you think they intersect or not.
Mai AlOwaish: So, as I mentioned a while ago that previously, digital transformation was pure technology effort, that you're taking a transaction or some kind of process that is happening manually and then trying to digitize it. Now in the current age, digital transformation is about being client-centric. It's about pinning somebody who knows exactly what they want, and we know that when can we push this product to the client, because we know that he is at this phase of the purchase or the customer journey.
Mai AlOwaish: So with the current approach of digital transformation being client-centric requires a lot of data about this client, and that's where we say we really need a lot of data to become client-centric or to perform that digital transformation. It kind of become a necessary part of digital transformation to first build the data platforms and then go into the digital transformation. Otherwise, if I'm building a customer journey and planning the journey without knowing exactly what the customer needs, there's no way for me to push the right product or to assess that this customer is actually planning to maybe close his account because of a certain behavior that we saw. And we won't be able to take the right action unless we have the right data, so to me, it became kind of an integral part of the transformation right now, and it's not just the technology aspect.
Adel Nehme: I'd love to deep dive specifically into how data or digital transformation projects are not just technology initiatives. Now, given the importance of data transformation within digital transformation projects, I wonder what you view as the key lever of acceleration in these types of programs. Do you think in that regards, it's more technology or people driven and how so?
Mai AlOwaish: So when we talk about digital transformation within the company, I think, and I always say it's people, people, people then technology, because if you get the right technologies in place and you get top of the line data platforms and all of that stuff, if people are used to extracting that Excel sheet and then crunching it into something, they'll still do it.
Mai AlOwaish: Digital transformation, if you have the right data, if you have the right platforms, but the wrong people, or just the wrong mindset on people, it will not succeed and you'll still be stuck into the pre-digital transformation era. And I think part of it is not just educating people on these tools, but actually building the culture for it, building the actual... bridging that digital transformation, how it adds up to their value and how it kind of roll ups into the whole organization objectives and strategy and all of that stuff.
Mai AlOwaish: One thing that I've seen kind of make or break transformation is the people who are not just leading it, it's the people who are involved and affected by this transformation, because the people affected by this transformation, they can just not make it happen because if they're not sold into that transformation, if they don't transform when you transform your solutions and systems and all that stuff, it's not going to help them go anywhere and it's going to make your transformation really not mean much.
Mai AlOwaish: So the key factor is really start with the people, then go to the technology, and that's kind of something that I'm a firm believer in and I've seen it happen more than once that when we start with the people, things go well. If we start the technology and then remember what the people need to do, transformation will fail.
Adel Nehme: Do you think then it's a misnomer for the industry to settle on the term digital transformation without necessarily doubling down on the data or people aspect of it?
Mai AlOwaish: I think so, honestly, because you say digital transformation and it has to do a lot with data, has a lot with people. Digitizing the process doesn't mean you're actually going to get it right if you don't have the right data. Digitizing the process where people are not informed of how this process affect their day-to-day process doesn't mean that this digital transformation is going to go through.
Mai AlOwaish: One of the things that I think we struggle with is naming. There is like, and I see it all the time, like I'm called the chief data officer. I'm technically the chief data and analytics officer. There is this chief digital officer, and there's chief information officer, which they're technically IT, but they to talk about the CIO of information, but it's more of a chief technology officer. So sometimes I don't like to use all of those names because they might really confuse us on the right agenda. I love how you said that it could be a misnomer. I totally feel that, and it's, I think for probably lack of better names, or just because digital makes sense to everybody.
Adel Nehme: Yeah. I definitely feel like it's very hard to sell the term people transformation.
Mai AlOwaish: Yeah. Yes. Then they'll go, okay, that's not us. That's something with HR. And it's very different when we talk about the people aspect of things. And even like if I say, when I started here and a lot of people thinking, oh, so you're doing data, and then you're not really going to be talking to anybody in the bank, where you're just focusing on the systems where the data lives and you're going to extract some reports or systems first. And I said, no, actually, I work with everybody in the bank, from the branch all the way to management, because everybody, if you're looking at data in your computer, then you are my stakeholder.
Creating a Data-Driven Culture
Adel Nehme: So if you want to break down the people component, what are the initiatives you think banks or other organizations need to scale in order to transform their culture into a data-driven one?
Mai AlOwaish: So one of the things is that we need to, as a bank or as any organization, there first needs to be kind of... I hate the word literacy, but it is a data literacy that you want to start with, to make sure know that everybody has a role that they play with data, and data literacy should be organization-wide, honestly.
