About this episode
Tim Gasper [00:00:31.541] Once again for Catalog and Cocktails. It's your honest, no BS, non-salesy conversation about enterprise data management with tasty beverages in hand. I'm Tim Gasper, longtime data nerd, Nerd Product Guy, Customer Guy, data.world. Joined by Juan.
Juan Sequeda [00:00:46.341] Hey, Tim. It's Wednesday. We're live here, middle of the week, end of your day. And it's time to take that break, have a nice drink, a cocktail, and let's go talk about data, metadata, knowledge, all that stuff. And today is one of these episodes where I'm like, finally, we're doing something that we should have been doing more before, which is we need to get comfortable being uncomfortable. We need to really bring in different diverse points of views. And from the data world, we need to just learn stuff that we're like not doing. And I am really, really excited about Amalia Child. So Amalia, we got connected with her other folks through Jenna, Jenna Johnson, I think. And she said, look, here's this person who's actually from the library sciences combining data. And you got to go meet her. And she's writing this great article about stuff we'll get into. So Amalia Child, a data manager and librarian, because how many people in the world can say those two things? Welcome. How are you doing?
Amalia Child [00:01:43.721] Thanks. I'm very well. Happy to be here.
Juan Sequeda [00:01:49.621] Fantastic. So let's kick it off. What are we drinking and what are we toasting for?
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Should I start? I'm drinking a phony Negroni. I'm nothing if not an elder millennial. So Negronis are my drink, but it is a weekday. And yeah, it's all right. It's not as good as a real Negroni, but it's fine. I'll do the trick. And I would love to toast to so I had two professors in library school who unfortunately have since passed since they were teaching me but they had a huge impact on my career and I would love to honor them Jim Monterazzo was my special libraries professor we can talk about what special libraries are if you'd like and Michael Sullivan was my public libraries professor and they've both definitely informed my approach throughout my career so. Cheers.
Juan Sequeda [00:02:29.737] Cheers. Cheers. That's awesome. You like you go back to your academic settings and you're like, there's all these people a long time ago who have made an impact and you don't realize it. Then you realize and like, yeah, these people will be there around for your entire life. And that's pretty cool. Yeah. Yeah. Tim, how about you? What are you drinking? What are you toasting here today?
Tim Gasper [00:02:48.257] I have made something up which is uh i've taken a little bit of whiskey and i uh i had like some, hibiscus liqueur and a little bit of rosemary liqueur and so i was like i'm just gonna see how this tastes it tastes okay it tastes all right so uh i don't have a name for it yet so audience members please come up with something um but uh i just want to say cheers also to yeah i think that's great Amalia like those who had it influence us in our academic settings like Like, especially for me, I had some high school teachers that were just incredibly impactful to me. I know one of them has passed away. So, like, just cheers to the amazing people that have an influence on us and get us going on this journey of learning.
Juan Sequeda [00:03:28.837] So I have. So here's the story of this. This is an Americano Aperol Spritz. So I've had a long day. I've had a lot of coffee. And then it's like it's four o'clock and I still have some of my coffee. like my third or whatever and we're like okay i'll just do something with my and i'm like oh bailey's or whatever i walk into my bar and i'm like there's april and i'm like let's look for coffee and april and i saw some cocktails like let's go try that actually this is pretty good it sounds pretty good i don't know if i could take the caffeine at this hour but. I'm colombian so i get i drink coffee all the time but this is actually like gets the sweetness And it's like, hmm, I'm liking this one. So, and let's do that. Cheers to our professors. Cheers to our professors who have really made an impact in our lives. Cheers to that. So talking about books and libraries, our warm-up question today is, what is your favorite book or your favorite author?
Amalia Child [00:04:27.637] Right. You gave me time to prepare this, and I completely forgot. But I think my default answer has to be Joan Didion as an author. I studied her in college. She's a novelist and essayist and screenwriter, famously from California. She's had a resurgence among some of the more stylish girlies these days. But I loved her essays in college. And she's known for style and tone and cultural commentary and politics. So, yeah.
Tim Gasper [00:04:55.331] For me uh that's so tough uh i'm gonna say i'm big i'm a big fan of malcolm gladwell and so uh blink is a really interesting book i mean all his work is very like thought-provoking makes you think in new ways and a lot of times there's a lot of data behind it so yeah i guess i'll say that.
Juan Sequeda [00:05:14.991] And uh for me one of the books i started reading as a kid which i really enjoyed is everything by Michael Crichton, the author of Jurassic Park and all that stuff. And I just really loved how I would read his books and I would imagine a movie in my head. And then I would actually go watch the movies because a lot of them are in Jurassic Park. And he has some cheese like Congo and stuff like that. But you would watch these movies and it would match so much with what I had in my head. And that was just so fascinating. And he has so many different movies that come out of his books. So I've really enjoyed reading his books. And I have to go back. There's so many classics.
Tim Gasper [00:05:47.951] You're a big Jurassic Park fan?
Juan Sequeda [00:05:50.971] Yeah, I have all the Jurassic Parks and then the Rising Sun. He started off being an anonymous writer because he's an MD from Harvard, so he had some medical stories back early on. So he has a very fascinating life. Interesting. Yeah. All right, but talking about libraries and books, let's dive in. So you wrote a post a month ago called The Five Laws of Data Enablement, how the father of library science would make his data team indispensable. Honest, no BS. What does that even mean?
Amalia Child [00:06:25.851] Well, the title is a play on the five laws of library science, which is a book that S.R. Ranganathan, who is known as the father of library science in some places and circles, wrote in 1931. And so I basically have adapted his book and his laws to modern data management. And I think his focus on emphasizing the use of books and data in this interpretation, I think Jenna Jordan actually gave me the title, led me to call it the Five Laws of Data Enablement rather than something like the Five Laws of Data Governance or Five Laws of something Data Management. management. And so I really wanted to lead with that enablement. And thinking about kind of the tone of some conversations I was picking up on this year in data, I think since interest rates have risen and sort of Gen AI is coming in, I just felt a little like, and maybe it's just my bubble, but like a little deflation among some data folks, a little pessimism. What are we good for? What are we doing here? There's so much competition. Are we making ourselves obsolete? That sort of thing. And really wanted to bring some grounding and optimism into the conversation, if I could. That's what I got from the book, anyway.
Juan Sequeda [00:07:36.085] So before we go into discussing all those five laws, we started talking before getting on live, telling us all the perception. I mean, people are reading this and kind of the impact it was already having. So let's get people excited about, hey, if you haven't read this, go read it. But look at the impact it's already having. Sure.
