 Hello and welcome to Data Diversity 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 Gail McAuliffe, the Senior Advisor Data Management at the Canadian Air Transportation Security Authority. 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 help make those careers a little 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 Gail McAuliffe, the Senior Advisor Data Management at the Canadian Air Transportation Security Authority and she is a member and former board member of the Dana National Capital Region. 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. So Gail, hello and welcome. Hi Shannon, great to see you, great to be with you. Likewise, likewise, likewise. We've known each other for a while and thanks for all your contributions to the data management community. You were so active in so many things that we do and really been a great network and support to so many, so many others I know. So, really appreciate it Gail. Tell me what is your, and I just kind of blurred over it but what's your current job title and so what does that mean what is it you do. Okay, so I'm a Senior Advisor at CATSA, which I explained to people it's the Canadian equivalent of the TSA. The only difference is that the screeners that you see in the airports in Canada actually work for a screening contractor who's, who's been, who's been contracted by CATSA to provide those screening officers. And that's the only difference the protocols are very similar when we work closely with the TSA as well as other agencies in Europe and the Far East. So, at the moment I am, I'm here to help push, continue to drive forward the data management program. It was implemented in 2014, and it took a while for it to get some momentum and I've been trying to push the importance of data of including data management at the table as earliest, earlier in the process as possible, because I remember when I first started, one of our big, our most important identifier of data is locations and then for, you know, the airport, what terminal it's in, where is the equipment located is it and the screen lines for passengers. Is it a special line for that is wider for people with families or with special needs, who, you know, like a wheelchair they need wider access. Is it something for trusted travelers that's the industry term for if you have TSA pre check, or global entry, or the nexus pass, many of your viewers will be quite as, as people who travel for business often those people should have those that makes things much faster. And what would happen is an airport would decide that, oh, that lines. We're going to be doing some renovation so you need to close that line down and we'd find out after the fact, and, or did someone would open a new location at it at an airport. And we'd find out when someone would contact the business team responsible for the reporting and say, why am I reports long wrong I don't see this screening line in my report, or this screening line used to be family special needs now just a regular line why is it still showing as FSN. That's one of the things that you in data, always know the most important thing when you start a new, a new place is learn those acronyms, and those common business terms. I also chair the day of the stewardship team so I work with them to help with the training and I work with other people in it. And because we're a government agency data. We don't quite follow the day my wheel. So, for security classification that belongs to our corporate security department. And then we have an information management team, and they're responsible for privacy. So, it's a lot of collaboration to make sure that we're looking after the data properly. And one of the other things that I've been doing is writing the data management policy, as well as the cloud solutions policy and the data management framework for your formal documents. So, that's been interesting and, and fun. And it's fascinating. It's, it always is fascinating to me, you know, the data that people look at and that they deal with and, you know, that it's truly interesting and an interesting times. So, tell me, you know, Gail, when you were a little girl, did you dream of being a senior advisor data management when you grew up, like, is that what you wanted to be. I didn't even know it existed. Actually, my parents used to my parents are both from the UK and they used to tease me that I was like a shop steward, because I had a righteous sense of injustice so I thought, Oh, I'll be a good lawyer one day and then I realized, no, because I did, and we love to debate in our family and, you know, and I was always obsessed with fairness so that would be interesting. Then I started once I was an undergrad and met actual law students and realize, no, that isn't really for me. So I just got a liberal arts education, which often people do and as Paula Poundstone says the reason adult class kids. What do you want to be when you grow up because the adults are looking for ideas. And that was one thing I wasn't really sure what I wanted to do but I knew I wanted to do something interesting and hopefully make a positive contribution. I started off as an underwriter for a property casualty insurance company so houses and cars. And without knowing it was actually good training for data management because preciseness and accuracy are so important in insurance. Describe, you know, describe the piece of jewelry that you're that you're putting additional insurance on. And if it's a diamond, you know, it's the clarity, the cut, the color, and obviously and the size all determine the value so those are dimensions of a diamond. But I didn't know what dimensions were back then. Also, it's slowly changing dimensions. The dates are so important in insurance. For example, I have, you know, I have a break in at my house and I things are stolen. But I just submitted my application to the insurance broker, but the insurance broker has often being given the granted the authority to act to bind coverage to actually cover use as soon as you signed your application. So that application might not even be at the insurance. Well back last century wouldn't have been, it wouldn't have arrived by courier or mail. The insurance company but yes you're still covered because you know you have the effective date was the first to mark and the the break in happened on the second of March and the underwriter didn't see it until the third of March but that's okay because the underwriter would have agreed to to write it so that's that's something that really did me and also document your file my very first manager that was her mantra, which meant record the date and the time, the name of the person what agency or insurance brokerage they were from, and then the details and I've actually had my notes looked at