Data Science Hangout | Aliyah Wakil, Texas DSHS | Increasing Data Literacy & Moving to Leadership

Transcript#

This transcript was generated automatically and may contain errors.

Welcome, everyone, to the Data Science Hangout. If this is your first time joining, this is an open space for the whole data science community to connect and chat about data science leadership, what's going on in the world of data science, and really just questions you're all facing as well. So we really want to create a space where everybody can participate and we can hear from everyone. So there are multiple ways that you can jump in the conversation and ask questions. You could jump in live, you can put questions in the chat. And then we also have a Slido link where you could ask anonymous questions too. So the session will be recorded and shared up to YouTube. So you can always use the anonymous way of asking questions if you prefer to not be part of that.

Also, if you want to ask a question in the chat, and maybe you're in a crowded, loud room, and you want me to read that out, you can just put a little star at the end of it as well. And I'll know to read that for you. But thank you all so much for joining. I'm so excited to be joined by my co host for today, who you may have seen as an attendee on a few of the past sessions, Aliyah Wakil. Aliyah is a epidemiology team lead at the Texas Department of State Health Services. And Aliyah, I'd love to just kind of turn it over to you first to just introduce yourself and share a bit about some of the work that you do on your team, if that's okay.

Yeah, sure. So thank you so much, Rachel. So like Rachel said, I am an epidemiologist. The majority of my experience has been in government. So I've worked at the federal level. I had an opportunity to work with the Centers for Disease Control and Prevention. And I have also worked at the state level. And I'm actually excited because I'm currently transitioning into a new role from an epidemiologist, epidemiology team lead with the Texas Department of State Health Services to an analytics manager position, which is really exciting.

So right now, the position that I'm in is that we are developing a center of public health informatics. And as an analytics manager, I have the opportunity to work with our stakeholders that are in the community, but also within the agency, and to really develop our skills and our knowledge around how do we leverage working with data and public health to really combat a lot of public health issues within the state. And then also building a community that really is comfortable with working with data. So that includes managing, analyzing, and most importantly, communicating data. So right now, my team is tasked with building out not only our analytic abilities, but also developing the workforce that we collaborate really closely. So I think that's really been exciting for me, just trying to figure out strategies to get people who maybe they aren't really, they don't really have those hard technical skills and working with data, but they do use data for like their strategic planning, to make decisions. So really just empowering them to leverage data in their everyday work.

Strategies for data literacy

That's awesome. And I know one of the things you said that you're most passionate about is being able to bring data science to everybody. And I'm just curious, what are some of the strategies that you're taking to do that? Yeah, so most recently, I really got on board with data literacy. So if everyone isn't familiar with data literacy, it's the ability to read, work with, analyze, communicate, and argue with data. So it is, I would say it's like a trending topic right now. And data literacy, in my mind, is really just meant for everyone. It's not just meant for the epidemiologists like myself, who have a strong research background, or data analysts, but it's also meant for business leaders and even nurses, consultants, medical doctors.

Again, I work in public health, so a lot of my references might be health-related. But that it is for everyone, that everyone can utilize these skills and benefit from just knowing some foundations around how do I interpret results that are presented in some literature, or even presented in news articles. And I would say that right now, a couple of the strategies that we are implementing, first is just getting an understanding of where other teams are in their abilities and in their knowledge. So we are data folks, so we're surveying, we're putting out assessments, giving people the opportunity to let us know what kind of programs that they have experience with, what is their level of comfort working in some of these programs, which includes SAS, Excel, Tableau, R, RStudio . And then also, are they open to learning other programs?

So we are also, with the Center of Public Health Informatics, we're expanding to really centralize all of the data that we use and all the technologies that we use, and moving forward to become a bit more data science-centered. So we're really trying to make a push from those that have traditionally worked in SAS to start using R and RStudio. Those that traditionally, you know, work in Excel and have those foundations, and maybe, you know, they are able to create charts in Excel to start moving towards using Tableau. So things like that. So as far as just getting a lay of the land, doing assessments and surveys, we'll also be creating some metrics for us to be able to monitor and track over time to see how, you know, from baseline to whenever we want to survey it again to actually see if people are kind of making some progress towards understanding these technologies.

And we also are, we are creating communities around sharing knowledge. So we will be developing webinars that we'll host maybe monthly, quarterly, where people can come join. We'll have speakers that are possibly talking about what they're doing in R or some visualizations that they're doing in Tableau. And then also holding office hours with some of our experts on our team. We do have like Tableau coordinators. So just making sure that they're available for people that are interested and if they are working on a project that they can receive some guidance and some consultation on a project that they're working with. And then also, we were able to procure agency-wide licenses for DataCamp. So DataCamp is a platform like Coursera, but we do have the enterprise access. So we have access to all the courses that include, you know, how to develop dashboards, courses on machine learning and predictive analytics, and also some courses around theories and just building that knowledge of how to work with data.

