 Hello and welcome to My Career in Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host, Shannon Kemp, and today we're talking to Cindy Cain Fitzgerald from Antioch University. With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year, the Data Diversity Training Center is your launchpad for career success. Browse the complete catalog at training.dativersity.net and use code DVTOX for 20% off your purchase. Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer at Data Diversity, and this is My Career in Data, a Data Diversity 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 helped 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. Today we are joined by Cindy Cain Fitzgerald, the Manager of Business Intelligence Analytics at Antioch University. And normally this is where a podcast host would read a short bio of the guests, but today, and in this podcast, your bio is what we're here to talk about. Cindy, hello and welcome. Well, thank you, Shannon. I'm very excited to be here. Oh, I'm so excited for you to be here because I've chatted with you a lot online in webinars and our webinars and stuff, and you've always been a huge part of the DataVersity community, which we always appreciate. And now you're gonna be speaking at Enterprise Data World in Anaheim. I'm so excited about that. I can't wait for your talk. I'm very excited about it too. It's my first time in attending an in-person university event. I'm really looking forward to it. You'll have to let me know what you think afterwards. I'm excited. What's your talk gonna be? I am going to be discussing the upside to compliance reporting. The real kiss what? I promise. I love it. I see it as an opportunity to really enhance data governance at an institution through the lens of compliance. So that's what I'll be discussing. Very cool. So tell me, Cindy, so you are the manager of business intelligence analytics at Antioch University. Tell me about Antioch University. Sure. Sure. We're a private not-for-profit higher education institution. We're a multi-campus, multi-state institution with campuses in New England, Ohio, California, in the state of Washington. We also have online and low residency options in undergraduate, graduate and doctoral programs. We offer degrees, certificates, licensure and professional development opportunities in a broad range of disciplines, creative writing, education, environmental sciences, leadership, management, transformational change and counseling, psychology and therapy. Oh, very cool. I didn't realize that you had so many campuses. Yeah. And actually, I think that positions me well to talk about compliance because being a multi-state institution really complicates the compliance landscape for our institute. I'm sure. So then tell me then, so as the manager of business intelligence and analytics, what do you do for Antioch and what is your typical work week look like? Well, I'm a fully remote employee so I spend a lot of time on Zoom. Yeah. Elaborating with colleagues across the country. And I have a pretty broad range of responsibilities. My typical work week has a lot of multitasking on multiple projects. I build and maintain an enterprise reporting system that is designed to meet both internal assessment needs as well as external compliance needs. And every year around this time, I need to check and see if there have been any changes in compliance requirements that need to be modified in my system. So that's currently happening. I'm managing a data strategy project right now to ensure that we're accurately and consistently capturing critical data related to new strategic initiatives. We're implementing new budget planning software right now. So I'm working to extract the right data for the integration between those two platforms. And we've just started the annual review of our institutional data glossary and I'm sharing that process. So that's an example of what this last week looked like. Oh, that's very cool. So you work a lot with data. I do. I do. So tell me those, Indu. Was this the dream when you were, you know, six years old, very young, you know, did you think to yourself, I'm gonna grow up and be a manager of business intelligence and analytics? Absolutely, absolutely. So top of my list. No, I wanted to be an actress. That's what I wanted. Yeah, I really did. But that didn't quite work out for me. So here I am. Let's talk about that journey then. I love that. So when, as you got older, you know, and through, you know, your schooling, you know, what did your, how did your interest types change and then where did you go from, what did you start focusing on initially? It's interesting. My background in education is not gonna take us anywhere near data. It just isn't because that's what I studied. I'm actually in the field of data management and I've been here for 25 years, but I'm here entirely by accident. Really? How did that, how did that, do you see majored in education? No, actually I was majoring in communication with a women's studies minor at San Francisco State University after a lot of moving around between different types of performing arts. In San Francisco, I was the director of development for the San Francisco Women's Building. That's what my, I had an entire career as an advancement professional before I started working with data. And the dot-com boom was happening and I did major donor work. So I was on the road all the time and I had a new baby boy. And we decided, my husband and I, to relocate