 Hello and welcome to Dataversity Talks, a podcast where we discuss with industry leaders and experts how they have built their careers around data. I'm your host, Shannon Kemp, and today we're talking to Dora Bousias, the Senior Director of Data Strategy and Architecture at Striker. With a robust catalog of courses offered on demand and industry-leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.dataversity.net and use code DBtalks for 20% off your purchase. Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer at Dataversity. And this is My Career in Data, a Dataversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who make those careers a little bit easier. To keep up to date in the latest in data management education, go to Dataversity.net forward slash subscribe. And today we are joined by Dora Bousias, the Senior Director of Data Strategy and Architecture at Striker. And normally this is where a podcast host would read a short bio of the guest, but in this podcast, your bio is what we're here to talk about. Dora, hello and welcome. Hi Shannon, thank you for having me. I'm so excited to be here and having this chat with you today. I'm so excited you could join us today. I really appreciate it. A long time friend of Dataversity. We just love you and really excited to hear more and learn more about your career path. So tell me, so you're the Senior Director of Data Strategy and Architecture at Striker. So what does that mean and what is it you do. Okay, yeah, thank you. Thank you for the question. So Striker just to put a little bit of perspective it's in healthcare it's a medical technology company we're actually the leader in the space. So that means the company designs manufacturers commercializes you know medical devices medical equipment. So my role is definitely very close to data strategy and architecture we're saying it's really driving data strategy and architecture for the company at the global level. So a lot of this focuses on the, the governance the MDM the stewardship the quality the data information architecture of things I'm, you know, and, and set up this this new function from the ground up for the company with my peer on the business side. We're co accountable for this program on the architecture side it's architecture for, you know, across domains across commercial divisions across regions across different other functions. And it's the architecture for anything from the terms actual side of things all the way to analytics. And it's an area that I'm really very, very passionate about. Now, we're talking about data, and obviously some of the technology aspects come into it but I always, you know, Shannon for the longest time I always say and I believe this and I'll leave my every day like this and I tried to get my team to think the same way. I'm a business person first and foremost. So what I do is really how do I bring the best practices around data and data management and architecture into the organization. So that I can help the patients really, and our customers, right, do better by helping my organization be a healthy organization, but better quality. Well, we've got most best quality products out there but I'm saying the products out there help the patients, you know what our business strategic objectives, so really always driving with what our business objectives first and foremost and that's why I think I call myself as a business leader first how can I do better there and then pull in anything around data and technology that I can bring to the table, myself, my team, you know the function. So, how did you then come to create this role you said you created it, and you have a business partner on the business side so where do you sit. I've actually been in my entire career, which is rounding it up to about 30 years about 20, almost 28 years now. I've always studied in it, but again, I've also because I've had enterprise architectural roles for probably the last 17 to 2017 1820 years. I don't know time time goes by fast right. I've always been in roles that that have enterprise perspective and enterprise accountability has been doing enterprise architecture always going the deepest in data. And so, I've always felt a bit of an IT it's almost like having a leg in IT and a leg in the business, especially because I'm always trying to drive with, what is this going for my business. What business goal is this going to help how can I help progress this business objective better how can I make this better for the customer or the patient or the organization as a business that needs to thrive right not just survive. So, strike like so many other companies has grown in silo so from the data perspective of things, how do we look at things across at the enterprise level, drive the synergies, obviously, data governance and trying to get to speak the same language on many things like, you know, what is a product what is a customer right where are the different KPIs, you need to bring the different silo teams together so how do we use best practices in this data management world. So, how do we go about doing that, bringing that expertise in and I've been with Striker about six and a half years now, wonderful company. Bringing that expertise really just putting the case together and say hey, here's where we can do a better, you know, better manage it. I mean, at the enterprise level drive those synergies get to speaking the link the same language common language that can help drive additional efficiencies, or can help really with new revenue streams by monetizing our data rate I mean everything around this again, in my mind typically is by management, you know, the data organization. How can I help grow my top