So yeah, so those are like a couple of things that that we're working on now. Nice. And so I know you said you're just launching some of those webinars too. How are you going about like sharing it with everybody and launching the program? So that is a really good question. I will say that I'm happy that we're in a position to where we plan on it being iterative. So really just, you know, let's see what works. If it doesn't work, let's revisit and try something else. So right now, we have identified a team of, I believe that they are a disease prevention team, and they're actually interested in learning a bit more about Tableau and how to do some dashboard building.

So we do have a Tableau coordinator who will start, he'll actually develop a webinar based off of some of the skills that they already have, so he can get an idea of where they are, and he'll create a webinar for them. And I would say that it'll be like a pilot just to see how it goes with them, and if it goes well, then this is something that will hopefully expand to other teams. And the ways that we'll communicate will of course be through email, but we also have weekly meetings that we are able to communicate with teams that are, it's like an all-hands-on-deck meeting weekly, so we're able to communicate with other people that aren't on our teams. So this would just be another way for us to put it out there, let them know what we're doing, how they can join us, and just letting them know our vision and how we do plan on really supporting them in this expansion of trying to build up our data knowledge and our skills.

That's great. I see there's a lot of questions coming through in the chat, so I'd love to bring a few other people into the conversation too. Sep, I see you just asked something around the the workshops too. Yeah, hi Aliyah, my name's Sep. Thanks for taking the time to share your story with us. My curiosity was around like these workshops and whether they're going to be mandatory, or is there like a broader program to kind of onboard people if you don't mind talking about that would be great. Yeah, I think that's a great question. And as far as it being mandatory, since we are in public health and COVID is really a huge, it's still a huge thing, that we are really sensitive on knowing that a lot of our workforce is still focused on COVID. So a lot of their time and capacity is really going towards monitoring COVID and just getting it under wraps within the state.

So I think we're sensitive on not wanting to make it something mandatory, but the more that we, you know, get this this pandemic behind us, then I think that there will be some workshops that will be mandatory for some teams, but just really just voluntary. And if you do have the time to come and join us, if you have the capacity, but just be insensitive that we are still in a pandemic and a lot of our workforce are working towards those efforts. That's great. And hopefully if you get only a few people, then they can help evangelize and move on from there. Exactly. That's, yeah, that's a great hope.

Frank, I see you asked a question earlier as well, if you want to jump in. I appreciate it, Rachel. Aliyah, thanks. Thanks, like I said, for your time and sharing your experience, it seems like your initial few minutes just got a lot of activity and got people's minds thinking. Where my mind went was as you start to build out these skills and these ways of thinking around the company, there's going to end up being pockets of information, and then you'll ultimately have conflicts and you'll have teams and team members saying, well, people aren't aligned and we have people working on the same stuff. And I think in a giant company, that is inevitable. I've handled that one way in my own experience, but I'm curious, right, is that something that you think about and worries you? Or are you like, no, that's way too far down the road?

Yeah, so with the development of our new center, it actually was to resolve a lot of those problems that we were seeing within the agency. Because we have a public health organization, it's very interesting. We're all epidemiologists, but everyone has their different topic of focus. Everyone has their different expertise. So because of that, there are different offices and teams. And what we were seeing was that there was very much a, just like an array of, like an array and a duplication of things that were already being done. So this center was actually one of those things that was brought up in order to help us centralize across the agency. And thinking about how can we, one, communicate more between each other, and how can our center be that liaison? So we do have an understanding of what every team is working on, and also so that they can rely on us to be kind of this centralized resource for them.

So I think for us, because we are a new center, that a lot of it is just going to be like learning the landscape, and then also sharing back out so others know what other teams are doing. So I think right now it's just going to be a lot of communication and a lot of standing up of these technologies and getting everyone on board. So I think this is where the heaviest lift is going to be, but I'm excited to even just, you know, start to communicate and sharing that knowledge. But I think it's mostly going to be how do we just communicate more and collaborate more so we know what everyone is doing. Is that mostly email and Slack?

So right now it's, I mean, right? So right now it is mostly email and then also leveraging these weekly meetings that we hold. And these weekly meetings include our health commissioner. So he's our health commissioner for the state. It also includes our central office. And then we have another level, which is considered the district level. So those are each local health district. So everyone has a representative that is on this call, and everyone has the opportunity to share what they're doing. They have the floor to discuss anything that they need. So just thinking of an example, someone showcased an analysis that they did regarding COVID cases in schools. And then just sharing that knowledge and giving everyone the floor. So I would say right now it's email and it is these like weekly meetings that we've been having.