Amalia Child [00:07:57.285] Yeah. So I think one of the reasons I wrote it is that I introduce myself sometimes as a librarian in the data community on and off. And I get a lot of reactions that are sort of like Dewey Decimal System or just a little bit simplistic about librarianship. And there's a lot of complexity that goes into librarianship and library science that I wanted to also surface to the data community and these parallels. Between the two fields. And so, yeah, I think the start opens with some historical context and kind of trying to identify some of those parallels and then has these five laws that I think some folks, it sounds like, have shared at meetings with their teams or sent along to their colleagues in different departments. And yeah, folks' reactions have been great. I think my favorite reaction probably came from the institute that Ranganathan founded in Bangalore. Someone named Janavi found me on LinkedIn and told me that she was really excited to read it. She had worked in data and is now studying library and information science there and had just celebrated his birthday with her classmates and everybody. And it was just like excited to see his legacy, you know, in the U.S. living on. So that was one of my favorites. Yeah. It's really neat. It was a really great note.
Juan Sequeda [00:09:10.653] That's fascinating. I mean, you should be very proud of yourself. So let's dive in. Let's go through these. Tell us about law number one.
Amalia Child [00:09:18.713] Well, should I start a little bit just with the framing at all?
Juan Sequeda [00:09:21.173] Actually, yes. Sorry.
Amalia Child [00:09:24.933] Books are for use. And so, you know, in 1931, Ranganathan was, he had been a math professor who was kind of a reluctant accidental librarian and fell into it. I'll make the long story short, got really excited about librarianship and studied it kind of across the globe, but especially in England and was learning about contemporary library practices. He was reluctant in part because the library that he had his first job at was pretty boring. Nobody was coming in. Nobody was using the books. There was just like not a lot going on. And so he was putting this in context, thinking about how, you know, back to medieval times, books were like chained to the shelves and librarians were tasked mostly with protecting texts that were hard to reproduce and like could get ruined by people touching them protecting those from everyone other than like specialists and scholars um but as democracy rose around the world and printing technology changed um you know by the early 20th century there was a paradigm shift in the attitude that we should like boost literacy and open up access to books and people will become you know better entertained but also um you know better educated and more literate and that will have economic returns and social returns and it'll be a great investment basically and so there were a lot of angles on that and that changes how you architect your libraries how you you program your libraries how you collect which books you collect um and then how you organize them so that people can come get them and then allowing people to actually touch them and and bring them home um and so as i was reading through kind of that history and framing of the book obviously i just saw a lot of parallels in the shift in data management over the the past few decades, you know, that happened over centuries, where, you know, data became cheaper to store and process, and there are new sort of modes of access. And we got on this sort of data democratization kick, and self-service analytics and all of that. And so it just, all these parallels were just, you know, like,
Tim Gasper [00:11:13.693] well, I see these things, they, yeah.
Amalia Child [00:11:16.393] And then as I dug into the into the laws, and we can talk about them and all his anecdotes, They're just kept being more and more analogs that were just fun to find and identify. So the first law is that books are for use. And so I go into all that framing because you kind of it's obvious and he sees it as obvious, but it wasn't obvious at the time. Now that's how we think of libraries. And so if that's the case, and if data are for use, and we want to get it into people's hands and enable people to use it, how does that change the design of our program and the way we staff our teams? What are sort of the ergonomics? So he was thinking about like, locating your library centrally, instead of up on a hill where it's pretty, you locate it where people can actually get to it, and you open it during hours that makes sense when they're not at work, or, you know, all hours of the day, basically, that people are awake is what he says it should be. You add comfy furniture or maybe you add a little garden so people actually want to go and be there and sit down and read a book and then you staff it with people who are going to be welcoming and enthusiastic and like ready to help and curious about you know if you come up to someone at a reference desk and ask you can ask kind of anything basically theoretically it's information related but it's it's a public service so you can ask anything and the librarian needs to be ready to kind of receive that and peel back the layers of what you're really asking and contextualize are you a five-year-old asking about birds or are you like a professional bird watcher? I don't know if that exists, but like you're going to need different books depending on that background. And so you want to have people who are both technically savvy and educated, you know, scholarly and can get to know the collection and have the skills to organize it. But you also want people who are just interested in people and making sure that they are served with the information that they I need. And so, yeah, that's basically the first law. And so the reference interview is a concept that, just to mention Jenna once more, has a post about kind of expanding on the reference interview and requirements gathering and data. But that's like a process that librarians have aligned on that is meant to convey that empathy and support and sticking with the problem until you can find a solution, whether it's like a book in the collection or some other information solution that's going to get them what they need.
Tim Gasper [00:13:25.048] So I love this first law, this first parallel here, obviously, it ties so well to, you know, this movement that we're seeing all throughout the sort of data landscape now around data democratization around self service analytics and self service data consumption, right, this idea that, wait a second, how can we open data up for other people to be leveraging? Leveraging, you know, it seems like, in obviously, the library kind of world, right? Like the problems have been mostly solved around, you know, hey, how do we let somebody borrow it? But what if they don't bring it back? Oh, well, they'll be fine. And you know, like, there's a system that makes sure that the bad things get taken care of, right? But seems like in data, we're still we're still working through some of that those things. But the goal is true, right? Like, if you want people to use data to make an impact, to make a difference, to do their jobs better, then you have to let them have it and you have to find a way to let them have it. Yeah.
Amalia Child [00:14:24.068] And yeah, I do want to emphasize, like, I completely understand that there are legal and ethical obligations that we need to fulfill. Like that's, it's not sort of, and you know, I'm careful to say what we call governance because I think you can define governance in a lot of different ways, but what we call governance around security and quality, like there are standards that we want and need to meet. But beyond that, when you have an option of saying like, yeah, I'll work with you in Excel, instead of making you sort of conform to what I think this data flow should look like, maybe that's your best option on this first pass so that you can build trust and they'll come, you're not alienating them and removing them from the tool they're most comfortable in, unless you see like a real business risk to using Excel for that use case. Just stick with Excel, solve that problem there. And then you have a chance of them coming back and, you know, following your process next time when it's a more appropriate solution, that kind of thing is the kind of choice I'm talking about.
Juan Sequeda [00:15:14.408] And so one of the things you brought up was these reference interviews and requirements gathering. Can you dive into that? Because I think this is something that from the library science is like, this is well-trotted territory. And now we're talking about data product managers and done. Right. The way we reinvented the wheel. So yeah, existing wheels.