Mai AlOwaish: There's no organization right now, big or small, where data is not used by their team members over and over again throughout the day, and not just being used once, but sometimes reused to analyze some more and more every day. So they need to understand kind of what resources they're dealing with, the assets of data that they're dealing with.
Mai AlOwaish: Aside from just basic data literacy, I think one of the things is trying to identify different people that are key stakeholders in data, and ensuring that they belong to a bigger team, which is what we call kind of the extended data team, or the team that is directly connected to the data office or digital office or whatever we call it, but those people are exactly knowing kind of the journey of data and how things are changing. Otherwise, that the whole journey of transformation, if you don't have the right people and the right calibers in place, it may have a hard time kind of getting traction.
Adel Nehme: That's perfect. And this marks a great segue into how you're accelerating data transformation and building a data culture at Gulf Bank. So it's been exciting this year with the release of the data ambassador program. I've seen you evangelize this program across social channels, and it's been great seeing it unfold from the sideline. Do you mind expanding into what the program and what are its goals?
Mai AlOwaish: Yeah. Yeah. It's been over LinkedIn, and I think the team made it so much fun with all the props and all of that stuff. It went viral, and I think one of the key things that made this program go viral, it was people-focused, very much people-focused. The way that we had this data ambassador program kind of orchestrated is that, like I just said, we realized that every single department in the bank works with data, whether it's, even if it's not client data, even if it's just data that's used for day-to-day operations, even if it's like I say, facilities department, which they manage buildings and so on, but they do some reports internally. So anybody who's extracting, working with data is identified as an ambassador in the bank. And we had 140 ambassadors out of almost 15, 1800 kind of staff along, operational staff, so around 10% of the bank went through this program.
Mai AlOwaish: And the way we phrase this program is that we are a data office, we have a data team, but then there's the extended data team, which are kind of the army of people working with data and embedded in every single department. These people need to know what we're doing with data and need to have a say in how the future of data and analytics and whether we're [inaudible 00:15:58], or we're moving into a new analytics platform.
Mai AlOwaish: I cannot decide on the bank, and I build practices for the overall good, kind of the common good of bank, but my stakeholders need to be involved as part of this transfer. And the way we did this is that, well, yes, we identified all the people who are working with data across the bank, but that doesn't mean I just identify them and give them work.
Mai AlOwaish: First, I have to teach them, and I have to kind of do kind of a training program because before we start working with data, we need to know kind of the data roles and responsibilities. And the way we started, we've done a five month program for these data ambassadors, once they were recognized in what we call the nomination process. So we did a big nomination process where every department nominated these ambassadors. And the way they were nominated is that these are the people who are doing my day-to-day reports, or these are the people who are really creating data for me in the report. So we group those people, and then we wanted to make sure that, because of the large number, we're a big organization, so 140 people, I cannot get them in one training room. It's not going to be effective. So we call them kind of, we group them in batches, which is a maximum of 20 per group. And then with this grouping, we make sure that people from different departments are in each group.
Mai AlOwaish: I don't want a single department per group. Otherwise, there won't be communication across the organization, because communication is key when it comes to data, because a data that is created at the branch is used in finance, and then finance creates a report and risk uses it for their risk analysis, and then risk does something, which the management uses for a taking decision.
Mai AlOwaish: So all of these different stakeholders need to have proper communication channels together, and that's how this data ambassadors program brought all of these people into the same platform. They go through a five month training program where first they learn about the roles and responsibilities, and then they learn about data quality, and then they will learn more about kind of how to improve the quality of data.
Mai AlOwaish: How do they manage data going forward? What are the things that we need to worry about, kind of the data cleansing? Or how do we actually create really good data that is valuable and that creates insight? So all of the training program, and then there's some tooling in the end. First, we started the concept. We started to do the people, and we launched this program this last month, in October, so we'll be wrapping up in February, March.
Mai AlOwaish: And once they are done with that training, then they're identified as the ambassador for their department. They're able to help their department with anything data, and then they work with us as the data office to be their kind of lifeline into anything that they need to do new, something for their department. If they're the data expert in the team and they need kind of more help in something, or they have ideas, then they have the platform of the data ambassadors, which is more kind of a club for every everybody data.