Dealing with patient data across multiple data systems

Sure. Can you hear me okay? Yes, I can. Yeah. So I work for a large local public health department. And one of the things that I think would really help us in terms of the pandemic response would be tracking patients kind of across all of our different data systems. So looking at our disease reporting database and linking that with the immunization registry to see if cases have been vaccinated or not, and then linking that with syndromic data to see who's been hospitalized so we can look at breakthrough case rates. But in envisioning, you know, there's the technical challenges of linking these systems, but then there's kind of the ethical challenges. And these data systems have different data use agreements. They contain more information than you would expect about a given person. And so when you start linking them, people who weren't originally intended to see the data now have access. And so we're having kind of a lot of back and forth about how do we do this responsibly? Can we even do it? And I'm just kind of curious to hear how those conversations are operating at other health departments.

Yeah. So I can speak on specifically in Texas. So that was a huge barrier for us where, like you said, Kelly, that because of data use agreements that, you know, we couldn't access, you know, we couldn't access a certain agency or office's data, but we were able to access other, like other offices' data. And to be honest, I kind of feel like that it should be at a higher level. I don't know who needs to mandate this, that there should be easier data sharing. But I've definitely been in that same position where we were interested in doing specific analyses, but because of, you know, the people that we were working with that we just could not access that data. So it does make our job, like, really difficult. When you know that the data is here, you know that it's not accessible, but you know that it's there, you know that it exists, but, you know, we can't get the agreements in. So sometimes we have to go to legal, we have to go to lawyers to really build a case on, you know, how are we going to use this? Why do we need it? So I've definitely been in that same position, Kelly, but I don't know what the solution is.

I kind of feel like that it should be at a higher level. I don't know who needs to mandate this, that there should be easier data sharing.

Thanks, that's really helpful. At least we know we're all in it together. Yeah, absolutely. And then I will say in my current position, because we work with aggregate data, so we're not looking at individual patient level data. So once it gets to us, it's all at the state level.

Increasing data literacy and getting buy-in

Thinking more about, like, getting other, like, teams involved and, like, pushing this up to leadership, too. I see Zach, you asked a great question earlier, as well, and mentioned, like, you've done a great job, it seems, at getting resources for training people, as well. Zach, would you want to jump in and add any context to your question? Yeah, so I, at the moment, so I've learned, so I'll just talk a bit about my background. I've learned this all in my spare time. And at the moment, we're trying to get other people to learn this stuff. And of course, therefore, they've got these, like, data camp course, and etc, are really good. But it's then about the person I was talking to, that's head of developing career development, I can't remember what their official title is, but that sort of thing, developing skills, just generally. And then it's just about how that person then going up and until you get the right senior stakeholder, I was wondering how you achieve that, because you seem to have got a lot of backing, not only with the data camp, but also the workshops. And yeah, seems you've done really well at that. I was wondering how you achieve that and what sort of steps us or we could generally follow, see if it works for us.

So I would actually have to give kudos to my director, who had put in the work, before I started this position. And he's been with the agency for a lot of years and a lot of different positions. And he's been in a lot of leadership positions. So I feel like that it could have a lot to do with him just having built those partnerships, people know him in the agency, they listen to him, they trust his vision, and they trust his judgment. So I'm fortunate enough that he also trusts me and with thinking about what kind of strategies that I'm interested in implementing. And he'll be supportive of that. But I will definitely say that he has done all of the legwork as far as procuring these contracts with data camp, with RStudio, with Google Cloud, he is really envisioning getting this, this center to a more data science centric center. And I would say it's all because of him. So I'm really just grateful and appreciative that I can actually lean on him for for some guidance.

Hugh, I do see you asked earlier about transitioning from SAS to R. And I know this is something that you're doing at your organization, too. I believe you if you want to jump in and ask that question. Yeah, absolutely. Hey, my name is Hugh. I'm a management analyst with the federal government. And I was kind of curious if you had any advice. Let me first say I really like your strategy of like multiple avenues for increasing data literacy. That's something that we've struggled with as well. But I want to know if you had any advice. You mentioned converting, trying to get people to learn R if they were comfortable with SAS. And that's an area where we've struggled with. And to be honest, I haven't really made a lot of headway. I was wondering if you had any advice or strategies for success there.

Yep. So I think I think that we will be in the same boat because I think when it comes to, you know, SAS users, they just get kind of comfortable in the language that they know. But one of the things that we do plan on doing is, one, since we did do that assessment, we do know that there is an opening, an openness to learning R. So that's good. So that's a good first step. And then also just providing those resources for them to do it. So we are fortunate that we do have these data camp licenses. So it's available for them, however they want to learn it self-paced. But then also, I think what we will do is probably just showcase the abilities, the capabilities that R can do. And then from there, just kind of showing them how easy it is to do knowledge sharing and to work across teams. So I think for us, it's going to just be providing examples to them and how we hope that it can make their jobs better. I think once they can see that benefit, that they'll be a bit more on board.