Amalia Child 00:15:33.888] Yeah. And, you know, I no shade to product management. I think they're, they can be complimentary and there are elements of that process that I think are very analogous. And I think, you know, I'm, I'm not an expert product manager. I've seen, seen guidance for requirements gathering. I think the reference interview really emphasizes that trust building and relationship building and empathy piece in a way that I just haven't seen in a ton of the material about product management. Maybe I'm just missing some material. And so, and there are certainly technical aspects to the reference interview and, you know, guidelines as well, in terms of what the steps are for how to do research together. And that might, you know, echo a lot of what's in the product management requirements gathering guidance. But I think what I see is that emphasis on the skill set around making sure they understand you're paying attention to them, you're a priority, and sort of following through and finding a path to a solution, even if you and your team aren't going to be the ones who are going to to provide it. So you see a lot of libraries offering resources that point people in other directions, even if it's not the library itself. And I think some people quibble with the idea of a data team as kind of a connector. But I think that we can be unusually situated to be a connector across the organization, since we have our eyes on so many different data consumers and producers, that it's one way that we can provide solutions without adding actually to our workload.
Juan Sequeda [00:17:01.116] I think that what you're opening it up is this connection part, right? It's like, if we understand, our goal is to really understand what is your true pain. And we have more like the data, the books, the library, all that stuff. I can really pull you to the right direction if I truly understand what you're trying to go do. Therefore, let's go really understand that. Because if otherwise you're just like, I need this. I'm like, you got to ask the why behind the why behind the why. Otherwise you're like just passing people data that you don't even know that's what you really need what is the problem trying to go solid because if you told me i can think that's not really what you need you need these other stuff and these other people connect to that stuff so.
Amalia Child [00:17:36.396] And i think the other piece of it is um you know that sort of getting to know your customer patron stakeholder whatever you want to call it over time or just knowing your organization so that you know like did they just come from a really high pressure meeting where someone got raided out and that's part of the urgency or you know if we develop this metric together and it shows that that they or their team aren't performing the way that they expect? Is that some anxiety that they're bringing to this organization? That's a lot of the other stuff that goes into the reference interview where you're thinking about there are sort of insecurities or external influences that could be changing the nature of the conversation. Like there's some sensitivity of data that we don't really always talk about where it doesn't always show a rosy picture. And so people don't wanna look at it. But in order to make progress, we actually need to be rigorous and do it anyway, right? There's a lot of emotion tied up in that.
Juan Sequeda [00:18:24.023] Tim, this is just a reminder of like the, what episode, I forget who it was, Ergist, he's like a recommendation. Like he was like, we're talking recommendations for data engineers. He's like, we need to be more empathetic. And I think another topic we've always had here is like the data therapy, having these therapy sessions. It kind of feels a lot like that.
Tim Gasper [00:18:50.783] Yeah, I agree with that. So let's move to the second law. So like, what's the second law of library meets data?
Amalia Child [00:18:57.843] Yeah, so the second law sort of is one of the other ones that Ranganathan really emphasizes. The last three are sort of shorter chapters. But it really doubles down on the idea that when he says they're for use by everybody, I mean everybody. And he was pretty progressive for the time. You know, he's talking about women and people of every class and all of that. And so, you know, the way I interpreted that was that a lot of the time, I think data teams focus on the analysts and the data scientists, and we can talk about what the definition of a data team is. Here, I'm really talking about kind of that data management central function, people who are sort of thinking about strategy and the end-to-end lifecycle and not sort of individual pieces of the flow. So we often think about analysts and data scientists as our core users, or at least I have. And this is really trying to say, no, we mean everybody. And that also means that everybody has a role to play in kind of the data management process and the data use process. So he says at some point, you don't just dump a bunch of books into the middle of a room and let everybody have at it. That's the piece that's a mix of enablement and governance. So I like that. Or a lot of people seem to respond to the idea of the little free library. Which I do have little free libraries in your neighborhoods. Have you seen those?
Tim Gasper [00:20:17.383] Yeah, we have one in my neighborhood. Yeah, it looks like you do one.
Amalia Child [00:20:21.043] Yep. Okay. Does it resonate with you that it's not the best books in the neighborhood in that little box? So people don't know them. These are sort of cabinets or sometimes they look like big birdhouses. They're lovely in their intent. And I like seeing them around my neighborhood. And they're usually sitting on like a fence post in somebody's lawn. And they're meant for it to kind of it's like a leave a penny, take a penny kind of thing, except with books. So you can put books in and you can take books out. Obviously, it's free. And usually somebody sponsors it in their yard. But they're not taking an active hand in curating the collection. They're not soliciting interesting books from their neighbors. It's just sort of a free-for-all. And if you asked people to pay for it, I don't think anyone would. Whereas when libraries in your city that are sort of well-run and beloved are threatened with budget cuts, people will come out, even if they're not library users themselves, because they see their community and its needs reflected in the library, whether that's the school kids or the older folks needing, you know, computer help or access, that kind of thing. And so, you know, this is basically the argument that it takes some administration and investment to get the most out of data. You can't just open up access and, like, expect to get a ton of value. And so he advocates for a federated approach. You know, this idea is really designed for public libraries, but I think a lot of folks tend to adopt or drift to the hub-and-spoke model where where you have a central library or a central team that is going to use and manage infrastructure or shared resources efficiently. And then what he has is branch libraries, but you might have kind of like domain teams sitting closer to areas of the business and specializing a bit more in those specific requirements. And then among the stakeholders, you kind of have the obligation to treat these shared resources as shared. And so their interaction with these shared resources, these data sets. And tools can have impacts on the organization and on their colleagues. And so they just need to recognize like you're there to enable them and not to inconvenience them. And those policies, in theory, are there for a reason. But they have to understand those risks and those benefits to themselves and each other to, I think, be incentivized to sort of go along with whatever policies you've set up and best practices and that sort of thing.
Tim Gasper [00:22:32.056] This is this is kind of um blowing my mind a little bit because uh i'm sure Juan can see my expressions if we've done enough of these episodes now uh where i'm like oh crap like libraries have been doing data mesh for like decades
Juan Sequeda [00:22:50.616] Oh okay tim
Tim Gasper [00:22:54.036] We think we're so clever we're like oh data mesh we're like oh shit we're we're 40 years too late.
Juan Sequeda [00:22:57.756] 40 years too late...400 years too late.
Juan Sequeda [00:23:00.336] Okay, that's it. Libraries have been doing data meshing centuries.
Amalia Child [00:23:08.796] That's funny. Yeah.
Tim Gasper [00:23:13.336] No, this is awesome. I mean, it's exactly right. It's like there's, you know, if it's a small town, right, you might just have one library, right? But as the city gets bigger, you might have a centralized library and then you have branch libraries and they need to fit together into a system. I mean, you're not going to have the exact same books in every single kind of library. And you've got different specializations, right, that start to form. You get librarians and administrators and different structures in terms of people to govern all that information. And why do you have governance? The purpose of that governance is not to take people's books away from them. It's to put the system in place that allows you to give the books to everyone.