line, because I am helping to provide a better customer experience for example, which would attract or retain customers or bringing a new revenue stream right, or how can I perhaps cut down costs by bringing in operational efficiencies streamline some processes, not having to reinvent and do the same thing data quality for example over and over again. Or how can I look at data and help that to mitigate risk be proactive about it save comma organization right so bringing a lot of that how do I drive those synergies and enterprise level kind of, you know, put the strategy together, obviously got the executive buy in. But it is very important that this is not just it driven, I look at this thing to be successful in any case, as a very close partnership between the business and technical teams. What this structure did is that this global level function, myself and my, my business partner that sits in the business, and her title is her title is senior director of business data governance, we are co accountable for driving this organization, the organization so the benefit that will come from this so we set it up at the enterprise level and you know driving and executing and seeing the outcomes from from doing this. It's a great model. Thank you. Yeah. I'm just curious. Did you. How do you find the business opportunities, whether to grow revenue or to drive efficiencies. Is it through that partnership or you know are you sitting in on executive meetings or, you know, how are you finding those opportunities where these are. Great question. So it's really being very intentional about looking at it so even, even if something data management has to do with bringing out the right technology, the right technology is, it has to enable some very specific business capabilities. And those are the business capabilities that we will focus on because it will help a very specific business problem that we're trying to solve for, or, you know, business objective that we have so the opportunities are all around us. There is so much really that we can do in our organizations and Shannon with like I said almost 28. I'm typically rounding it up to almost 30 years right now being exposed to a lot of different verticals right of working finance and insurance a bit in retail and healthcare medical technology here. I'm saying this because I'm seeing it across verticals of experience it right the opportunities are there and we do have the opportunity to better manage our data to really get more out of it right so prioritizing actually I think it's a harder thing to do versus finding the opportunities. There's a lot of opportunities I think is how to prioritize what we focus on being very close partner with my business counterpart helps but you know, I always say to really successfully understand and get value out of implementing a very intentional and thoughtful data strategy, it's not one person or two people or one team, right. So we really that partnership really understanding, you know, what are the strategic what is the business strategy, what are very specific strategic business goals. Okay, so taking that. How does that with that connect with the data strategy. How do we, you know, stop prioritizing the demand there seeing what is the biggest impact I mean we have different frameworks that we've developed us to. Okay, all of these areas could be areas that we can do better. We did develop framework that looks at, for example, you know, what, what is the risk, how is he helping us from a financial perspective from a risk perspective from an operational efficiencies perspective right. And so we apply that, but also initially we even interviewed across the organization really trying to understand, okay, we kind of know we think we know but let's just put a little bit more structure on this so we actually did interview across regions and functions and say, Okay, what are your biggest problems that are related to data, especially master data, because we started focusing its multi year roadmap and a journey but we started focusing on very specific data domains, and even within those data domains we prioritize, but we kind of knew the issues, but we did try and just hear from the organization across the organization. Why are your biggest problems. The biggest problems in terms of what gets delayed or what gets what it's broken, what can become even better from a business efficiency or effectiveness or opportunities. So we took all of that was synthesized it we looked at it. We connected to our bigger business strategic objectives we put a plan together. We agreed this is what we're going to focus on. And that is important to do actually because then, as a lot of demand comes from across this global strikers of 17 plus billion dollar organization it's a large organization right 46,000 people. So having a very well known and intentional roadmap in terms also of not not just the processes and the tools, but what business problems are we going to solve. What did we focus on to solve this particular business problems. That helps us because the demand is always coming. So we're staying true to, you know, we've done the work. We looked at all the issues. These are the highest ones in terms of the business impact. We're staying true to that. Of course, sometimes things to come that we might need to, you know, reassess and pivot can just be locked without really taking into consideration the situation at the time. But that's typically how we do it and it's a conversation with the business and the technology teams really to because from there you learn a lot about hey, there is an opportunity with a business here that process keeps breaking for example because of the data quality