And then I think the more that we push R, because even for us, as far as like supporting guidance, we won't support guidance with SAS. So it's like, if you're coming to us for help, we'll provide support using R, Tableau, and we're trying to move away from Power BI. So we're not going to be providing that guidance in that way. So I don't know. We'll see how that goes. But yeah, I hope that helps. That does. Thank you. It's nice to hear that similar struggles. I figured we'd show them the pipe operator and they'd stampede to R, but that kind of hasn't been the case.

Millie, I'd love to have you ask your question too, if I can pass the mic over to you. Yeah. Hello. Yeah. I was curious what success looks like for your, I guess, mission of data literacy at the agency, because it sounds like teams have their set ways of working that seems to work fine for them and what they've always been doing. And I'm wondering what you envision, like saying, like, OK, we've met the mission of having people be data illiterate and data science forward and what that looks like to you. Yeah, I think that's a good question. I think for me, what that looks like besides us doing our assessments is even in, I would say, like conversation and how well versed when we speak with each other, are we incorporating data into the decisions that we're making? So if we're on a planning meeting, for me, what that would sound like is that we are just providing evidence of why we want to do something based off of such and such analysis, like this is what we saw. So we think that this is a good idea. So I think when I just hear data being incorporated more in conversations, especially around making decisions and strategic planning, that that's when I believe that we've got to a good point.

Moving into leadership

Aaliyah, a question that I'd love to just talk a little bit about is I know you mentioned you're moving into this new role. So congratulations. But also for people on the call who are starting to take that step towards the new role or wanting to move up into leadership, how did you go about that or what tips would you have for people?

That is a good question. So I would say that my transition to leadership was first just expressing that interest to my management, to my immediate supervisor, of letting her know that, hey, this is where I want to be in the next two years. I'm letting her know that in the next two years, I would like to be in a leadership position. And then based off of that, going back and forth with her about, well, what does a leader look like in her eyes? And what kind of qualities would this person have? And then just kind of creating some responsibilities on myself to get me in that position. And then just taking on the leadership role, still just seeking guidance. I think that it is something that I'm still getting used to. It still takes practice. But then also knowing when to ask questions and then finding maybe like a mentor who I trust, who's also in a leadership position. And I think that they could just give me some great insight to understand where I'm coming from. So I would say just knowing that that was something that I was interested in, like in the next few years, expressing that to my manager, my leadership, and then just creating that roadmap. But I think the first thing is just letting them know what I wanted. So she was well aware.

I would say just knowing that that was something that I was interested in, like in the next few years, expressing that to my manager, my leadership, and then just creating that roadmap. But I think the first thing is just letting them know what I wanted.

Patrick, I see you had asked a question earlier around the amount of time spent working with hands-on with data, as opposed to managing, organizing, leading. Patrick, would you want to introduce yourself or add context to that question? Sure. Thank you, Rachel. And the question you just asked is really sort of the overarching question, right? That's the bigger question. Hi, Aliyah. Thank you very much for your time today. I appreciate this. And it's been helpful already. I'm Patrick Tennant. I'm with the Meadows Institute. And we're a health policy institute in Texas. So we talk to HHS from time to time. And we'll probably cross paths at some time, it sounds like. I'm the director of evaluation and analytics. And right now, I'm sort of making this transition that Rachel was just talking about, where the data is being pried out of my hands, so to speak. And I'm going more towards management and overseeing our transition to a secure cloud environment and stuff like that, where I spend less time in RStudio than I used to and maybe would like to. I'm still sort of determining how happy a transition this is. But so I'm just wondering if you can talk a little bit about that for your current role, your upcoming role, how you've thought about what is the right amount of time for you to sort of be directly in touch with the data versus overseeing others who are.

Yeah. So that's actually a really good question, because I definitely started seeing that I am working less one-on-one with the data. I'm more so providing guidance around analytics. As like a subject matter expert, I'm just providing guidance. I'm making sure that it makes sense for us to do something this way or that way, but then really just letting my team do the hard number crunching, doing the visualization, and then just providing guidance around that. So I would say that a lot of the time that I spend with data now is reviewing and taking a look at something, providing feedback, and then I would say talking a lot. I feel like now more than ever, I'm just talking with somebody. I'm on a meeting, collaborating with stakeholders, gathering requirements, getting an idea of what they're envisioning.