Amalia Child [00:23:51.336] Right, exactly. Okay. I like to think a lot about libraries and vacation towns in part because I have two nieces that I'm obsessed with. And now that we go on vacation, we use the libraries for that. I go to libraries almost everywhere on vacation because you can charge your phone and sit in an armchair and pick up a book that you left at home and just keep reading and that sort of thing. Um but yeah with the kids we go we tend to go in sort of vacation destinations and thinking about the way that uh sort of those types of towns organize their resources um sort of seasonally or um and like programming and allocating their budgets just because there are kind of competing interests in terms of the locals and the and the visitors and the fact that most visitors don't pay into the library but you still want to support them um again seasonally it's that's just sort of one interesting example of that yeah and that's another another piece of this this law is that um. The community or the organization needs to have a sense of its vision and its identity and its goals for your data team to respond to right it's really hard as a data team to prioritize if the company doesn't have its priorities organized um and same same for any library right if the town doesn't and really know who it is or what it is, it's hard to program for, yeah. Or if you don't have data on your town, for example, like librarians are very strategic and data-driven and use a lot of statistics to inform their decisions about this stuff.
Tim Gasper [00:25:13.996] What's an example of a vision that like a library system might have, which would allow them to kind of rally around some clarity?
Amalia Child [00:25:25.956] That's a great question. Yeah, I mean, I think libraries tend to have a few different governing bodies, right? And so you have the administration and the city and then also like a board of trustees and that sort of thing. So you take input from the community and as well as kind of the administrators. But yeah, a vacation town feels like one of those where you, tourism is probably part of your town's identity. And so you want that to be reflected in various services. But you also have, you know, a population throughout the year. This is a terrible answer. Let me think about this.
Tim Gasper [00:26:02.589] No, no. I actually like it. I wasn't sure where you were going to go, but I like that.
Juan Sequeda [00:26:08.709] That makes sense. I mean, it's like, I mean, going back to the, like the analogy is like, we have to understand with organizations. It's like, what is your identity? Like what are your objectives? What are the values that you are trying to go put out there? And I mean, and that's really going to inform like where are you going to go invest more? Like we need more data stuff in here versus this other thing and so forth. Right. Are we, are we, we, are we really customer centric? Are we really customer driven? Right. This thing, are we really, are we really about like operational costs? So low, we're trying to be so lean. Right. So I'm like, I mean,
Tim Gasper [00:26:40.169] and how do you connect it to your identity? Right. Because like, if, if your vision is democratized data, it's like, okay, well, good. You want to do that. Right. But it's not specific to your identity.
Juan Sequeda [00:26:51.189] That's like, yeah, we need to have a library. Right. Yeah. Yeah. I get it. But we're a vacation town. There's a lot of tourists. Well, if we have libraries, I think I'm going to get a lot of the books around. There are going to be things about things that you can do here, right? Right. There's more of those books versus something else. Yeah.
Tim Gasper [00:27:08.871] Beach reads, fun reads, right? Yeah.
Amalia Child [00:27:10.671] And then on the flip side, I think you probably have some more cities that are known for an entrepreneurial spirit, and they may have more of a workspace type of thing and different types of a business center or technology center, that type of thing. And so you see, you see, if you look closely, you'll see a lot of libraries sort of adapting their collections to their populations that way. You might have a ton of kids or not a lot, a ton of kids, you know.
Tim Gasper [00:27:34.191] Right. Yeah. Yeah. Kids, you might have more kid centers and things like that in the library. it's a more entrepreneurial spirit, you might have more spaces where people can go into a closed room and there's a, you know, people can get some work done collaboratively in small groups and things like that. It's even more than just the books. It's also the spaces and the experiences that these libraries are creating.
Juan Sequeda [00:27:57.091] To translate this back, what is the experience that you're providing then within your organization for people to go use the data? Is your organization very technical? You're a software company, right? You build software. So the majority of people in your organizations are very, very technical. That's going to be a very different experience than if you're not one, right? You don't do technical stuff, right? I mean, just thinking, I mean, not non-salesy stuff, but we can publicly say that one of our customers is Indeed, for example. Indeed is a highly, highly technical company. Even the CEO goes in and writes code and stuff. So they have a completely different experience of some of the other customers who are like, no, we just want to have a marketplace experience and stuff. I think that this is really resonating. This is about understanding who your community is. And there's like no one size fits all. All right. I love these. Keep going. Keep going. Keep going. Because, um, yeah. Yeah.
Amalia Child [00:28:58.712] So third law is the flip side of the first, the second law. So every stakeholder, their data set, third law is every data set it's stakeholder, right? So, uh, the first component of this is really leaning into sort of education, marketing, and outreach. And a lot of librarians, you know, in school environments and academic librarians are actually sort of instructors, um, are certified as teachers as well as being librarians. Um, so leaning into sort of education, marketing and outreach practices in order to make sure that the folks who aren't sort of naturally just going to jump at the chance to have access and, and follow that path all the way down to whatever technical, um, sorry, whatever use cases you intend for them to use, like some, especially if you're pivoting from more of a restricted access governance focused paradigm, you know, over decades or months. To a more access based orientation, not everybody is going to know what they can get from the data or how to work with your team. And so this is a chance to use sort of onboarding sessions or documentation or just like a sort of more intuitive architecture in order to make. The data more accessible to the folks who aren't sort of naturally inclined and so or like already aware whether from a previous organization or a previous role of of how to work with you and I think some of the folks who are naturally inclined can give us a false sense of confidence that what we've built and what we're providing is intuitive and wonderful and we think of them as our champions and they're amazing but and I think they can also be like a, point of access to the folks who don't feel that way. But yeah, this, I think I'm a big believer in sort of level setting sessions to onboard folks and just make sure everyone kind of has a point of entry. Who is this team? What do they do? What are they for? How do I contact them? Basics. And then from there, you can get into sort of more advanced stuff and, you know, data catalogs and enriching metadata and making that available is one mechanism and so on. Yeah.
Juan Sequeda [00:31:09.022] So the way I'm interpreting this is like we have all these books, we have all this data, and then we really need to be able to kind of educate the community out there. It's like, here's what we have and here are the opportunities and not just expect like, oh, we know that they're going to build it and they will come, right? Yeah. There will be some folks who will build it and they will come, but we have to be careful saying, oh, those are their champions is because there's maybe so other people who can really take advantage of that who are going to be very diverse kind of backgrounds on this, but we're not paying attention to them. We're not going out. We're not outreaching them. That can actually kind of change the perspectives of stuff.