to Vermont, which is where he is from. But there were no remote work options back then. And in the state of Vermont, there's a lot of volunteer work that is tapped to actually do fundraising for nonprofits. So many of the jobs were only a few hours a week, limited hours, limited salary, limited benefits. So I ended up taking a job with world learning, the school for international training as a database manager. I didn't have any experience managing a database. I didn't have any data management at all experience, but they didn't hire me for data management experience. They hired me because I understood the business needs of a fundraising professional. They hired me because that was what was missing from their technical support is having somebody who had that business acumen. And as my boss at the time told me, anybody can learn to program, it's just syntax. So most of my learning has been on the job. I was a junior programmer for a while at SIT when Antioch recruited me. I shifted focus more to business analysis and functional analyst for the administrative departments. Shifts at Antioch moved me to be the analyst programmer for just HR and finance. And then in 2014, the office of institutional effectiveness was founded. And I was tapped to become the programmer analyst for OIE. And that's where I still sit today, but my job has evolved to be the manager of the business intelligence. And I love that a lot. And so you're searching for a job in this new state for you, right? And just trying to find something. Do they really focus in on, I mean, is that the job description? Just to, I did not apply for the job that they hired me to do. My background in advancement was really focused on personal one-on-one fundraising. Although as a director of development, I did grant writing, I did special events. I did the whole gamut. My specialization was really a major gifts program. And the position that they were hiring for was a director of corporate and foundation giving, right? So they didn't see me as a right fit just for that job. But over the course of the interview, the CIO was in the room, was on the hiring committee and she pulled me aside and said, I don't think you're gonna be a right fit for this, but I have a position in mind for you if you'd be willing to consider it. And that's what started me on this path today. That's so exciting. And I love that you weren't afraid to say yes and that you dove in and learn. Did they provide the training or did you just dig in and? A little bit of both. I went through three different platform transitions, three different migrations with them. So there was always training that came as we were moving from an older system to a newer system, right? Kind of focused around the new architecture and the new buttons and gizmos that you needed to use to access your data. I think though, starting my career the way I did, I don't know, just made me less afraid of data as if it was a foreign concept. You know what I mean? I really did buy into, you know, she taught me some basics. Oh, my very first job working with them was the whole Y2K panic. I had to go higher, fundraising database and expand all of the two-year, two-character year fields to four-care. I mean, by the time I was done with that, I was like, I don't have to do this. I can take the same concept and apply it, right? Right, right, right. So something about my backdoor entry into this field allows me, I think, to approach it differently than somebody who studied to be a data architect or studied to be a data scientist. Sure. I'm a real generalist. And I think it works. I, yeah, and you know, we've heard a lot of stories like that, you know, just really, you know, to be in data management, you need to understand the business. You need to be curious about the business and have that skill in order to be successful. Absolutely. And if you think about it though, Shannon, degrees in this field and certifications in this field, they're relatively new. The CDMP has only been being offered for the last 25 years. Think about it in the context of other degrees that you might have pursued, or that I might have pursued when I was an undergraduate. There weren't degrees in this field, right? So it's a rapidly changing landscape and I think flexibility is key to longevity. I agree, yeah. So Cindy, tell me, what's been your biggest lesson to find in your career? The fancy technology, right? Having the right fancy tools and using exactly the right hip language, the right turn of phrase that is hot in our industry at the time. That's helpful, right? They're both helpful, but they don't replace the need for basic common sense, which for me is at the heart of quality data management, right? I like to say to any executive leader who will listen to me, that if we don't manage our data as an asset, in the same way that we manage our fixed assets and our financial assets, then we risk it becoming a liability. And the problem is data debt is invisible, right? It doesn't show up as red ink in the balance sheet at the end of the year. So it can accrue exponentially without any real understanding of what it is at the executive level. So common sense is pretty important. And then the other thing that I would say is that really understanding the data lifecycle is critical. You can't harvest roses if all you have planted is beans. That's another one of my analogies, right? Right, I love it. We reap what we sow in data as in life. And so it's really important that we