So for me, I definitely plan on taking advantage of the data camp license that I have just to keep me fresh, but it is definitely, yeah, I would say that my interaction with data is reviewing, providing feedback, providing guidance to my team, and I will say that I do also enjoy advising and teaching and providing guidance, so I have enjoyed that aspect, especially when it comes to newer people. Maybe they're just starting their career, so I think it's a really awesome opportunity to just think about how I can help them move along and get them to where they want to be. Yeah, so I think I will say that it is a huge transition, but I am enjoying it because I think looking ahead that I would like to be more in a position where I am providing guidance, where I am teaching. I'm also interested in teaching data literacy and teaching how to build dashboards, so I think I'm in the right place, and I'm definitely going where I want to be, so yeah.

Thank you so much. That was helpful, and I'll second that piece on teaching. It's been really fun, and actually something I found is that I think I'm exploring more broadly now about potential applications and use cases and things because it's not specific to one problem or project. I don't need to solve this. I need to find out what are the things that are available to us, and how can we best utilize them, and then putting those down the chain, so I agree. The teaching piece has been really helpful for me, too, and I'm glad to hear you're enjoying the transition. And I'll second that as well, that a part of this job also is just figuring out what is best for the agency, so that includes technologies. That includes piloting CIVIS analytics, and just how can we utilize this? Is this going to be beneficial for us? Will people actually use it? So it also is a part of that decision making, and yeah, so kudos.

Technical vs. management career paths

Thanks, Patrick. I think this conversation around moving into leadership and maybe sometimes having to step away from writing code yourself is really helpful because I know a lot of people are running into that and maybe not as happy with sometimes how that turns out. But Matthew, I see you asked a great question about this as well. Could I have you ask that one next? Sure, and pardon my delay coming off mute and things like that. Thank you. Yeah, continuing on it, maybe instead of asking my question, I have an analogy, and that's the analogy of think about a used car lot, right? And you've got your salespeople and your management. Do you promote your best salesman to lot manager? Are those comparable skills? Should they know the product? And so I've thought about that often. I'm in the education industry and seeing pathways where you take your good technical people, and in fact, I left an organization because they said, well, we're going to promote you and give you more management experience. And I said, well, but I have a PhD, non-MBA, and I'm not denigrating anything, but, you know, the recognition of there are technical pathways and you want to give some progression and not afford growth for people who are technically oriented. And then there's management and leadership, which is the traditional sense. And how do we think about that? Are those separate paths? Am I making it up? Is there an opportunity? And how do we, you know, how do we support that idea?

I like, and I'm also open to opening the floor to hear other leaders and their take on this, but I definitely agree with it being, you know, two paths because someone that, you know, is highly skilled and, you know, they produce great analytics doesn't mean that they'll make a great manager. But I also think that there's a difference between, you know, managing people and managing projects. So I think that's a really good question. And it's something for me to think about. Yeah. I think that's a great question as well. And I'd love to open it up to everyone as well, because, I mean, I've thought about this myself too. Like, what if you don't want to manage people? How do you move forward?

And if you're leading those technical people, like, how do you say, okay, there's no path, like, how do you avoid saying there's no path forward for you because you don't want to manage people? I'll be honest, right? I am actually in a leadership position. And so this is something I think about just about every day. I've got great technical people and I've got great, you know, leaders that I work with, but, you know, acknowledging people's strengths when businesses, especially outside of say software development, you know, do a better job of rewarding people management versus technical leadership. Maybe what, is there something we can borrow for anybody that's in software development on that side? You know, I've seen like tech leads in software development. Is there an analogy here where we reward that kind of expertise and you're managing the technical thought leadership and how can we borrow that, beg, borrow and steal that?

Yeah. I see a few people have unmuted. So I think they maybe want to add some thoughts here too. So Brian, do you want to jump in? Yeah. So we actually, we actually did that when I was at Hanover Insurance. So we had junior associate data scientist and he had all the way up to lead data scientist. The more senior you got, the more people you managed, but you also did project. But then we created a fork and the fork became like principal data scientist and a few other levels up that were beginning to parallel the management side, which would have been like AVP and various positions like that. The responsibilities were very different though. And so for your technical people, it was, you had to do white papers and a lot of other research technical oriented stuff to get down that pathway. And it does open the door to it, but, and it's available. So you can separate that.

It's fairly common in the insurance industry with actuaries just because you're a great actuary doesn't make you a great leader. And so in order to prevent the churn in that, you have to create positions where people can do and use their technical skills and still kind of progress along the way. And so that was our way around in the data science world. We created all the pathways and we were young enough team. So no one really got to the point of approaching that first technical role, but it was open. I mean, we had it in the, we got to bless with the businesses and HR and everybody else. So it was there and that's your way around it, but you're going to have to work with leadership and HR to establish those pathways.