Amalia Child [00:31:44.242] Yep. Yeah. And I think, you know, we are the sort of data experts. And so there are probably cases where we understand that a certain data set could be really useful to a certain team. Can we make that connection for them? There's something in librarianship called reader advisory, which is a little different from reference, where somebody comes to you saying like, can you recommend something? Here's something else I liked, for example, or here's who I am. Um. And I think there's an opportunity, you know, you don't want to sell anything people don't need, but there's an opportunity to do some of that matchmaking from the vantage point of being the expert in the data and understanding the data that's available with those teams who might not sort of intuit automatically that that might be useful to them in their decision making. And then the flip side is that if you've tried to provide data sets, tools, newsletters, services, whatever it is, and nobody's coming, like cancel office hours, let it go. So weed, you know, I mean, you should make a good effort, but, you know, weed the data sets. We call it weeding in librarianship. Archive, put them on ice. Things that nobody is using. It's expensive and it sort of clutters things up in a way that makes things harder to navigate for a lot of users, I think.
Tim Gasper [00:32:54.076] This was actually kind of the question I was going to ask you is like, well, what happens to the books that people aren't reading? Or, you know, you said weeding, right? I think in data management, we think of like sort of data lifecycle management, right? Right. And like, it's time to archive. It's time to delete it. Right. We don't need that table. This is all part of the process.
Amalia Child [00:33:11.736] Yeah. Yeah. And, you know, I think librarians and archivists have this reputation for like being hoarders that I think is a misconception from maybe previous times. You know, even archivists are very strategic about what they acquire and what they keep. And they have a process for deaccessioning based on some rubric of like, what's valuable? What, What do we need to keep for posterity? Okay, the auditors are going to come. We have to keep that data set. We can't get rid of it. But other things like, you know, sort of the Marie Kondo approach is overplayed. But like, you know, thank it for its service and let it go. There's a reason you walk into libraries and they don't have every book they've ever collected. They have a physical space. It's a real constraint and a budget constraint that they're working with. So there's a whole process for decommissioning books and weeding books. And I used to be on the board of the Friends of the Library in a city near here, and we ran the book sales. And that was part of some of the sort of inputs to the book sales were decommissioned library books. And you'd see the jacket with the call number and everything. And then other ones were donated by the community. And so those would get resold for like a dollar a pop. And then there's a whole... Sort of waste management process from there they go through all the different stages of trying to get sold and then eventually
Tim Gasper 00:34:28.645] That's fascinating this is the part of libraries that i have no idea about
Amalia Child [00:34:31.365] The underbelly it's like happening in the basement
Tim Gasper [00:34:36.185] What happens to the forgotten books. Um now one other related question to this is like um and you mentioned it a little bit is this like is a curation aspect right and like you know you go to the library and you see things like that that table in front that says like, you know, you know, hot reads for, you know, a cool day or something, you know, like there's like these curated kind of things. I mean, that's sort of a, you know, sensational example, but sometimes it's topical. Sometimes it's genre oriented, right? Sometimes, you know, it can be different things. Is, is curation part of this kind of law and this story, or is it kind of part of something else?
Amalia Child [00:35:11.965] Yeah, I would say so that sort of promotion and marketing that certainly falls under the third law, those, those displays. And I would say, I, you know, in my research role, often we would come across things just in the course of research. And you'd say, I know this team or that person was looking at this last week. Like, I just found this interesting thing that just came out. I didn't have access to it when they were asking for it. I'm going to send it along proactively. And it takes a little maturity and familiarity with the organization and with people to like do that. Because when you get something like that and it doesn't hit the mark, you're kind of like, okay, now I have to respond to it. But when it hits the mark, you're like, oh, they were thinking about me. They understood what I was interested in and what might be helpful to me. And I think it really just demonstrates that feeling of being like plugged in with your organization and means a lot to stakeholders when you do that, I think, when you get it right. And so it does take a little bit of, I think, professional maturity and like institutional knowledge to get to that point. But yeah, that's sort of that proactive outreach.
Juan Sequeda 00:36:10.125] All right.
Amalia Child [00:36:12.905] Oh and sorry the other piece of this and we can move on but is um one of my favorite parts was in the book Ranganathan mentions as like a lure to get people into like more serious literature and and boost data literacy was to create these like comfortable um rooms close to the entrance for like periodicals magazines and newspapers because that's what people were going to read like regularly and it was easy to read and so that's how you get them in and so i think of that is, like, give them a data set that's fun to work with or that they really can see themselves and their team in, if you're doing a demo or something like that. Like, give them something that's going to resonate and feels easy to engage with versus, like, your most impressive and challenging data product. Yeah. It seems like he was trying not to be snobby about magazines but he sounded kind of snobby about magazines
Tim Gasper [00:37:01.766] These ones don't count as much
Amalia Child [00:37:06.406] I can't say enough about how weird and funny this book is.
Tim Gasper [00:37:09.266] So um yeah what's what's the fourth law?
Amalia Child [00:37:12.726] Yeah, also pretty intuitive save the time of the stakeholder or the reader um originally if nothing else they'll go around us if we don't data solutions pretty quickly and so this is really i think it's pretty intuitive to people that that people need things quickly and they're they're going to see more value out of data if they get it you know quickly by the time they need it um and so he highlights three mechanisms that i've translated or not mechanisms strategies that i've translated loosely to you know building self-service tools so you see in libraries like so i think of wayfinding and signage as as a self-service tool. That's how you navigate the Dewey Decimal System yourself for the Library of Congress system or whatever. If you don't know kind of call numbers by heart, you'll see a lot of like color coding and sometimes just the very architecture of the building will help you kind of make your way through the system. Self-service, self-checkout kiosks, just like at CVS. The Libby app, I don't know if you've used that, but it's a great app that was developed, I think, like in collaboration with librarians, that will give you access to e-books and audio books that your library network holds. So I use it a ton, just on your cell phone, things like that. So you can just sort of self-serve and never interact with a librarian. And that saves the time of the librarians as well, right? They don't have to serve every one of those requests. And so I think there are a lot of applications for that in data. We think about self-serve analytics, data products, all of that falls under that bucket. But I also have experienced quite quite often as a data consumer and librarian, that if you're really engaging with data, it's not that hard to hit the limits of a self-service tool. Like sometimes if you're really digging into stuff, you might need to differentiate whatever your analysis from the definition that was set for you in whatever that user interface is. And so making the data team or the librarians available for when people hit the boundaries of those self-service tools, I think is needed in many cases. And obviously we all deal with like burnout out and overload in that context but um so you have to manage that that volume sometimes but just making yourselves available and so people know how to find you and then the third is meeting people where they are and embedding you know analysts or solutions in processes and workflows and tools that already exist or teams that already exist and i like the example there of the bookmobile, Which we can talk about, if you'd like. I don't know how much you know about bookmobiles. They used to be like horse-drawn wagons. So they go way back, and they've changed form now. They're more like minibuses, usually. And, you know, they can be used to deliver materials that have been requested by a community that can't make its way to the library for mobility or distance or time reasons. And so that's kind of like, you know, on-request delivery. But often they're also used to sort of curate a collection based on whatever the community at the destination might be interested in, again, using some data about what they might be interested in. And then sometimes it's come with programming. And that gives you a point, once you get there, it gives you a point of access to folks who don't necessarily walk into the library and tell you what they need. And so you're getting a better understanding of your community and hearing from people just by being out in that part of your city or whatever. And then all along the way if you have your logo on the bookmobile it's sort of a marketing tool for everybody to get a visual reminder of the library who might not pass by it by their their branch every day and so it serves like many different functions um which is why i like it.
