Alter Everything

MaddieJ · ‎05-23-2022

Analytics on a helicopter? Predicting crime before it happens? Data really is everywhere! Alteryx associates Dr. Erica Reuter and Sergeant Melanie Goulette join us to share how they used analytics in their past lives in the U.S. Military and law enforcement to make an impact in their communities. They also share cybersecurity tips, and have a discussion about how important it is to avoid bias in your data analysis.

Panelists

Will Machin - @WillM, LinkedIn
Dr. Erica Reuter - @EricaR, LinkedIn
Sergeant Melanie Goulette - @M_Goulette, LinkedIn

Topics

2022 LinkedIn.png

Transcript

Episode Transcription

MADDIE 00:01	Welcome to Alter Everything, a podcast about data science and analytics culture. Today, we're going to talk about how data is used in law enforcement and in the military. [music] Our first guest is Sergeant Melanie Goulette, an intel analyst with over six years of experience in the US military and is now a sales engineer at Alteryx.
MELANIE 00:21	And here I am. I'm on a helicopter. I have an interpreter. He's telling me what these people on the ground are saying. I'm able to locate them, and I tell the pilots where these locations are at, slew your cameras, all this stuff is going on. And at the end, I'm the one that has to parse out the data. I'm the one that has to remember everything that happened. I have to take notes while I'm in a helicopter.
MADDIE 00:45	You'll also hear from Doctor Erica Reuter, sales engineering manager at Alteryx, with a background in managing a police department intel unit.
ERICA 00:54	When you watch The Sopranos on TV, and you see those charts with all the strings attaching people, and you get the organization of the crime family that way, you do that with technology now.
MADDIE 01:05	And finally, our guest host today is Will Machin, team lead for community management at Alteryx.
WILL 01:12	You're both [inaudible] rad, and it's really awesome to work [laughter] with you, and I hope we can bleep that out, because I'm sorry, I curse like a sailor, [laughter] and I think I did this in the last episode, too.
MADDIE 01:21	While this conversation focuses on the experiences of two United States citizens, our global audience will also benefit from their tips for how to keep your data and the data you work with safe, as well as important reminders of how bias can harm your analysis. Let's get started. [music]
WILL 01:45	Awesome. Hi, my name is Will Machin. I am a team lead for community management here at Alteryx, and I am guest hosting today's episode. We are very lucky to have Erica and Melanie here with us today.
ERICA 01:58	Will, so, technically, Doctor Reuter and Sergeant Goulette, if you want to be fancy, because I know you're very sensitive about your last name and--
WILL 02:07	I am. It's very true.
ERICA 02:08	--credit.
WILL 02:09	Much appreciated. Today we have Doctor Reuter and Sergeant Goulette with us to talk about a topic that I think is really interesting. We're going to be talking about public sector usage of Alteryx. And a lot of times, our products are often thought about as positioned in the finance industry or just kind of business analytics, but there's so much more depth to the uses that you can have. And you all have some really, really fantastic experience and information about it that I think is just going to be very interesting for everyone to hear. So, with that, I will let you all go ahead and introduce yourselves to give a little more background and in a far more appropriate fashion than I would be able to.
MELANIE 02:47	Well, thank you, Will, for the introduction. My name is Melanie Goulette, aka Sergeant Goulette. I have been in the military for almost six years as an intel analyst. I'm in the Army National Guard. And so my full-time job used to be a geospatial analyst as a contractor for the Department of Defense. And then, way before that, I was also a teacher for the military. So those are kind of my three main gigs, you could say. I just joined Alteryx back in November, and I am a public sector sales engineer. I work for Erica. I'm very excited to be here. This is all new to me, and I feel like a fish out of water, but it's in the best way possible.
ERICA 03:32	I really should have gone first because she's a tough act to follow. But my name is Erica Reuter, and I used to manage an intelligence unit for a police department. I had a lot of roles in law enforcement because they like to rotate us around a bit. But in the end of my career, I was doing intel work and helping support our investigators, our detectives with capturing bad guys. Towards the end, it kind of got to the point where the industry wasn't satisfied with capturing bad guys. We wanted to stop people from being victimized in the first place. So we started dabbling into predictive analytics and trying to figure out like, "Hey, how can we kind of just be in the right place at the right time as much as possible and get some things and stop people from having to go through some terrible ordeals?" So I learned how to do that, and then I got recruited by the tech world to teach other departments how to do the same sort of thing. And now, here we are at Alteryx where we're sort of continuing to work in the state, local, education, and federal sectors. So super excited to talk to you about our personal experiences, what we've seen other people do, and the intersection between technology and public safety because it's a fascinating field.