And Brian, in that example, that like more technical person, did they go off to, I guess, being like, like the lead of a project and they just weren't, you know, managing, like they didn't have people under them, but they were considered like leads and like SMEs. Yeah. So there's a couple of things. So, so you generally, you will probably manage multiple projects on your own and, or you may, or you may be on a team with it. But you, but the kind of like the research where you're going to have to publish something. And that was, that was requirements, you know, whether it, or, you know, speak at conferences or something like that, you have to fulfill this technical role. And so that's what we put it as is, you know, whether it was speaking at conferences or doing white papers or other stuff that projected you and the company. And, and that was, that was, and so the nice thing about that, it's a pretty easy, it's a pretty transparent requirement. You know, cause we know whether you've spoken at a conference or you've been invited to speak or you've applied and all these other things. So from that standpoint, it's not very subjective goal. And so I think it clearly, you know, fits with those type of positions. There's no, you know, did you achieve happiness? And also the kind of thing is, did you actually apply for these speaking positions? Did you do it? Did you publish papers? And, you know, some of it was actually teaching the team too. And again, very measurable, how many sessions, cause we, we held a session every month for the whole team and, you know, multiple people presented. So it's all along that line of projecting and communicating your knowledge and skills to other people.

Ryan, if I could piggyback off of some of what you're saying, I'll just do a quick introduction myself. I haven't been here in a while. I, so I work in, technically I sit within HR. I am in a workplace behavioral scientist role at GE healthcare. And so I spent a lot of time working on helping people with developing career pipelines, a lot of the analytics that we use to help do that stuff. And I think, I actually think that response you gave is great. There's a lot of fantastic suggestions in there. I think the other reflection question you need to consider is sort of where some of those value-add behaviors are useful, depending on the maturity of your organization. Because I've also heard the perspective from someone where some of those things are not available or they're not justifying that person's salary. I've seen some fantastically leaders who've done a great job of saying, look, this is that this organization's current standpoint in time, having that blunt conversation of these are some of the limits I currently see for you as an employee here at this organization. And a lot of great leaders I've seen do a good job of recognizing that some people can only go so far in certain organizations and we'll try to help that person move on somewhere else. And sort of by going back to what you were saying, move on somewhere else and sort of by creating a great reputation as a manager, it helps them backfill that role eventually, because that person might have a recommendation. In fact, my role was a backfill from someone else who met and knew that my manager that I have now is a great manager. So there are those people end up being in service to you as long as you're in service to their career development as well. So I think, I think both of those things have to be considered in tandem.

Thanks. Hi, I haven't been here in a while either. So welcome back, everybody. Thank you for coming back. It got busy there for a while and sort of dropped off, but I'm happy to be here. So I work now in a finance group. I used to be on the engineering side as a data scientist. And I work at Apple. And the way things are done here is that two separate tracks. It's very much an line with what Brian sort of said as well. We have this individual contributor track and then a managerial track and they both have progressions and they're completely separate. Right. So I've been in a more traditional manufacturing company for, you know, in my previous career. And that was the more traditional, you know, you become the IC, then the natural progression is you become manager of a small team and so on and so forth. And that's surprising when I came here is this completely different. So if I have to grow, I'm offered like right now I'm an individual contributor and I can keep going. So I work with ICs who have been here for 15 years at Apple, right, or 20 years. And they're just ICs. And the expectation as you keep growing is you work on more complex stuff and you bring innovation to the company and you're able to influence. Influencing other teams, right, who are not part of your control is a big part of it. Can you make big decisions and can you do big innovation at Apple by influencing a whole bunch of other teams, using your technical expertise, using your personal connections. Right. And that's your role as you grow in that individual contributor ladder.

And if you want to become a manager, then you can. And then the role is really to enable your ICs. So the managers are expected to make sure they're working on the right projects, that we have the right resources, doing project management and resource allocation, making sure people are happy and all of the managerial piece. And they have to, their primary purpose is, are my ICs happy? Do they have what they need to get the job done and then get out of the way? Right. And let the ICs do the work. So the way we have these discussions every year is my manager, for example, he's asking me all the time, he's like, okay, what do you want to do next? And it's, you know, you can sort of choose either path, but the paths are completely different. Right. You can be, you know, and I feel the way they even motivate you to even stay at ICs, they have that path for IC and give enough compensation, right. You know, a lot of times folks end up moving to managerial because there's not enough compensation on the IC path. Right. And it's like, yeah, I love what I'm doing, but as that happened to me at the previous companies, like I was forced to become a manager because I hit that glass ceiling is that I could be here another 15 years and I'm not going to earn any more. And all of that kind of thing, it becomes real, right. I want to do what I'm doing, but I also have to earn more money. At least Apple, they've taken that away. They're like, you can stay at IC and we'll keep paying you more. As long as you do bigger things, you don't have to manage people. And I like it. So I feel there's less pressure for me to like move to management just because I've been here 10 years or something like that. Right. That's sort of a bad motivator for me.