Juan Sequeda [00:40:36.002] I'm thinking about the analogy of like how you would do this what is the equivalent of the bookmobile meeting people where they are in organizations it's like really like doing these workshops or stuff like going in there and like i won't you won't come to their to our data catalog our marketplace and let's go let's go do some workshops with different kind of parts of the org to understand or i we've talked to a few people let me go show you some stuff that we have that your colleagues that are interested in and we want to hear from you so yeah
Amalia Child [00:41:05.362] I think about it a lot it's like also just breaking out of our not every team is like this but if you have some rigidity about the stack that you work I think of it often as breaking out of that. So the example I used earlier of just solutioning with someone in Excel, if that's what they're working in and it works fine for their use case, but they need some help with data and data expertise. Like that's what you bring to that situation. And it gives you that point of access into, okay, this is how they're solving that problem. Maybe in the future, that's something we can build. We can put it on our backlog and build it out differently, but you're not alienating them. You're meeting them where they are at the moment. Again, if there's no great business risk in handling that in Excel, work with them there. Or we all complain about Salesforce. I just saw someone the other day kind of making this point, so I'm building on it, if you will. But we all complain about Salesforce and Salesforce objects with like 500 columns or whatever. We're the data experts. words, we're too far downstream often of the process of like building things out in these operational systems. Is there an opportunity for us to partner with people rather than having to clean it up in the warehouse, you know, six months later? Is there an opportunity for us to be part of those conversations instead? And I think some teams are doing that. But this is just an example of it
Tim Gasper [00:42:21.358] It starts to go beyond the metaphor a little bit, but it starts to make you think like, how How can we streamline this? How can we make this system better? How can we ultimately result in time savings for individuals and the organization? And that may require that we move up and down sort of the stack here, left and right, to people that are upstream, to people that are downstream. Another thing that crossed my mind when we're talking about the bookmobiles is there's an aspect to this which we're solving through humans right where we say hey here's a data analyst and they're coming to the marketing department and saying like hey look uh i know you guys are struggling with x and y problem like i here's a couple of data sets that might be useful to you and you know here i created a couple of reports already that i think you might be able to leverage and you're kind of bringing that curated collection to them in your analyst mobile bookmobile and trying to help them out. Yeah. Yeah.
Amalia Child [00:43:24.158] Yeah. And to the degree that there's capacity, I think also like folks will send analysts to different meetings and that just saves, saves the time of like explaining what happened in the meeting and getting that recap. Like you want to save the time of the data team where you can as well. And I completely recognize that, that issue as well. But so you have to obviously use, use a mix of tools in the kit and find the appropriate moments for this.
Tim Gasper [00:43:45.558] You can't have thousands of bookmobiles per city. that doesn't work.
Juan Sequeda [00:43:51.658] All right, we got the last one.
Amalia Child [00:43:56.658] So the last one is that basically if you follow these four laws, your data function or your library will grow both in terms of like the size and the number of books or data sets that you're managing, your team, your tools and services over time, as well as in the sort of, it'll change and grow in the form that it takes. And so, you know, I think we see over the decades evolutions in tech and circumstances and priorities for any given data team and for the industry as a whole. And so I think that's both, exciting and optimistic for a lot of data leaders and also really daunting um to sort of have to renegotiate your boundaries and your scope um when new technology emerges or when new needs arise i think it's a good problem to have um a better problem to have certainly than nobody engaging with the data um but uh yeah i i at moments where i feel sort of overwhelmed or daunted by that idea i do think it's helpful to come back to sort of some of these grounding principles and like think about what you're, what you're here to do and, and celebrate incremental wins. And, um, you know, on some level, like touch grass and think about, you know, what is the business trying to do and not worry so much about like, whether you're keeping up the latest data tech.
Juan Sequeda [00:45:14.780] It's for me, it's like, if you're, if you're, if the note, you know, if you're being successful, if you, if your work just got freaking more complicated.
Amalia Child [00:45:27.120] Right. Yeah. Yeah. And, you know, change is constant. My boss at the investment firm used to say that all the time. And that's hard, but that's what growth feels like, I think. Yeah.
Juan Sequeda [00:45:39.360] Wow. Okay. This resonates. This connects. My day-to-day just talking to customers and prospects and just leaders and friends and everybody's face, everything you just said is just so connected with what I'm hearing every day. And I know, and it's just, there's just so many, once we're having this conversation, it's like, oh, this is kind of obvious. This is kind of like, but we don't, we need to make these connections. And they were like, if I would look at it from that perspective, it makes sense. I mean, the simplest thing, it's like, oh, libraries, if you're in this bigger place, you have a central library, you have branches. Like, we all talk about what's a centralized place. You're already centralized. Like we've been doing this type of stuff forever and i just look at the stuff that in your own your own city your own town like just go to the branch in your one library and go to another library and probably be different just trying to understand those things like the stuff is like so much right in front of us that we that we i know it's so freaking complicated when it's not it shouldn't be.
Amalia Child [00:46:45.200] I know but it yeah i think so many professions feel sort of oversimplified or misunderstood from outside. And libraries are no exception, but they're also not alone in that, or librarians. And so I think, yeah, it's easy to oversimplify from outside, but they're, yeah, they're very similar in my experience, this layer, at least, of the two things. And, you know, I've started to think about it a little bit. It's not quite right to left. I feel like it's a stack all along. It's sort of like the computer science, data science, information science, and library science layers of all of these problems. And, yeah. Yeah. Anyway, I don't know.
Tim Gasper [00:47:22.730] I love it. I love, I love the parallels between these two universes. And honestly, they're not, they're not parallel universes. They're overlapped. They're highly integrated with each other, which I think is an important thing to remember, you know, just before we kind of go to our lightning round here, uh, you know, we talked about the sort of the library analogy and obviously these five rules, which are awesome. And folks should go, uh, check out your blog post to learn and more and read up more on this, you know, library science specifically, right? Is there anything from library science, which is sort of outside of these five laws that we should be taking more to heart when we think about our data?
Amalia Child [00:48:13.150] That's a great question. You might have stumped me. Let me think.