issue. I'm making it out, but I mean that could be a, you know, I think that's very usual thing that we see and it's an education over not over an area that you know we can we can improve on. I love it when you mentioned, you know, you've been sitting in it for a while and you have quite a bit of experiences and enterprise architect, but so let's back it up then a little bit. So when you were a child a very young child that you dream, I'm going to be an enterprise architect when I grow up. What was that dream what was that original dream. Not quite, I didn't know. I didn't know anything about data. Folks may not know I was actually born and raised in Greece. And, you know, I was going to high school it was actually a brand new model of a high school setup. And I pretty much had to make up my mind as a junior in the last senior year of high school. What would I focus on and at that point you know I used to love reading and writing. And I always thought, you know, I want to go into literature want to be a professor of reading and writing literature and things like that and that's Greek right because I like I said I was, I was born and raised in Greece. But it just so happened I also took this basic basic the programming language which I liked. And to be honest, Shannon, the decision. It was a very practical decision I said, Okay, at that time there's about 40,000 people waiting to be hired on, you know, to be a professor back then there was not too many private schools colleges it was mostly you know state colleges where the situation is different. So it was really very practical decision saying, by the time I go through the right schooling and able to get a job like that will be a lot more people waiting to be hired. I love this but I also want to be able to make a living. I like this basic programming this is different. I really think this will be the profession of the future. So, you know, I made a decision on that point to focus more take more courses like that. The last year of high school and then after that, I, yeah, I made a decision to come to the United States. I have two siblings that were already here to study computers, the software side of things. The schools were not as good in Greece at the time so I came here plus I have my siblings here. So, yeah, my first degree was an associates in data processing. That was my very first degree. Wow, that's amazing so you say your first degree how many degrees do. So it's just from this technical school in data processing was very much computer classes I said this is crashing the surface. So then I went to Quinnipiac in Connecticut I got my bachelor's in computer science. Actually with the bachelor's I had to do an internship, a three month internship to even be able to get the degree in hand. And I did that but that internship turned out into full time job offer, which I accepted. And that's how I started really being an IT. A year later I went back a year later I went back and I did my MBA. In terms of formal, you know, academics. I never really stopped learning. I mean to the day I think I'm going to keep on learning I'm very curious inquisitive you know after on a couple of certifications after that but the most formal in terms of degrees was was those three. But about that time is when I started in IT and really I started as a mainframe cobalt programmer. I was a cobalt and JCL and a sampler and working on IMS and DP2 databases are learning about hierarchical and relational databases on the mainframe. You know how I ended up with enterprise architecture to your point. Because I always want to keep on growing and learning. I actually, although I was doing mainframe and writing cobalt programming and JCL and CICS during the day in the evenings I would teach myself new skills and back then in the 1990s I basically taught me the entire thing Microsoft Office suite, including access which I got Microsoft certified back then, but access is a database right back then. You have the database you have a little bit of programming the reporting all of that. So that got me out of the mainframe I got into rapid application development team as it was called the RAT team. And more software programming. Fast forward the one thing that I realized. I don't know how I don't know why, but even when I was doing mainframe you know cobalt work I realized that at the end of the day. When I was doing when I was part of the cobalt team we were producing a lot of the financials for the company, which was a retailer. I realized we're looking at these reports, we're creating these reports financials that we're going to the CFO of the organization and other CXOs of the organization, looking at these things so I realized. Okay, this is data, we're looking at this like our decisions have been based on this so it's very important that this is good because, as we say, if I look at garbage garbage and garbage out. And being also software programmer you know I had the opportunity to actually do everything from gathering requirements to designing to building to training like I even as part of the RAT team I build a whole platform that basically was kind of like. Yeah, a whole platform for the loss prevention department back then everything from the day to day to the actual functional capabilities to because it was its own silo to you know they chart components of that department. So I ended up doing the whole thing and what I realized is, okay for this to really sustain, I have to have a really good solid architecture. So I was really passionate about is the data I'm looking at good. And am I building this in a way that is not going to break that it's going to sustain like how good is the architecture. And I've always