Handling the "technical box" and imposter syndrome

Yeah. That's really helpful perspective, Rahul. And thank you all for jumping in on this conversation too. To kind of change the track a little bit, I see Rachel Peters, you asked a great question. And I'll read it aloud because I know you have some crazy dogs running around, you said. But Rachel asks, I'd like to hear how people or question to Aaliyah, I'd like to hear how people handle the tendency for business partners to put you in the technical box, like make me this versus being involved in the ideas process, et cetera. That's a good question. Wait. So the question is, can you repeat it, Rachel? I'm sorry. Yeah. Yeah, definitely. So Rachel asked, I'd like to hear how people handle the tendency for business partners to put you in the technical box of, hey, make me this versus being involved in the ideas or the process.

Yeah. So I think with us, it again kind of goes back to like the communication and actually working with leaders, so like across the agency, so that they can actually understand what we are capable of doing, why we're here. And then again, because the center is new, we were built up for a specific purpose. And that one of those main purposes was to like centralize our agency. So everyone can get on the same page. So we're not duplicating efforts. We're not duplicating work. So I think that it definitely, I think that it really takes place at the leadership positions to where our leaders are communicating with one another. They are building up that rapport. And then also that it's really kind of this, I don't want to say compromise, but it is this understanding that we should be collaborating. I mean, I will say that in public health, that it is supposed to be super collaborative in order to actually make a difference and to get things done. So I think that there's actually an initiative that the CDC just put out and it's called like public health 3.0, but it actually does focus on collaboration. So there is this huge effort that we do collaborate more. So I think that we kind of are on the same page and we do value that, but it kind of, I believe that it will start at leadership to create those relationships. So then it can like trickle down to the rest of us and they're leading by example that we are collaborating and that's what we should be doing.

Thank you. Can I jump in and make a comment on that? Sure. Go ahead, Ron. Okay. So I'm Ron Sokoloff. I'm the chief of informatics here in veterans administration centered out in Nashville. We run into almost an identical situation where it's your building. I need more granular detail is the common order. It's like, here's an Excel spreadsheet. I need granular detail. And I've learned not to just roll my eyes, but rather what I finally did was we don't start a project without a clearly defined scope of work. Where we sit down with the person who made the very vague request and we forced, we don't like force them, force them, but we talk them through not just what, what is their goal? Okay. That's your goal. And we slowly work backwards to your data points and how do you want to look at it? And by really involving them in the process, we've really had great success in getting them to understand what we do and by incorporating the data analytics into that discussion and showing them what their various options are. It's gone a long way to get us involved in these sorts of discussions earlier on, perhaps not at the beginning, but much earlier on in a much better, more refined request for a product.

Thank you. Yeah, thanks so much, Ronald. Javier, I see you have your hand raised as well, if you want to jump in and ask your question. Yeah, thanks. Actually, it's just to piggyback off of what Ron said. Yeah. So just to piggyback off of Ron's comments and actually sort of, you know, I had worked with a lot of actuaries over my career and so I've seen this sort of dynamic where if we're building out shiny apps or dashboards for a less technical audience that will also be used by a technical group, that there's like less trust in the app as a whole if the technical users don't have the ability to extract the data or see how it is you calculated all these metrics. So what we started doing for all of our shiny apps was to have, you know, like a download Excel button pretty much, right? Like an action button, you download the file, if you use the OpenXLSX package or there's a few of these. I prefer OpenXLSX, but you can create like very pre-styled dashboards, or I'm sorry, Excel files as downloads. And that, you know, that seemed to sort of give our very technical, you know, counterparts or business partners more confidence in like the analytics we were showing or the metrics or KPIs that we were showing because a lot of the KPIs we're showing on these dashboards don't exist in any one data warehouse. We're calculating on the fly in the server of the shiny app. So it's a way to be able to sort of, you know, bridge the gap from the detail to the higher level data points that you're communicating.

It's really useful. Thank you, Javier. I think that's come up quite a bit too on like also with getting people on board from Excel to think about learning R, like giving people that option to always have the Excel version of something too.

There were, there's so many awesome questions here. So I want to make sure that we get to some that were on Slido as well. And I know Toyin had to jump, I believe, but I want to make sure to ask this question. But Aaliyah, Toyin had asked, what strategies would you have for someone on your team to kind of combat, combat imposter syndrome? That is a really good question. So I would say to combat imposter syndrome really is, I think it takes just more practice. So just more like fine-tuning your skills and even just producing things maybe for yourself, maybe like your own projects that can really just back up your expertise. And then I also am really big on just learning how to communicate and then even just practicing like communicating like your methods, communicating your results. So I think that the more that someone shares what they've done, what they're doing, that it helps them become a bit more confident in their skills. And then also to not, you know, put so much pressure on yourself, but to understand that everyone's learning. And even like people that have high skills, they're always learning. There's always something new to learn. Everyone's not going to know everything, but to just be patient with yourself. But, you know, keep going, keep learning your skills and you will continue to get better.