Tim Gasper [00:48:19.690] I just think there's these there's all these skill sets you know across a lot of different disciplines but certainly library science is one of those where these arts are sometimes thought through a pretty niche lens but they shouldn't be right like uh i'll pick something a little too technical i think but like classifications and and and schemes around classification right Right. We think, oh, wow, that's so like that's so specific. It's like, well, isn't like kind of everything that we're trying to do around curation and around, you know, identifying things isn't at all a classification problem. Like, why don't why aren't there more people that understand the best practices of classification instead of just making it up? Like there's way too much making it up when it comes to these types of things going on in the industry right now.
Amalia Child [00:49:08.150] Yeah, I think that's a good example. And I feel like things like sort of taxonomies and tags and data catalogs are underutilized. But so that's a great one. And I think I've landed as well on sort of information literacy. And we talk a lot about data literacy. And I sometimes sort of tease them, and I did in the essay, into sort of numeracy and information literacy. I'm not in the weeds of that conversation. But there are folks who specialize in information literacy and in library and information science in particular. Laura Saunders at Simmons, where I went to school, is a specialist in that and could be interesting as a guest not to spoil my... I have a different recommendation from your last question. So that's another area where it feels like both let's not reinvent the wheel, not that we are. I think there are data literacy specialists who probably have a lot to add to this conversation too. But... I would love to see a little more collapsing of the distinction between data sources and information sources, I think, might be what I would say. As a research team, we did a lot of work in data, but we didn't sort of distinguish between qualitative and quantitative research in that environment. The way that once I joined a data team, it sort of, it felt like sometimes it fell off our radar to think about all of the different information flows that were happening alongside the data.
Tim Gasper [00:50:33.714] Yeah, I don't think that data organizations really, I mean, like people will say that they understand, but I don't know that they really understand some of these different levels of the layer cake that you're talking about, kind of like data information, like, like, like, there's these layers. And I don't know, I feel like everyone tends to kind of muddle them together in the data space. So like, I like your distinction here around like the data, like data versus information.
Amalia Child [00:51:05.154] Yeah, I think in practice, a lot of people are dabbling across that spectrum and just might not have plugged it into a framework for themselves, right? Like people are working in information who are working in data.
Juan Sequeda [00:51:19.414] There's so much to read, so much stuff to go learn about this. Yeah. Thank you so much. We got to go do let's do our lightning round yeah all right i got it number one do we need library scientists on our data teams?
Amalia Child [00:51:32.094] I think or is it lightning round uh yeah why not consider it, consider how they might plug in.
Tim Gasper [00:51:42.914] Yeah love it um second lightning round question where do you feel, this is actually going to be an open-ended one. Where do you feel is the biggest disconnect between the library analogy and data?
Tim Gasper [00:52:02.634] The analogy? I think... Probably when you start thinking about data products and data teams as producers. Librarians are researchers often and might consider themselves producers in some ways. But I think that is probably the area that I've struggled most to sort of complete the overlap. And I think, again, they're complementary, but that's probably.
Tim Gasper [00:52:32.354] The people writing the books live in the library.
Amalia Child 00:52:36.314] Right. Yeah, exactly. Something like that. Yeah. And like, yeah, I think often of like analysts as sort of journalists, working sources and directing attention and getting scoops and things like that. And yeah, that doesn't feel as much like, yeah, and data scientists sort of have a different profile. So as insofar as they are data producers, I think of that as a distinct thing. But I also think, you know, data scientists and analysts often wear that data manager hat and function as librarians in some ways, too.
Juan Sequeda [00:53:04.974] All right, next question. Can we think of knowledge and data in the same way?
Amalia Child [00:53:12.034] In the same way? How do you mean?
Juan Sequeda [00:53:16.634] Well, I think it's the way we, let's say the way we manage data and manage knowledge, are those, can we do this in the same way or like very different approaches and different tools and technologies and approaches and systems and processes and people?
Amalia Child [00:53:33.754] So, okay, I'm going to spoil my second recommendation for who to talk to next. I think there's, I think data management is sort of like a form of knowledge management. Yeah. That's sort of how I see it. Stan Garfield, I think, would be a fun guest on this show. I don't know if you know him, but he's a leader in the knowledge management field. And I would love his take on how to enrich a data catalog and get adoption and engagement with metadata and all of that. So that'll be my cop-out answer.
Tim Gasper [00:54:06.354] This is an interesting statement to me. I know we're out of time to unpack it today, but data management is a form of knowledge management. I want to unpack that at some point.
Amalia Child [00:54:19.074] Yeah, sounds good. I'll think about it some more and we can catch up on it another time.
Juan Sequeda [00:54:22.394] We have this book. I mean, it's on my read. Making Knowledge Management Clickable by Hilder and Waltz. Joe Hilder was on the guest before. But there's so much knowledge management.
Amalia Child [00:54:38.394] I just think you're defining concepts and and modeling the data to represent those concepts it feels like you're capturing knowledge at that point and then gathering information about you know it just yeah
Tim Gasper [00:54:48.734] Knowledge management has been too relegated to this idea of like uh you know uh yeah structured and cms's and you know things like that you know um but anyways we digress all right final lightning round question um in the data world right we've got like things like stewards, owners, curators, ambassadors, subject matter experts, therapists, right? Yeah, whatever, right? We got these different roles. Does library science inform something about which of these roles are the right ones?
Amalia Child [00:55:33.374] That's a good question. Sorry
Tim Gasper [00:55:41.694] No no you're fine you're fine
Amalia Child [00:55:46.714] Which ones are the right ones...
Tim Gasper [00:55:46.714] Maybe the answer is no i don't know i think
Amalia Child [00:55:48.414] I just need to think about it some more that's a complicated question,
Tim Gasper [00:55:52.354] Well that's fair yeah
Amalia Child [00:55:55.374] I'm gonna take that one i'll find you on linkedin or something
Tim Gasper [00:56:00.574] All right no that's fine interesting question yeah all right there's so much disparity across the landscape as the like what what do we call our data roles right
Amalia Child [00:56:08.794] I know i i think the thing Something I'll say that's been sort of reverberating in my head this summer is that it feels sometimes like the librarian role integrates a number of different hats or roles that data teams have specialized in a way, particularly around data management versus governance and analytics, I think. But I'll take that one to sleep on.
Tim Gasper [00:56:38.902] No, that's fair. It's possible that the data librarian is an underappreciated role. Term. Yeah.
Juan Sequeda [00:56:47.642] All right. Tim, take us away with your takeaways. We took so many notes.