looked at somehow you know okay how solid is this what else is impacted what's going to break. And throughout the years ended up getting into enterprise architectural roles like I said for the past 10 or no closer 20 years now I've been in EA type of functions, which is important because I've always been driving without enterprise mindset be data technology be business processes and capabilities. What I'm doing here, who else will be impacted downstream upstream. How do I design this to be a very solid foundation that as new demands come. I don't think flex can scale. And no by the way, what I'm looking at what runs through those finds that data. Again, garbage and garbage out so how do I make sure that it's really good data. And having worked for financial services company when the crisis happened. We had to figure out everything that's when I got deeper into the whole MDM and data governance and data and information architecture. And that's the quality aspects of it. A couple of things here. So what made you decide to get an MBA what was your focus for your MBA. Thank you for the question. I think for me, it was. What I'm looking at these executives are based in the decisions on they're making business decision. So for me it was like okay this is great all the technical stuff. But what are we doing that for. I, you know we're not building the system just for the sake of the system it actually is doing something for the business. Okay, I don't know it was just in my mind, it was almost like, I want to combine the technical expertise with understanding more about the business so how can I use this technical expertise as a tool to help my business go forward so it wasn't that was just a thought. I don't recall like a particular thing that triggered other than just that thought. We're doing this, these executives are looking even as simple as these financial reports, making decisions. So there's a business usage for this. How can I learn more about the business surrounding a better business. So that's what really triggered me to go morning to get an MBA versus a master in computer science for example. So something that I continue to drive with this is why even when we start I said I think of myself as a business leader first and foremost. You know, even though I sit in technology and it and little secret here when people say you know business and it and I say sometimes too but it's it's like it is part of the business. That's cool of thought. Right. And interestingly, you know, I say this, even to my team when we're talking about what we focus on. I always say, okay, what are the technical skills. What is the functional and business acumen side of things what can we get better there. And also by the way also communication, we can forget about communication and leadership behaviors to me those are the three buckets that I always for myself but my team the people they work with or or I mentor you know I always look at this at what is the technical skills if this is the area what is the functional business acumen side of things that we want to focus and develop on and then even though we're technical it or data you know the communication and working with people and the leadership behaviors are important too. They absolutely agree and very interesting I love that path and mindset. I think it's one of, as you mentioned curiosity. I'm trying to hear, and just natural desire to keep learning, which is, you know, very impressive. Visit dataversity.net and expand your knowledge with thousands of articles and blogs written by industry experts, plus free live and on demand webinars covering the complete data management spectrum. While you're there, subscribe to the weekly newsletter. So you'll never miss a beat. So, having been in data for so long, then as being having it being a huge part of huge focus of your career. What is your definition of data. Yeah, what an interesting question. And I forgot to say by the way I spoke about software programming but I mean I did go deeper in data data so I've done data engineering data modeling databases I was a DPA was a data modeler. I, you know, was a data developer all of that stuff. What is my definition of data. I haven't even thought about it but for me. So for me is, how do I, how do I look at this thing that we call data the bits and the bytes how do I put it in context to help me really decide what should I focus on next right it's an interpretation of things that what they are but but, and I go into data, not to get to technical here, and I know not everybody possibly thinks of it that way right, but data and information right so for me data, it's the very, you know, how do we represent what things are, but then I tend to think of it, putting in a business context and that's when I start speaking about information and information architecture of my data architecture data management, right. So, I don't know I haven't really thought about it interestingly now, but that's how I think of it. It's the representation of what things are and what they mean and how can that help me, helping form or drive my decision for the next thing to do. I like it. And so, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years and why. I think that we're at a, we're at a point where the jobs will probably increase and probably a little bit different to, because with machine learning and AI is doing more and more with it in terms of processing a lot of different data. There may have been jobs that people were doing that now I will pick up but I think more need for people that can really not only work with data the technical side of things, but can also communicate with folks that are not data folks or technical