Mai AlOwaish: And the idea is even once we're done with this training program, I told their departments, we're not done with them after this training. We're really going to have kind of those monthly meetups for all the analysts or the data ambassadors, because there's a lot of value in getting those people together in the same room, communicating and talking.
Creating a Data Curriculum
Adel Nehme: That's wonderful. And I love how much emphasis there is around the community and how bottom up this transformation program is and not vice versa. You mentioned here it's a five month program that goes from concepts to tools, and so on and so forth. Can you walk me through the process of creating a data curriculum for your organization, and why and how did you prioritize the skills that you chose to prioritize?
Mai AlOwaish: So currently, and I love how you call it curriculum, given that you're DataCamp and all about learning and curriculums. And it's funny, we actually use the same word. We didn't use training program or something. I said, there is the ambassador curriculum, and there is the kind of a data literacy curriculum. And even funny, we call them like data 101, and that's for everybody in the bank, kind of the data literacy or basic data literacy program. And then the ambassador series was not 101, it was 201, just like college when this is the advanced version of data training. So the 101s, they were for everybody in the bank and not for the ambassadors. This is a curriculum that was intended for everybody in the bank to see, as a bank employee, what are my roles and responsibilities towards data.
Mai AlOwaish: If I am in the branch creating data, then this is, and we even customize that curriculum to the audience. So we have a 101 for all the kind of the juniors in the bank, and then 102 for the managers, and then 103 that was for branch and sales, kind of the front lines of the bank who are dealing with clients. And, and each of those curriculums is kind of had the same concept, but they're really customized towards the data scenarios that they deal with on a daily basis.
Mai AlOwaish: For some managers, it's really looking for issues of how reporting is the done. For front liners or sales, we're really focusing on when entering client data, this is what you should be doing, and so on. As for the 201 series, which is the other curriculum for ambassadors, we kind of customize that because these people do the day-to-day reporting, they do the analysis, they do the kind of crunching of data. And that's where that curriculum 201 is really focused on that type of work. When you're crunching data, how can you avoid kind of data quality issues. The redundant data, how to deal with it. What to do when there is a problem with a data source, and there is some tooling aspect of it. So it creates kind of a concept about data quality and cleansing, but also tools on what's best practices when dealing with big data, when dealing with kind of structured, unstructured data, because these are people kind of the analysts and the data scientist of the bank.
Adel Nehme: And what type of tools do you prioritize in the program? So, for example, what's the split in terms of coding tools versus non-coding, business intelligence tools?
Mai AlOwaish: Right. It's, again, we have to kind of even slice and dice that further, because in the bank, we have, like I said, 140 ambassadors, which vary in skills and based on their role, based on their skills, based on what type of work they're doing, the tools differ. So there are some kind of the, we call them the explorer analyst, which are people who are just doing ad hoc reporting and kind of basic reporting for day to day, operational reports, I would call it, and these people are kind of trained on Tableau for a tooling perspective.
Mai AlOwaish: And then there are people who are kind of advanced or the power users, where there's some R or Python that they have to do, because they're building that into Tableau. And these people, we kind of, when we did the ambassador program, we did the breakup for what I call them, the different batches or different groups. But then we kind of did another breakup where we had the power users versus the explorers. And then they, when we do the tool training, we kind of change the whole structure. And it's nice because they get to see different people at different times and that's the whole point, like I said, of the community of ambassadors.
Creating Enthusiasm and Excitement Within the Organization
Adel Nehme: I love the granularity that you've applied in the program. As a leader, how do you these types of cultural or transformation programs? What are some of the best practices that you can share around creating enthusiasm and excitement within the organization?
Mai AlOwaish: Yeah. That's a great question, and honestly, that was one of the biggest things that we wanted to start with as hammering down before we go into the curriculum stuff, because I said, listen, whenever you see someone leave their job to go to a training, people just don't think that they're going to go have fun in training. And if you tell them, okay, let's do this training online on Zoom, they're like, okay, I can just turn it on and then kind of give it half of my attention and do other stuff. It's that kind of stereotype of training not being always the things that you'll go and have fun. And we wanted to, like from day one on that training, we wanted to make sure we have exactly the opposite, to make sure that they know that this training, how much does it impact them, kind of giving them a sense of what they're learning in this is going to affect them as an individual, going to affect their department and the bank overall.