think strategically about that point at the beginning of the lifecycle, data creation, data collection. Are we doing it in a way that is meaningful and sustainable and meets broad enterprise needs, not just the need for a student to register or a bill to get paid, but thinking about the whole data lifecycle picture. Very true. So, and you mentioned data debt a little bit ago. So data debt, tell me a little bit about data debt. How do you accrue data debt? What is that? I'm still rubbing my head around it actually. And I have a fantasy. I have a dream that I'm gonna develop a model that can be easily adapted by small institutions like Antioch to help mid-level administrators like me express data debt in a meaningful way to the executive suite so they can understand it. But I'll give you a real practical example. Antioch is a multi-campus institution. And not that long ago, our institutional governance was completely decentralized. Every campus had a board, a president, a registrar. Every campus had a faculty senate, their own academic calendar, their own academic catalog. All of that data lived in a single ERP system, but it was managed according to campus-specific processes and values. The upshot was that not only did we have the silo data that you anticipate that many of us see were siloed by business function from HR to finance to academic affairs, we had additional silos that were campus-based. And we ended up, a campus our size, I think we had a little over 150 unique department values. And we don't have 158 departments. We just had 158 ways of describing the departments that we do have. So I use the analogy that if we had a department called Blue, one school called it Teal and one school called it Navy and HR called it Aqua. And therefore there was no way for us to aggregate up and get that 30,000 foot view in our analytics that executives are always looking for. So that's data debt. It's invisible because people like me for years simply made it work. So the executives were able to get the reports they needed. They just didn't have any idea how long it took and how much labor was actually involved. And the fact that that process wouldn't really be replicated because it wasn't relying on any consistency in the data. We just underwent a pretty big project. We updated over 2 million data points in our system of record. And I am happy to say that all departments in all business units across multiple platforms are now consistent. So that's us embracing some data debt. But it was a big investment to get rid of it. It would have been a lot cheaper to plan for it at the beginning. Oh, that makes so much sense. And I love that you're dreaming about it. I love the solution. If you figure out that solution, will you let me know? I will publish it far and wide. You bet. Oh, that's awesome. 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 tell me, Cindy, what is your definition of data itself? And that's a good question. Because I think it's changing all the time, right? So I don't think I have a static definition of data other than perhaps this. Data is information that we need to access in some way, understand in some way, and then take action in some way. But maybe that's an image or maybe that's a set of images or maybe that's a file or maybe it's a date or a year or some of the other concepts that we traditionally think of as data. And I think I've already described to you that I'm a little bit of an odd bird. I'm a little bit IT, I'm a little bit end user, right? And I don't have technical training or background in this field. It's all sort of hands-on DIY, right? I learn a lot from the diversity talks that I attend. But I do a broad range of working with data. I work with end users to clarify what their business needs are and to document them clearly and then connect those needs to the available technology. I help them create procedures so that we can maintain high data quality. But then I can also translate all of that into technical requirements. I can either hand that off to another programmer or I can take those technical requirements myself and build what needs to be built. And then once we have all of that, I can work with it at the back and develop reports, develop a BI environment that those reports can read from and set up reports to be delivered. And I kind of do all of that over the course of my week. I spend a lot of time on governance though. And I have to say, I know that there's a lot of mixed feelings about it, but I'm a fan. I really like my work in data governance a lot. Oh, I love that, yeah. And I know there's a lot of people who, we get questions about this all the time and you've seen it in the webinars too, like my boss thinks that data governance is a dirty word. They don't want to go anywhere near it. But it's such a good thing, right? At the end of the day, it helps to resolve those things like data debt and it helps so much in providing value to the business. Absolutely. So here's a great example. It ends you off, like most institutions, we have an academic year that has a start and an end. Like most other enterprises who have a fiscal year that has a start and an end, ours don't happen to align, right? So you need to know that and understand that if you were trying to bring together data from the academic side of the house with data from the finance side of the house, you need to realize that there's a slight overlap and mismatch, that can occur in data governance, right? That kind of conversation