Tim Gasper [00:56:55.502] We took so many notes.... Listeners, we're screwed. We're screwed. We took too many notes. We're too excited. We got too excited here. All right, I'll do my best. So takeaways, um, you know, you started with, um, with talking about Ranganathan and, and what he wrote right around, uh, around being this sort of reluctant librarian and trying to change the way that changed the perspective around how we build libraries and how they actually have value for organization, well, for the world, right. For the communities that they serve in for the world. Um, and you kind of kind of contrast it like medieval times, right? The books were chained to the shelves. Now you got the printing press, you've got democratization of books, the price of a book is coming way down. You can have lots of copies of books. Books were becoming democratized, right? And communities wanted to boost literacy. They wanted to improve the access to the books. They wanted to provide education and economic returns and social returns and sound familiar. We want to do some similar stuff like that around our data and knowledge within our organizations. And so he wrote about these five laws, which you expertly adapted in your post to the world of data. And the first one is books are for use, right? The point of these books is for it to be used, which, you know, wasn't, wasn't obvious at the time, right? It's obvious now that books are for use. Data is for use. Mostly obvious, not always obvious, more for some organizations than others, right? But isn't the goal to take data and empower the organization with that data and knowledge? And the answer should be yes. And you provided this kind of analogy around the library where, you know, the library is there to provide books to the community. There are certain decisions you make to improve the access to books. For example, you don't put it on the high hill far from town just because it looks pretty, right? You put it in the center of town and you make sure that it's got, got a nice big door and it looks welcoming and it's got places to sit and ways to enjoy and be social. So this is all part of that democratized experience around books, around data. We talked about reference interviews. And really, the phrase I wrote down was get to know your data patrons, really get to know the folks that want to leverage this data. And that's going to help you learn return emphasis on trust, emphasis on empathy. You mentioned, obviously, you have to meet legal and ethical standards. So that's an important part around data. But you know, where you have to meet those things, meet people where they are, for example, if they want to be in Excel, find a way to collaborate around Excel. Law two, was sort of the the flip side of that, right? Where, you know, if the first one is data for everyone, it's, you know, law two is everybody to their data sets. Right. Um, and this is really thinking about how these different personas they exist, right? You're not just going to dump all the books in the center of the room or have these free use libraries that hang out in the corner of the street. There's a fit for purpose aspect of what you're trying to do around data and around how you're curating and managing the library. And, uh, we talked about, um. How this scales and how you scale this sort of specialization. It's this hub and spoke model, right? And as you scale, you have to have sort of the central library and the branches and there's specializations that happen and some books you want to have shared across organizations and some you want to be specialized and crap, we've been doing data meshes for over 400 years. And we think this is so novel. So, you know, it's just cool to see these parallels. I think it helps us to learn and borrow what works and what has been established and also appreciate where some of the differences are. Oh, so many other things I could say, but Juan, what are your takeaways?
Juan Sequeda [01:00:58.502] So let's go, law number three, every book gets reader and every data sets its stakeholder, which means that we really have that education, that marketing and the outreach. Not everyone is going to know what is out there to get that data. There will be the folks that you may think about it, build it and they will come and that does apply to the folks like I need this, I can go run. To it but there's also probably people who have no idea about that you need to go be able to go reach out to them so you can understand that understand who they are and everyone has an entry a point of entry we need to be able to come on board folks um but at the same time like hey if you're doing all this stuff and having office hours nobody's coming just cancel them like we have to go through that whole life science that life that that life cycle the weeding right it's time to archive it it's a just part of the process and and there's this misconception exception librarians archivists are not hoarders they're actually being very strategic there's some things that you do need to keep track of auditors will come and then you'll need to have that balance of does this bring me joy or thank you for your service right um we have we should also be very proactive with the community the stakeholders i mean hey i'm reaching back to you because i know that you're interested in this and i found this this is maybe of your interest, and um we want to get them in just like the analogy of the libraries is like at the entrance you have all these newspapers and the stuff that you're looking to read day to day like get them them in with the, with that fun, easy data stuff that resonates with. Then the fourth law is save the time, the stakeholder and reader. So people need things quickly. That's why we want to have a lot of self-service and the self-checkouts and innovative signs and color coding. People can understand this, right? Ebooks with content network for fast digital access. So I think that's one of the things that we want to make it easy and make it fast, but also know that with self-service, we will hit a limit. So once you hit that limit, you want to be able to have access to those data teams, those librarians who will help you when you go to hit that limit. it. And saving time is also meaning about meeting people where they're at. And I think the analogy with the bookmobiles was like, you want to be able to deliver materials to folks who have requested it, some curate a collection for a community, give access to folks who don't go to the library. And it's also a marketing term. So the analogy here too is like, hey, somebody is doing something with data or they're doing it in their Excel approach. Well, meet them where they are, go solution with them in Excel and understand what they're doing and how they're doing that. Maybe that's something that you can go apply and improve on your library site, on your central site, wherever, be able to go help them back later on. So don't alienate them. And finally, the fifth law is if you follow those first four laws, your library data function will grow. This is exciting, but it's going to be daunting. So it means basically price of success. So you need to know how to negotiate your boundaries, your scope, but better than no one engaging with all that data. Then finally kind of close up with saying hey what else should we be taking about library sciences and there's the whole area about like classification taxonomies it's all about information literacy i need to dive into more into that like this difference between data sources and information sources and kind of what is quantitative and qualitative and i mean i think we're just barely scratching the surface here what we've discussed uh how did we do anything we missed?
Amalia Child [01:03:58.135] No sounds good
Juan Sequeda [01:04:04.052] All right. Well, you already told us who you want to invite next. What's your advice and what resources do you follow?
Amalia Child [01:04:10.152] Okay. Two pieces of advice. One came from this exercise, which is like read the whole book. It's never served me wrong to just actually go read the whole book and do that homework. And a lot of like historical and technical books tend to be, I'm sorry, the light in my house is shifting. Historical and technical books tend to be more entertaining and have like more personality than you'd expect. And this is one example of those. And then my other piece of advice is more life advice. And all my friends, if they listen to this, will laugh at me, but try weightlifting if you haven't already. I'm doing it to prevent osteoporosis, honestly.
Juan Sequeda [01:04:42.312] Try weightlifting? Yeah. That's where I'm late. I need to go to my gym right now to go do that.
Amalia Child [01:04:52.232] And then resources. I want to plug Locally Optimistic. I appreciate them having hosted my essay. And I also think they have a pretty great evergreen collection of career development and leadership type of posts as well. Really great content. Great stuff. Great editors. And then for weightlifting resources, I use the RISE program and can't recommend it enough, but so I'm an evangelist for it.
Juan Sequeda [01:05:17.852] Fantastic. Well, Amalia, thank you so much. This has been eye opening and hopefully everybody who's been listening here, we're blowing people's mind. thank you i really appreciate it
Amalia Child [01:05:30.212] Thanks so much for having me
Juan Sequeda [01:05:33.592] All right cheers everybody cheers everyone.
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