twice in examinations for discovery pre trial examinations so I gained that's all about the data. So, so how did that lead you to your current role. What, what was your path to get into become a data management expert. It was, it was quite circuitous I'd say I am, you know, but it's underwriter at different companies and I then began to work at a new company as a as an ahead office underwriter which is someone who advises the across the across the different regions of the country as to what you know how to define a coverage I also helped to write policy wording or update policy wording that that was back when most insurance policy wordings were written in legal ease and we were changing it to plain language, and that position was in the technical team, which, so beside a small it shop and I worked closely with a business analyst thought, Oh, that looks interesting. So, next job I got was as a business analyst, working for a startup in insurance, and I started off as a BA and then I became a product owner and project manager, we wore lots of hats in the back then. And I discovered sequel and it was like, Oh, now the system makes so much sense to me. I can right click and expand the tables that I can do selects top 10 100 to see what those values are. And I realized that was what was really interesting to me. So, my first real data management job was implementing represent representing the project management business side of the organization in in conjunction with an MDM implementation consulting firm, and it for a large pharmaceutical global pharmaceutical operation and the first data management, the first subject matter for their master data management contacts, which is people so, you know, didn't define party we just went right into the context and it, it really helped uncover for me or open my eyes to all the, all the potential issues, because, especially when you have sales reps who are commissioned driven their compensation information is often how many sales I make so you can't display their sales rep. And it was it to the point that they enforced you can't, you can't see another sales reps contacts, or customers, which makes sense, except when you have two sales reps in the same geographical region, but selling different product types. So, there were so many duplicates, because of course the first thing that they would do is search to see if that doctors office already existed, and they wouldn't see it because it existed for someone else. So, yes, it was interesting. And, and that that was fun. And then I just continued in different data roles in insurance and in health care, and I eventually became global director of business intelligence for a global global insurance broker and it was interesting because we did operational financial reporting from our data warehouse. So, that was a lot. It was very interesting at the last week or two of the month in the first week of the month because that's when everyone wanted to look at their reports. And of course, when you're trying to load transactions that during, you know, for two weeks in a month hardly anyone looks at and then for the first and the last week everyone, everyone's loading transactions and everyone's trying to look at it so then we made the decision to move back to Canada until I ended up in Ottawa. And, you know, as a almost bilingual person I was the opportunity to be able to regain my French speaking and writing so that's been fun. Nice. Yeah. So here and so here I am and continuing to do it and luckily lucky enough to be able to work from home with them and do it. I'm doing this. That's fascinating. It's, it's a very interesting path indeed. And so, as you've grown into this you know we've talked to you see the importance of. So, well actually let me back up a bit. What is your definition of data then and how. How do you work with it if you've talked about it a little bit but how do you work with it in your current job you talked about the data that you analyze but what else do you do with it. So, it, I mean there's so many different definitions of data from you know the, the, the numbers and letters that are entered into a system but to me, it's data is a raw material. It comes from an organization information, and you know the system source from your, your systems and processes, and it becomes information and knowledge when it's put in the proper context. So I think that my favorite part of the job is data in context and it promoting a common understanding. For instance, why once worked for a multi hospital chain, and what define a patient. And is it a patient, you know, people, it was a specialty hospital so people would come to be diagnosed. So, someone decided that you don't call a person a patient until they've had their first treatment. Well, some treatments can also be considered diagnostic procedures. So, when is it a diagnostic procedure and when is it an actual treatment. That was a bone of contention and some of the business, the people whose compensation relied on revenue would say. Well, a new patient is any of these procedures. Well, okay, so you're going to artificially inflate your, you know, your number of new patients in the first year using this because it was an organization that decided to implement a new process. By implementing a new system. And so fine for the first year you'd look great but in the second year it would drop because you're not, you're not always converting those. Not people who come for a second opinion and that's the only reason they come versus the people who come for for a clear diagnosis maybe it is second opinion and decide hey this is where I want to have my treatment. So, that, that was interesting. And, you know, what is a hospital bed. What is an inpatient. Well, an inpatient is someone who's in a bed. Well, if they're being treated in the emergency room. Is that a bed or not. Sorry, I got off track for a moment there but no I love it I mean you said that you know data in context is your favorite thing and that's a really good examples you know sounds so easy to say to you know what is a patient and and you know it seems like it's such a simple thing but it's not it's it's very it's very complicated. Especially in the data verticity webinars when people say oh you know customer is something that you know as a subject area of master data, and the people who have beaten data management for a while kind of chuckle to themselves saying. Yeah it's an obvious place to start but it's not an easy place to start because you know define a customer. Well, who a marketing person a customer is a person who has a potential to buy something from when you want to attract to your web website, perhaps or to your store. Well to to into a brick and mortar store or to the. You know the accounts payable people it's someone who's actually made a purchase is a customer everyone else is a potential customer or or just a contact. And actually at that hospital, some of the inside sales reps because they were, you know, if they answered a call from a potential patient, then they, they, that person would always be rooted back to them so they would get that person did become a patient that kind of took you know that was a positive aspect of their compensation, and they want it, but it takes time to enter information into the system when you're talking to someone. I just wanted to be able to save a contact with just the first name. Yeah, I'm, you know, not, you know, there aren't as many Shannon's and gales in the world says there are johns and Peters, Mary's and Karen's that it's just not feasible. 