WILL 04:46	It really is. And just in some of the prep calls that we've done for this episode, it's just kind of shed a huge amount of light on like, "Oh, there are capabilities far beyond what I'd even thought of," like working with a lot of our customers and community. So, Melanie, can you share with us a little bit how analytics and data is used within the military space, in general?
MELANIE 05:07	Yeah. And that's a huge subject, especially with the military as a whole. It's kind of hard to know where to start because really, the whole entire military relies on big data, anything from administrative, budget, finance, personnel, supply, logistics. Everything relies on data management. I come from the operational side, which definitely relies on data, but it's less of a big data picture and more of a specific. So, if we have a specific target, we need things or information on just that target. And so the challenge is finding all of those sources of data. So, there, we have this volume issue. We have these systems issues where they don't talk to each other. And then, on the operational side, it takes so long to find that information. So, really, from top to bottom, left to right, the military is just driven by data.
WILL 06:11	That's really interesting. We're talking about big data, and that's something that has been such a buzzword for such a long time. But I think it's a really cool contrast there to talk about how the small data is also really important, especially when looking for a specific target or a specific instance. Do you have any stories or examples that you're able to share about that? Is that all kind of redacted at this point? [laughter]
MELANIE 06:34	Well, I did deploy to Afghanistan in 2018 and '19, and obviously, that era has kind of concluded. And so it's not that it's so sensitive anymore, but when I was there, I was an all-source analyst or am an all-source analyst in the military. And so we're kind of known for being PowerPoint rangers. We take everybody else's information, and we compile it into PowerPoint reports. And we're aware of that. We know our reputation. But I had a very different experience in Afghanistan. I had a very small section that I worked in. My captain was very proactive. He was very passionate about intel, and he was also an Apache pilot. So my unit is an Apache unit, and he was just balls to the wall all the time. And so, when we got to Afghanistan, he said, "We're not just going to sit around and be PowerPoint rangers. We're going to figure out how to affect this war." Because Afghanistan was known as the 21-year war, essentially. So, every time there's a new administration that would come, a new leadership, they would restart the strategy. So we got to Afghanistan, and we're like, "How do we fight this war? What do we do?" And so we kind of pioneered a new intelligence collection method while I was there. We took what's called a V rod, which is basically an antenna that collects push to talk, so like radio traffic. So it could be similar to a police radio here where people listen in on it. So we took this machine that people would use to listen to radio traffic, and we attached it to a helicopter. So we attached it to the outside of a Black Hawk. And what we would do is, we would take these full-on helicopter assault packages, usually called a half helicopter assault force, and what we did is called it a false half. So we would take two Chinooks, two Apaches, two Black Hawks. One of the Black Hawks would have this machine on it. And we would fly over a village that was supposed to be a Taliban village, pretending like we were going to insert a team to conduct an assault. But really, what we were doing is flying around, taking video, and listening to these radios to see what their reaction would be.
MELANIE 08:49	So what we were able to do is identify when people on the ground identified the helicopters, identified which direction they were going, and communicated that to the village. By the time we would get to the village, they would already know we're coming, and then we would be able to see how many people there were, what weapons they had, where did they go when they thought a helicopter assault force was coming? And so this really filled in a lot of the gaps that they needed to kind of conduct some of the more off-hand's targeting, like striking, basically. So, in the process of that, we realized that there's so much information here, and we don't know what to do with it. We're just all-source analysts. We're just PowerPoint rangers. And here I am, I'm on a helicopter. I have an interpreter. He's telling me what these people on the ground are saying. I'm able to locate them, and I tell the pilots where these locations are at, slew your cameras, all this stuff is going on. And at the end, I'm the one that has to parse out the data. I'm the one that has to remember everything that happened. I have to take notes while I'm in a helicopter, and I have to get in touch with this interpreter, who it's probably not easy to get a hold of, and see if he can go through the tapes again and all that kind of stuff. So, really, it came down to just me and the couple people I had around me to figure out trends, to analyze what these people were saying, and when and how that correlated to the assault force and all this stuff. So it was just a lot. It's a lot of information. And that's on the operational side, which is small data. It's not even big data. It's just, there's no way to really catalog this, analyze it, look for anomalies, changes, that kind of stuff. So, long story, short--