folks. What is important to do what we do in the data management world and what does this mean how does that help the business go ahead. So if they were going to see a lot more of those roles as well. It's almost like translators you know business, business data translators if you will right that just puts it into context, in addition to the more technical roles right. But you know with AI machine learning taking off even more and processing not only large amounts of data but just doing things and automating things that people had to do before. You may see a little bit less of those types of roles and more of the types of roles that just need to bring a little bit more of that of that context and that human side of things where we're looking at something we understand it, and we translate and what it means to how we're using it. But I certainly think that this is a field that will continue to be very, very relevant very current and very critical to the health of our businesses and really our everyday life because everything we do right. I mean, it's, I always, I typically think and say that data is the lifeblood of the organization but if you think about it even about personal lives, we can't do anything without the data that we're looking at on our phones so that we hear from other people, I mean it's all around us. It's part of life. Absolutely. So, what advice then would you give to people looking to get into a career in data management. I would say it's a, it's a great field to be in. I, the advice that I would give is there's a lot of different areas that you could focus on. So figure out what it is that you like focus on that and get really good at it I always believe in knowing your craft. You know, you may know a lot of different things but what are you known for so in the data world do you want to go more into you know the data quality aspects and the data engineering aspects the data visualization aspects. You know, the, you know, data governance, whatever it is, maybe, you know, more than one. I would say, get really good at that know your craft, but in addition to that, please be intentional about understanding the business you're in, and how you can use those technical skills and that data to help progress the business. And, oh, by the way, we cannot really do that successfully without getting really good at communicating about it. So my advice would be, figure out which area you're more passionate and passionate about, get good at it. But don't forget learning the business, speaking the business functional, don't speak in technical terms, even if you're doing data engineering, whatever you're doing when you're speaking about it, speak about it in business terms, which is why you, we also have to get really good at communication. But I think there is a great future in this space, more so than ever before in my humble view. I totally agree and it's for somebody who's not comfortable with communication how do they get better what are some resources that you found that are helpful. I say practice is probably the most critical. Well, obviously, take communication courses and communication is pretty vague, right, depending on what you want to do. Maybe it is about storytelling, right, maybe it is about presentation. Maybe it is about influencing, right, depending on the role. So again, how do we deconstruct that problem, figure out specifically what it is that we need to focus. So look for, look for training courses. So that's one thing, but then in my mind, the best results come from combining the, the learning the academic or just learning theory, the theory with the practice. So then experience it as much as you can practice it as much as you can. So that could mean that, you know, find groups that you can be part of that you put yourself into those uncomfortable situations. So practicing those communication skills that you want to get better at. You know, there's, there's groups that people. It could be things like and I'm not talking about toast masters you can do that but I'm talking for example, in your local, maybe there's a data management group, maybe there is a, you know, IT group, whatever it is, right. Go to conferences, actually practice the skills that you're learning theoretically. Speak to your manager, ask for opportunities that help you stretch in the areas that you're most comfortable with, because not only are you going to get better when you practice it, you're also going to show the initiative that you're getting out of the comfort zone when you get out of the comfort zone you're growing new opportunities open up it's actually good for your career. Right. So you can do that too, or, or, you know, find a body also, you know, sometimes, you know, before a big meeting for example you want to practice something. So the idea could be practice it, record yourself and watch it. And this is something that I learned from I was part of a leadership training program once a week long leadership program that I did with G, G, Carltonville, New York for those that know about this. And one of the biggest takeaways for me as part of this leadership program was an exercise that I had us do where they recorded us. And then we watched the recording. Now it was something around communication. And I was trying my best to, to, to get better specific things I was working on. And then when I watched the recording back and watch myself for the exercise, I could see, Oh, wow, how it is in my head, it's not how it comes across. So from there, I think a good tool is for those things that we want to try, you know, practice it, try it, but then, yeah, for something big like that, I do it sometimes. I practice it, I record myself then I