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 DB talks for 20% off your purchase. And is that how you work with data currently in your current role is putting it into context for people and is that primarily what what you do. Yeah, one of the one of the first things I did was for myself I created a glossary, because there was a glossary of terms for, you know, specific to, you know, what's a screening officer, what's a passenger, those are pretty straightforward. But there were all there was a lot of specialty things but I just wanted to make sure that we're, even though we're using the same word, is it. Do we do we mean the same thing, like customers a great example where we're using the same word but there are three different definitions depending on the area of the business so you know you, how many. How many vendors advertise that they can give you a 360 degree view of your customer. That's great. If you know who that cost, what that everyone agrees that customer means the same thing. So, that's one of my the biggest things that I try and, and emphasize the people is define your process define your terms before you try and implement a tool. And I remember listening to Claudia Imhoff, when one time and she was talking about the, the first class, airline experience, where the CEO talks to another CEO and learns about this great tool but they've just implemented this increased revenue and decrease costs and they come to it and say okay we want to implement this. What for why, and they don't know they just heard that it's a good thing. So, you know just like data driven approach a couple of years ago everybody wanted the data driven approach but no one was really sure what that makes. And we're talking about data literacy, people don't understand the data but you don't want to say oh your data illiterate because that sounds insulting. And everyone knows data is important but it, it's working with them to understand why it's important. We're working with the people who are actually entering the data to show them the downstream effect of their data. One place I worked the place of birth was a was a field, you know, we had an out of the box, the billing system for for patients and unfortunately there were people who were homeless, and they use the place of birth field to indicate that someone was homeless, but no one never ever told data, or the, or the business areas that consumed that data so they look and they see, oh look there's a place of birth that would be great for clinical research because if you have many people with the same say a same type of cancer, all born in the same place. That's, that's a critical data element for research, but not if it's used for something totally different. Right. Yeah. And the same was as out of the box systems that give you user defined fields but you can't change the name of the field from, you know, in the database from udf one through 100. So then you have to, that's why you then you need to map out what is that used for in one place. I worked. It was the, the heavily customized the out of the box solution and when someone say oh we want to be able to track this okay well we'll just add it. So we've got a clear udf over here, we'll add it. And then someone would ask for something simp someone similar but and that's another thing that I try and do is, let's not build a report or a dashboard. Before first checking if there's already something we have that works because unfortunately, ever since I've been in data we've had that problem with with silos of data and people come to the report developers wherever they sit in the organization Well, we want this and so then the report is built and because it's the easiest way to do security okay everyone belongs to this business unit or this business area can view view the report of the dashboard but no one else can. We have someone who wants exact a very similar report, and they don't know that something already exists that might just need a few tweaks to work for them or could already work for them so that's something that I also try to do is one place that I work we were converting or migrating from one reporting platform to another, and we were able to reduce. I think we started off with like 420 reports, and we had it down to 130 or or so, because there are so many duplicates so many things that you that were just Oh, I like this report but can you add a column so instead of adding a column to the existing report a new report was created. And then again, if you don't have a good catalog of what your data solutions are your you could be creating the same thing over and over again. So that some so I guess I'm more on the business side trying to to teach them how to work with their data and what what to look for and how to how to increase the quality of their data. I love it that is that is. It's that's hard work and 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. Gail. Do you see the importance of data management and the number of jobs, working with data increasing or decreasing over the next 10 years or so and why I think I think it's going to increase because everyone's caught the data bug so to speak. And, but we can't take advantage of that data without, without people who can help the business fine tune their data, you know, data quality is the very first thing that you need to do. It sounds boring. You, but you, and you also need, we need everyone needs, you need to have a business glossary, you need to have a data dictionary that ties to the business. You need to have good, good data models I know a lot of people, especially in an agile world think, well, data, data architecture is just a waste of time it takes too long. Well, no, if you don't have a map, then how are you going to get to where you want to be and to me, a good, an enterprise data model is a map of the existing business. As you, as you bring in new data sources, bring in new data solutions you, you have to keep your, like as a business sense you always want to keep your requirements