ERICA 10:35	Is there no way? [laughter] There's a way.
MELANIE 10:37	But there is a way. [laughter] And I didn't know that. And so, when I went to interview with Alteryx and create my demo, I was like, "Holy cow. Where has this been my whole life, this product, this program?" Honestly, I was like, "I could see this being used in so many different ways on the operational side." So that's my Alteryx plug.
WILL 11:00	I love that. That's so cool.
MELANIE 11:00	That was a good story. [laughter]
WILL 11:02	I mean, talk about learning on the fly, quite literally, when you're expecting to be a PowerPoint ranger, like you said, and then you're in a helicopter in kind of a live situation that provides safety for God knows how many people and helps every aspect of the tactical deployments and everything. That's incredible. Okay. So, switching sides a little bit here, Erica, can you share a little bit how analytics and data can be used within the law enforcement space, specifically?
ERICA 11:33	Yeah. But it's going to seem so boring now. Yeah. We use analytics a lot. And you can think about all kinds of different aspects of crime, different aspects of society. If you think of drugs, for example, I'm super passionate about narcotics investigations. I'm super passionate about the war on drugs. I know, Nancy Reagan, whatever, but people die. And I think all of us probably know someone within one degree, if not two, who've had their lives destroyed by drugs. So the thing about it is, drugs are a business, right. And there's data behind every single business. And when it comes to things like this, it's not necessarily about making an arrest. We could arrest someone and take them off the street, and that's great. And then they bond out, and then they go back to doing their thing tomorrow. That's fine. Really, what it's about is shutting that business down, setting up a RICO investigation, seizing all those assets, taking all their money, getting them to the point where they cannot start that business back up again. And that comes down to data. You have to be able to prove that it's a business, so doing things like network analysis. And when you watch The Sopranos on TV, and you see those charts with all the strings attaching people, and you get the organization of the crime family that way, we do that with technology now, and we do that with drugs, and we do that with burglary rings, and we do that with all things like that. When we're looking at social media, when we're looking at financial data and money laundering, there's just so much that goes on right now that crime is so much more organized than it used to be. And people who are committing crimes are so much smarter, I mean, maybe not smarter. I guess criminals have always been smart. Society has always been smart. But it's evolved. And now, there's just so many high-tech ways to do crime. And there's just such a digital footprint in everything we do. So the intersection is pretty natural, and the work that's being done blows my mind. I don't know how people could think they're going to get away with anything anymore because there's such a digital footprint in our lives. It's very hard to not have a trace of where you've been and what you've been doing.
WILL 13:41	Yeah. It's interesting you say that because it's such a voluntary digital footprint as well. People opt into everything, like every app we download. So thank you guys so much for going into a little more detail there. I think that both of those stories are really, really cool. And Erica is saying that's boring. I think not, because you're right, I think all of us at some point or another have had some kind of experience with someone we know that has been super-negatively affected in some aspect of their lives due to drugs and everything. And so, the ability to kind of go in and look at that, like you said, not from an individual kind of bad actor, but looking at it more as an organizational kind of attack and problem, is really a much stronger way to go about it. So I think that's a really, really great perspective. So we've got a little bit of details about both of your background and kind of some of the things you've done there. One of the things we've heard about a huge amount recently in the news and with coworkers, friends on Twitter, on Facebook, on whatever social media you're on, is cybersecurity. And so do either of you have any kind of general, quick tips for our audience about their personal data, the data they work with to make sure it's secure, to make sure that people are being safe and making kind of informed, intelligent decisions whenever they're dealing with those things?
ERICA 15:07	We have a little saying around here, "Dance like nobody's watching. Encrypt like everyone is."
WILL 15:12	Ooh, I love that. [laughter]