Mai AlOwaish: So giving them the big picture, helped [inaudible 00:25:06] those ambassador engagement, to become really engaged. So one of the things that I highlighted on the first session was that you're going through this ambassador program and we're teaching you how to better use the data of the bank, or better analyze and do all of the good stuff with data. Now, this may help you as a department be more kind of creative with your data, be more efficient with your reporting, and that will help kind of the bank bottom line, but at the same thing, once you learn this, there is, and I highlighted kind of different tracks for them on how they can get certified. How does this affect their career growth personally, as an ambassador, as an employee, as an analyst? And we now just said, with this investor program, you can do this certification.
Mai AlOwaish: Oh, I had like three or four different certifications on that screen because some people are more focused on, for example, when I said Tableau, there's Tableau certification for analysts, but then there's some people who are really focused on kind of the data dictionaries or data governance and so on, and that's where we said there is the DAMA certifications where people love to get on that track. There is, for risk people, there is tons of different risk-specific data certifications. So a lot of people sometimes go on the training and yes, they know this is helping them do their today job, but if they know there's something also in it for their career, that helps them really grasp that this is also valuable for me as an individual. And that's kind of once you get them hooked on the value of this.
Mai AlOwaish: And then now, after we started the training, we really need to make it fun. People, I think, were very excited when we did a lot of the props at all the training and kind of give it that viral aspect. We had a lot of youth in this program, giving their the analysts and most of them are juniors, so we wanted to make sure that any picture that we took during the program can become viral. And it really helped with, previously when we had some people in the bank, they were saying, you know Mai, I don't know if I should be part of this training. I really don't know about data, or I'm really not a technical person. Why should I be an ambassador? I get these reports and I review them and that's it. And I said, you know what, just attend the first session and we'll talk about it.
Mai AlOwaish: So those are same people that when they were saying at the beginning, am I able to come into this training or do that? The next session, they were calling my team and they were saying, oh, when is my next session? I'm excited to learn more or do more because they understand that they're part of, the learning of this is really kind of for them, and that data is for everybody and not for the technical people in the back.
Most Challenging Aspect of Cultural Transformation
Adel Nehme: That's amazing. And I really appreciate how you approach this with humanity and empathy, and how you explain the value of acquiring these skills for your people and for their futures. Now, what do you find outside of skill transformation to be the most challenging aspect of cultural transformation?
Mai AlOwaish: I think once we start with changing these cultures... Technology is a, of course, a major driver, but the being agile honestly, is the main important part of being in a transformation and helping you transform faster, because people have become impatient, I think, in the recent age, but they expect things to happen, and if you wait too long for that project to launch, people may just lose interest. I think the Agile process have really kind of provided the great solution for this, because now we launch something, we have some data to give us some feedback, and then, we prioritize, we kind of even optimize it further and do more. So the ability of becoming an Agile organization, I think really helps the transformation chain
Mai AlOwaish: And in terms of whether it's culture or if it's technology, or if it's abilities, even the people that they, once they get into that Agile mode, they know that they're continuously shifting, and they're able to accept changes faster. Prior to that, people hate change and they would resist it every time you changed something, whether it's a system or a process, people would resist it and they'll get mad and they try to stick to their good old ways, but kind of confirming, or kind of giving those people that we are going Agile, and this is how we become Agile, and that change is just the only constant, and we can live with that.
Mai AlOwaish: I think it will help people drive those, whether it's culture, whether it's process, whether it's anything, it's going to be... People will become more flexible and more resilient to those changes.
Adel Nehme: That's awesome. And I feel like it must be harder to instill as a quality within the organization rather than data skills, for example. What are some of the tactics that you've used to reinforce agility and resilience within your teams?
Mai AlOwaish: So in terms of data skills, just whenever somebody hears data, they think it's technical, they think it's for geeks, or they... Even one of the management here, like, I really met your team and they're not really those data geeks with glasses. And I said, yes, we're not geeks, and data is for everybody. It's not for just highly technical people.
Mai AlOwaish: Anybody is somebody who's working with data. I said, even your branch teller, he is somebody who creates data, so he is a stakeholder in this data game. He doesn't need to be an engineer or a data scientist or a computer scientist. And that's kind of the things that we wanted to focus on when we did this training program.
Mai AlOwaish: And aside from the training program, we were doing kind of something called the data chat across the organization and our social channels, like internal social channels, to just make people hear that data is really for everybody, and as an organization, as we're transforming, data is becoming part of our regular kind of assets or things that we work with every day, just like you sit on your computer, you realize how much data you're working with every day.