can happen in a data governance conversation where it's unlikely to happen in other administrative meetings. And I am fascinated by those conversations. I really enjoy those types of conversations. I love that Cindy. And you make the point too, right? Data governance is not just about following the letter of the law and complying with legal matters, right? Which is why so many people are like, oh, I just don't want to deal with this, you know, which sounds not fun, but it can be so much fun. I think so. Yeah, I think so. For many, they think of data governance as simply getting to the point where you have policy. And then we're done. We've got a privacy policy. We've got a security policy. But I would argue that if you don't have procedures that align with that policy, then you're not done. Right? You have to take it to the practice. You have to make sure that your people processes reflect your governance policy. Yeah. Yeah, very true. So Cindy, 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? Well, I see the importance increasing be exponentially with the growth of our data sets and all the different platforms that we all need to navigate these days, right? Data is the new oil, right? Isn't that what they said recently in The Economist and it's true? I am really interested to see what's going to happen in the next couple of years in the field of data management as it relates to AI. But honestly, I'm not sure AI can ever replace people. People fully replace them. Every single example that I've given you in this interview, AI couldn't have untangled the knots that we had tied ourselves into, right? It took people and not me, not person, it took people coming together, thinking together outside of their own area, putting on a completely different hat, looking through a completely different lens, right? Having a conversation that helped lead us to a better place with our data. And I know there's a certain amount of that that can happen with AI, but I just don't think that process can ever fully be replaced. Our data's here to stay and they're gonna need people like us to wrangle it for them, whoever they may be. I absolutely agree and we're seeing a lot of that. So many companies are trying to stand up all these really cool tools and tech, especially in analytics and suddenly are realizing that they forgot the data prep, they forgot the data governance to drive the data quality and went, oops, wait, oh, we also need a data model. We also need somebody to manage and create all that, create the model to design the architecture and to ensure that we have processes in place to drive data quality. Right, and to make sure that when we say blue, we all understand what blue means. One of us doesn't think it's purple, right? It's called blue, right? I love those analogies. Cindy, what advice would you give to people looking to get into a career in data management? Well, I think that understanding the business need is essential. So developing your skill set as a business analyst is a really important beginning. I would say that understanding the data lifecycle is critical and understanding that the investment early in that lifecycle pays off that your biggest return on investment is investing time in the creation and collection phase. And then I see the tools and technology and language change rapidly, but the fundamentals generally stay the same. Yeah, very, very nice. Very good advice. And I would argue too, like that we're seeing a lot, I'm learning a lot from these interviews, just that curiosity that you talk about. So finding out what are the business needs? Not assuming, not dictating, just what are they? And then trying to meet those needs. There's a real talent to eliciting business needs because people are prone to coming to you with a solution in mind. They know what their need is and they've already decided the solution, you just need to build it for them. And it's not uncommon for that solution to just not be feasible, given the data architecture that you have or the tools that you have available or the resources or the timeline, right? So really helping them, really digging out, well, what is it that you're trying to get to? What is it that you need to do? Say more about asking those open-ended questions and giving them space to really explore what their need is rather than focusing on them, telling you what I really need is an API that does these five things, right? Let's back up to why you need the API and how it's going to help you in your work and then that's gonna help me get you the right tool. Very true. Well, Cindy, this has been such a pleasure. I've really enjoyed talking with you. I've enjoyed this as well, Shannon. Thank you for the opportunity. Oh, well, thanks for joining me and thanks for participating so much and being such a great networker and in our webinars and such and being such a great part of the community. I'll see you in a couple of months. Yeah, a couple of weeks. What? No. Yeah. It is, I know it's coming up so fast, the third week of September. Yeah, and Elheim. There you go, I'll see you then. Yeah, I'm excited. It will meet me in person. Yeah. So, oh, Cindy, thank you so much for taking the time to chat with us today. And again, for all of our listeners out there, if you'd like to keep up to date on the latest in podcast and the latest in data management education, you may go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. 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