ERICA 15:14	So encryption is always huge, right, and just understanding that nothing's ever private and being very careful and checking, naturally, the sources of the emails that are coming in to you and things of that nature. Melanie is actually getting her master's in cyber, so I'm sure she's got a lot to say on the topic.
MELANIE 15:31	Yeah. I know a lot about law and policy and the disconnect between public and private sector and cybersecurity if you ever want to chat about it. But actually, this is kind of something that I'm a bit passionate about when it comes to my military peeps. I have to kind of plug here for them because I've seen, a few more times than I'd like to admit, people putting our soldiers at risk by what they post on social media. It doesn't matter what platform it is. If you're posting about troops traveling or posting pictures, their location is attached to that most likely, and you don't even know it. And so I understand the desire to be proud of your soldier, marine, airman, whoever it is, but you could be putting them at risk. And so that's something that hits very close to home for me, just having seen some of the effects of that loose information out there. So I would just say be careful. Definitely be proud, but maybe wait till your soldier gets home, or just keep it within family, off of social media, and stuff like that. But I mean, other cyber tips, you just can't be too careful. Also, when you get your own modem, router, whatever it is at home, change the admin password. A lot of people, I feel like, don't do that for some reason, and it is the easiest way to get into your home network where you're using your banking information, all your passwords are stored, your phone is connected to it, your cameras are connected to it. Just be safe. Change those passwords.
WILL 17:05	Use a password manager. [laughter] So I know that we have chatted a little bit previously about this, but crypto and blockchain is always a huge talking point at this point. Everyone thinks it's absolutely secure, and no matter what they do, they're going to be fine. But I know that you have a story that kind of shows that may not be the case, necessarily, and some steps that might be able to be taken to rectify something when it does happen.
ERICA 17:32	So I am far from a blockchain expert, right. I'm sure when I tell the story, you all who know about blockchain are going to be like, "That's not exactly right," but the essence should come through.
WILL 17:42	Oh, I don't even know what an NFT is right now, so I'm not going to be the one to call you out.
ERICA 17:45	Right. [laughter] So there is a guy that works with Melanie and I, and he's my favorite kind of technical person, in that, he's sneaky smart. You know those people that you talk to them, and they're just totally normal, and then, after a while, you're like, "Oh, you're smart. I had no idea because you seem so normal." So, anyway, he invests in crypto, and he invested in a crypto project. And the way he explained it to me was, developers make projects where maybe they're making a new coin, or maybe they're making a new security feature, or things like that. And then they put it out, and then people can buy into the project as investors, just like you would a stock, right. But you're buying it, and it's on the blockchain, and you can see all the transactions of everyone who's bought and sold their interest in these projects. So he buys into it. He knows it's a risky one, but it's doing well, so he's happy about it. All right. So, then, a little bit later, the developers reach out to everyone, and they're like, "We got hacked. All your money is gone. I'm so sorry." This is kind of the risk of blockchain. It's unregulated. It's on the internet, and things happen. So he's like, "Oh, we got hacked. That sucks. All of our money is gone." But our associate was like, "Not today. You messed with the wrong person. This seems suspicious." So he actually used Alteryx, a little gentle plug here, and he got an API to get every single transaction on the blockchain, right, which is like millions. It's impossible to just look through this and find patterns. And he basically found that the developers of the project were slowly siphoning money, like 5, 10, 15 dollars at a time through an anonymizer into their own wallet on the other end. So they kind of just made a bunch of transactions and pocketed all the money, and then called it a hack. And they sort of just hacked themselves and drained the account. So he's like, "I got you." He was real proud of himself. And he called his friend at the FBI, and he's like, "Hey, look what I found. Blah, blah." They've opened an investigation. So, hopefully, we'll see some justice, and people like this can't continue to do this to people because whatever, we don't like people like that. Why can't everyone--
WILL 19:51	No.
ERICA 19:52	--just be nice?
WILL 19:53	Well, I mean, I think nice is overrated, but kind is not overrated, necessarily.
ERICA 19:58	Not devious.
WILL 19:58	But that's a different subject.
ERICA 20:00	Yeah. That's a subject for another episode.
WILL 20:01	Exactly. But what I've learned from this is, make friends with someone at the FBI. So, if I do need to call them, [laughter] I know who to call.
MELANIE 20:09	That's a great point, Will. Yeah. I think that's the key takeaway here.
ERICA 20:12	I feel like they have other channels, but yeah.