Mai AlOwaish: So just the recognition that data is not really a technical thing. It's just whenever you're filling an account application for a client, you're working with data, and that just helps them see how much this is part of our day-to-day work really.
Adel Nehme: Now Mai, before wrapping up, I think what's exciting about the data ambassador program is that it really broadens accessibility and inclusion for data science within Gulf Bank.
How To Broaden Data Science and STEM
Adel Nehme: But I'd love to discuss how to broaden data science and STEM in general, across the board. Both of us come from the Arab world and you being the first female chief data officer in Kuwait, I really admire your journey and how you've paved the way for other female leaders, especially from the region. What do you think needs to change so that data science becomes even more accessible and diverse today?
Mai AlOwaish: I think one of the things is we... And to me, I was always passionate about having more women in tech, and now I like doing the same thing with women in data, and just making it available for everybody.
Mai AlOwaish: I think, and I remember when I first worked in tech, I was always the only girl when I was in college, or in the IT department, the first department, I was always kind of... It's hard for that inclusion to happen back then in 20 years ago, but I think right now, it's much easier because when, in my generation, there was no tech leaders who were women for us to look up to, as young girls who's going into college or finishing high school or doing the STEAM program.
Mai AlOwaish: It was hard for us to find those kind of female leaders to look up to and want to be somebody, want to be like them. Right now, it's so much different and I'm just very happy. And I think the way we're seeing how much leadership is being diverse right now is really a promising change, but I think one of the things that also organization need to invest in is to make sure that this leadership is a hundred percent diverse, because once you have that diversity in leadership, it will automatically reflect on the younger kind of staff, and then that will kind of reflect on the overall kind of community or organization that we have. And I think making it, as I said, like when we're trying to do this ambassador program, we're trying to make data available for everybody.
Mai AlOwaish: I don't think anybody will be afraid of data anymore, and that's how, once we try to normalize it, people won't be too kind of annoyed by saying, okay, you're working with data, or afraid or kind of just scared of that, oh, I need to do this data thing. It's not a... And the same thing we had with technical where people were like, oh, I'm not technical. That's the first thing I hear with a lot of people when they talk to me. I'm not technical, but I said, we're not talking tech here, and even if you do some stuff on your computer, you might be doing already these technical things.
Mai AlOwaish: So I think the youth, they do have a lot of more potential right now, just because back in my age, there is not all these STEM programs going around for kids. Right now, my kids are five and seven, and there is some coding program that we were playing around with. I've never do that back in my age, but now these programs are available, the tools are fun to do it, and I think once we have more kind of diverse leadership, I don't think we'll... I think the future is much brighter.
Adel Nehme: That's amazing. Finally Mai, any final words before we wrap up today?
Mai AlOwaish: No. Just thank you, Adel, and thank you DataCamp for this, honestly, and I love how DataCamp is making data for everybody. That's something that I kind of preach for here is that data is really for everyone, and we want to make sure that for the future that we're going into, for this digital future that everybody's going through, I think, like I said, data's not scary. Data's not too techy. Data is for everybody and there's a lot of resources out there. If you have just a tiny interest in learning something about it, whether online or in your organization, I think it'll open up a lot of aspects in your career.
Adel Nehme: Thank you, Mai, for coming on DataFramed.
Mai AlOwaish: Thank you, Adel.
How to Become a Data Scientist in 8 StepsFind out everything you need to know about becoming a data scientist, and find out whether it’s the right career for you!
YOLO Object Detection ExplainedUnderstand YOLO object detection, its benefits, how it has evolved over the last couple of years and some real-life applications.
5 Ways to Use Data Science in MarketingDiscover five ways you can use data science in marketing. Get ahead of the game, improve your data skills, and work on a data science marketing project.
How Data Science is Changing SoccerWith the Fifa 2022 World Cup upon us, learn about the most widely used data science use-cases in soccer.
The Deep Learning Revolution in Space Science
Justin Fletcher joins the show to talk about how the US Space Force is using deep learning with telescope data to monitor satellites, potentially lethal space debris, and identify and prevent catastrophic collisions.
Regular Expressions Cheat SheetRegular expressions (regex or regexp) are a pattern of characters that describe an amount of text. Regular expressions are one of the most widely used tools in natural language processing and allow you to supercharge common text data manipulation tasks. Use this cheat sheet as a handy reminder when working with regular expressions.
DataCamp Team •