updated. As someone who's working data you always want to have your data model current, and you need that common understanding across the organization. And it's, you know, and there's always new technology coming out, and in order to take advantage of it you need people who can understand that, that technology, you know, many people are realizing that they don't many organizations realizing you don't need to keep everything on premises and you know vendors are kind of pushing that by saying, you want the, the best that we have to offer, well, it's available in the cloud. You know, so that you have to be prepared to use the cloud in there sometimes when you've got, you have to have a hybrid model because there's just some data that you that maybe for regulatory reasons you can't have in the cloud. Makes sense. So what advice then would you give to people looking to get into a career in data management. I think the first thing is don't be afraid to ask questions. So, you can learn a lot. There is, and there's so much tacit knowledge undocumented knowledge. I remember on, and one of the recent webinars someone was talking in the, in the chat about interviewing someone was about to retire from the agency after 30 years or more. And he's building kind of like an encyclopedia of knowledge based on that person's historical knowledge and all that tacit knowledge all the knowledge that's up in your head you need, you need to learn from that. Technical skills are important. You need to be able to work well with whatever the technology is that's available but a lot of it you can learn it easily to, but just make sure you keep those technical skills skills. When you start working at an organization find the glossary if there isn't one just start one in an Excel spreadsheet for yourself. You can maybe even put it in a SharePoint list until the organization's ready to invest in a tool like a data dictionary and data lineages so important as well. So understand the organization's processes and don't ask for okay well, don't ask for the manual and how the users guide for system, because that's what everyone expects people to do, but just like that example of the, the date of birth that was common understanding of a small team of people, or sorry place of birth being used for a totally different reason, you need to see, you know, if you can, as a, I remember sitting beside someone. When I first started out as an organization just asking well can you just show me what you do and as a business analyst trying to, to help define the requirements for a new application, and people are so thinking in, well this is the way I've always done it. But that's just because the system requires you to do these steps. What is, so I, you know, I would say imagine you've got a physical piece of paper that you, what do you have to do to the information on that piece of paper to be able to move it to the next step. And don't think about about how you currently do that think about what needs to be done and then then we can figure out how best to a tool can can facilitate that process. Often we, we migrate to a new platform but we migrate our garbage or redundant report, our rot data as Peter Aiken likes to call it, redundant obsolete and trivial that's, that's important. And keep learning but you need business knowledge as well. You can, you can't get a deep down business knowledge but you need enough business knowledge. And so, not only, don't be afraid to ask questions but know who to ask or where to go to find the answers. Because that's one of the things I've always said to people is, I may not know the answer, but I will find, I will find the answer and it's the more you do it the more you know where, where to look for those right answers for that information. And don't forget your business subject matter experts, don't forget what people sometimes refer to as the shadow it the the departments who built their own data analytics solutions. You know what are they doing, let's learn from them, but maybe we can leverage what's already there maybe we can teach them how to leverage what they've already built and and help make it better. So, I think, yeah, I think that's about it. And also, yeah, go ahead. I think Dama joined the data, the data governance professionals organization attended diversity webinars, you don't look at the professional training available, go to the con go to conferences. That's one of the things that I learned. Yes, there's a lot of great speakers and presentations where you learn a lot but you also learn so much just having a cup of tea or coffee with someone. With a colleague, or, you know, having a drink after in the evening. And you, you data people like to talk about data problems and data solutions. And that being very helpful as well and I think that's one of the reasons that I really enjoy the diversity webinar webinars is because I'm with my people. I'm with people who understand the value of data and are are fighting to bring that that they're understanding to the organizations they work with. That's awesome. So I think, you know, in summary there, I mean it's so important is, you know, really have an open mind, be curious and be open to learning and don't assume anything. Oh, that is the best, best thing don't assume and don't presume either. Yeah, and especially, you know I know that when you're starting off you're full of confidence in your technical abilities. You know, listen, as it's amazing. I read Peter Covey seven habits of highly effective people so many years ago, and so many things he says come come back to me as you first seek to understand. But don't try. And I know we're I'm guilty of this to where you want to jump in and help, but you can't help if you don't understand the problem. So first seek to understand the problem from the point of view of the different business areas. And you know and that's why you need a map of data modeling you can't get to where you're going if you don't know where you are right now. That's true and so important and Gil. Thank you so much this has been really a great conversation and really interesting and what you're doing. I love these conversations to find out more about about you and what you're and all the things, the great things that you're doing. Thanks to all of our listeners out there. If you like to keep up to date on latest podcasts and the latest in data management education, you may go to dataverse.net forward slash subscribe. Until next time, Gail. Thank you so much. Thanks Shannon. This has been so much fun. I love talking data. Thank you for listening to Dataverse City Talks brought to you by Dataverse City. Subscribe to our newsletter for podcast updates and information about our free educational articles, blogs and webinars at dataversecity.net forward slash subscribe.