Sorry, I'm trying to scroll through from earlier questions. So there was one on Slido that was asked anonymously when you were talking about tools that you use. And it was, what was the reason for moving away from Power BI? And then asking, also, do you use Shiny for visualizations? So I would say that the, now that's a good question. So that decision was something that was made before my time. And I think, you know, I don't know too much about Power BI. Someone can correct me. But to me, it just sounds like it's something that is maybe a bit more easier to use since we are able to utilize the server and people can connect live to data sources on our server. They can also like download workbooks on our server. So I feel like just maybe ease of use and then with just building this enterprise of technologies probably was the vision for that. And then the other question regarding ArcShiny, I have used ArcShiny in the past to do some visualizations, more so just, you know, practicing on my own, just so I can have an understanding of how to use it. But I haven't used it in a, you know, in a few years. And that I would say is because most of our visualizations have been in Tableau now.

Thank you. There was also a question from earlier that was, I think, the Sui, and apologies if I'm pronouncing your name incorrectly. But if you want to jump in, you can ask that too. Sure. Yeah. My first name is Brian. Last name, you got it right. It's Sui, like chop. Okay. That's a hard one to pronounce. Yeah, it is. You'd be surprised how many ways that can be said. Anyway, thanks for having me. It's been a really good discussion. One thing that a lot of upper management that my company is concerned with is, you know, with so many people and so much proliferation of some of these tools like R and Shiny, you know, Power BI, things like that, Power Query. How do you manage the code? And what does that look like? You know, how much reproducibility is required? I know, probably, in some of the healthcare, there's a lot of that. In my business, there typically hasn't been. And then also, how do you govern new technologies? Because we always have people that want to try the next shiny bubble that comes along. If it's not R, it's Python or Julia, or, you know, other technologies that somebody, you know, some wants to try. And how do you wrap your hands around governing that?

Yeah. So, to answer your first question, again, with just expanding the technologies that we're using. So, we will start using GitLab. So, that's really exciting that we will be able to create our repositories where we can share code across the agency. I think with that, that is going to be another heavy load of trying to get people to actually use it and learn how to use it and understand how to use it. But I will say that there is a data camp course on Git. So, we will plan to just let people know that it's out there and probably make that a required course to take. So, moving forward, that is the goal right now. And then I know that on teams, like smaller teams, as far as, like, code sharing and version control, I'm pretty sure that they, like, developed their own ways of doing things. But again, trying to make this a lateral movement, that GitLab will hopefully help us, you know, we can implement this thing across the agency.

And then your second question, I'm sorry, if you can repeat your second question, actually. Sure. It was about just new technologies or ideas that people have to bring and introduce new technologies in. Do you have a process for doing that? Or is it case by case? I would say that it is case by case. And we are open to mostly just look at, well, what are the benefits? So, doing, like, a cost benefit analysis. And then maybe even piloting. We have done piloting in the past with certain, like, analytics and platforms to see if this is something that we do want to take on. But, yeah, I definitely understand where you're coming from, that there is always this thing of, like, this is the next new shiny thing that we want to use. Let's try it out. But I think it's really just first we want to get comfortable at least using these new technologies that we're already kind of standing up. And then just taking it from there, really.

I realize that an hour just went by so fast right now. So, if some people have to drop right now, I just wanted to ask, Aliyah, if people have follow-up questions, what's the best way to get in contact with you? Yeah, so, you guys can feel free to contact me on LinkedIn. I don't know if I should put it in the chat. Yeah, you can put it in the chat. LinkedIn or even by email as well. And I'm happy to put my email in the chat. But, yeah, if anyone is interested in reaching out, happy to discuss more. Awesome. And there are a few more questions, too, but I don't know if you have to run to another meeting right now. So, just let us know. I do have to hop off. But I'm happy to join another week if I can be the leader again. But if anyone has any follow-up questions, please go free to, like, reach out. Yeah. Awesome. Thank you so much for joining and sharing your insights with us. And thank you to everyone for all the questions, too. I feel like this is one of the, like, the most questions of any session so far. So, apologies for not getting to some of them.

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Data Science Hangout | Aliyah Wakil, Texas DSHS | Increasing Data Literacy & Moving to Leadership

Transcript#

Strategies for data literacy

Dealing with patient data across multiple data systems

Increasing data literacy and getting buy-in

Moving into leadership

Technical vs. management career paths

Handling the "technical box" and imposter syndrome

Featured software#

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