watch it and then I try it again, and I try it again because it's different when you observe it from outside of you will versus in our own head, we don't always pick up on all things. That's a very good advice. And to kind of summarize so find your passion, hone that passion to a skill that you're very good at, and then step a little bit out of your comfort zone and get a little uncomfortable and learn something new and learn that soft skill of communication. If that's a, if that's not something that comes naturally. You know, I would also say, even if we are going to communication I always believe and there's always room to get better. So even if you think you're good at it, I would say keep on trying to get better, because every situation is so dynamic with communication every person that we speak with every instance that we speak with that person depending on the situation you know there's always a lot of variability there. And I would say underlying all of that be very intentional and thoughtful about it. You know, it's not just going to happen. So what I've learned throughout my career. Everything that I've done, it didn't just happen. I had to work for it. But the other thing that I've also learned is that there is no big bank things happening every little thing that I've done or that I've stretched that I went over. And I think adds up, and then you look back and you're Wow, this big thing happened, but I didn't set out to do this big thing gets it's the little incremental change that actually results in like a, you know, accomplishing a teeny, you know, hitting, hitting a goal that's so much, so much bigger. So, do you really admire that about you. You know, listening to your curiosity is impressive, your desire to learn. I have this quote from Brené Brown that you know I'm here to get it right, not to be right. You know, and I think you emulate that so well you're so curious about the business and wanting to help it succeed and it's just all about that goal. And through that you've helped yourself and become really successful in what you do. It's really impressive. Thank you Shannon I love that quote by the way I love that quote I think curiosity being inquisitive asking questions curious questions. I think no one knows everything I think I'm learning right so I'm very intentional about being curious, I would say, being consistent and resilient about what happened overnight and I think, even with the younger generations I'm working, you know, my kids for example then 20s and and I know I'm like, you know, generalizing right now but I think there's some truth to it with the younger generations were more about gratification right so there is a lot of value to really just kind of go through the process like I said it doesn't happen overnight but you got to keep consistent. I'm not just reminding me I was listening to Simon scenic, a little snippet on LinkedIn the other day when he was saying about something about. I remember correctly to go to the gym, you come back you work hard you come back you don't see a difference, you go to the gym the second day. You don't see a difference we come back third you don't see a difference but if you consistently keep at it 3060 90 days later all of a sudden what happened you see the change. So, so even in our data management world, especially because and you and I chatted about it a little bit earlier right. In the role, like in my role, I drive a lot of transformation, you know, getting folks that have been used to working in silo to look at this to say how do we work together that if I do something here or anyone that works in master data management for example, right, where you got to get people to work together across lines across teams, right. If I do something here, I'm impacting somebody else right. So, so you know that doesn't driving that change of mindset habits every day. It takes resilience. It takes consistency. Right. It takes curiosity to because by being curious, you ask you learn, well, what is it really that is that this person that you're talking from this function on that region versus the other person from the other function the other team the other region. Right. It's the same problem that I'm trying to solve but how I communicate to this team versus that team in a way that can understand for me to be able to do that. I need to be curious to understand what it is that they do every day what is their function do we're all teams in the same company you know but you know this team does it a little bit different than the other. So, this may be an operations team, this may be a finance team and yet they're working with the same data. Right. So how do I get them to work together so that curiosity, asking the questions been consistent being resilient about it. I think, I think those are are very critical to lasting success really. Again, great advice and again I think you emulate those things so well it's really impressive. Thank you, Shannon, I appreciate that. Thank you. Well, Dora, well, thank you so much for taking the time to chat with us today. I really appreciate it's been fascinating. I love learning more about you and, and getting an opportunity and excuse to chat. Yes, I am honored to be here. Thank you so much for having me on and so great to see you. And hopefully our conversation is, it's helpful to some folks out there. Thank you and thanks to all of our listeners out there. If you'd like to keep up to date in the latest podcast and the latest in data management education may go to dataversity.net forward slash subscribe until next time. Thank you for listening to Dataversity Talks brought to you by Dataversity. 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