WILL 20:15	I mean, I would assume so. [laughter] So that's such a cool story. And I think it's such a really interesting point and perspective on being able to kind of do your own work sometimes to get the ball rolling when something's happened. And sometimes, you have to take those first couple of steps yourself, and then, having that kind of literacy and knowledge can really help that. Even if it's not as advanced as what he did, necessarily, just being able to do some investigation and everything like that can be super helpful.
ERICA 20:44	Honestly, what he did, though, it just took him a few hours. All he had to do was download all the transactions, and then say, "Hey, computer, show me anything where there's a lot going between more than one account. Find the pattern for me." That's it, just a little, "Hey, computer, figure it out." So it's not as hard as people think it is. Sometimes, it is. I'm not going to say it's always super easy, but in some cases, it's really not that bad. Definitely worth dipping your toe into.
WILL 21:10	Yeah. And it's pretty crazy. We, essentially, legitimately live in the future now with the way that data and technology and everything is just so easy and accessible, which kind of leads me into my next question for you all. Are there any specific initiatives that you guys are working on within public sector to really help with kind of the betterment of the sector, in general? Because I think a lot of times, people think of data and technology working together to be kind of scary, or it's, "Big brother is going to watch us," but there's so much good that can come out of it, too. And I think that you two would be perfect to share some examples of that.
MELANIE 21:44	Yeah. And so I'll start on that. Erica might have some more to add. But really, what we kind of want to focus on is like health system integration.
ERICA 21:56	Basically, it's an alliance between the military, academic resources, major universities, and technology vendors. And we're all coming together to kind of research how we can help integrate data for war fighters to give a good continuity of care and get all these systems better integrated, so we have a more holistic view of what they need when they need something. And I'm sure Melanie could speak a little bit better, more intelligently than I, as to why there is a gap there.
MELANIE 22:25	Yeah. So, before you join the service, there's the MEPS program that you have to go through. While you're in the service, you either have care provided by the military if you're on active-duty orders, or if you are Garda Reserve, then you have TRICARE Reserve Select, and then you have your choice of providers. And then, when you go to get out of the military, you have your healthcare, post-military. You have the disability system. And none of those systems talk to each other. So you have to take everything from one system, get the reports, and physically give it to somebody in the next system. There's just no continuity there. And a lot of times, it ends up with gaps in care. And that's what I've seen a lot around here, especially where I live. There's a huge veteran community, and there's gaps in care, and they may not know how to fix that or how to go about getting that care that they need. So, if we can start to solve that problem, where these different systems are talking to each other, and it's not on the veteran to go figure out what to do-- well, I mean, part of it is on them, but also, we should be taking care of them. The military, the government should be taking care of them. And so I think if we can start to head in that direction, that we can make some big changes there.
WILL 23:50	I think that's hugely important. I used to live in DC and just was pretty involved for a while with the veteran community, and it is such a huge issue. These are not exactly super-transparent policies. I mean, even standard healthcare stuff, you try to figure out, and I have no idea. I have to call Cigna on a regular basis. So, when you're switching between programs, and the government's involved as well, it becomes pretty obtuse to try to navigate. So the fact that there is some way, or you guys are working on something that can help with those transitions is a massive improvement, I would say, already. I mean, I'm really excited to hear and see where that goes as well in the future because it's something that affects a large number of people that may not necessarily have the resources to hire out for help sometimes or know who to even reach out to for help, occasionally, because calling a call center is not always going to fix that problem for you. So what else would you guys want our listeners to understand about the use of data and analytics from a safety perspective? We always talk about how data literacy is really important, and that the ethical usage of data is really important, and bias is a big conversation right now. And I think that that could be something that's looked at because people always think of data as just black and white. So there's no bias. But collection of data can include bias, like reporting of it, and how it's presented can also show that. And so we'd love to hear your perspective on that, about that usage in the public sector and just kind of from a safety perspective, in general.
ERICA 25:24	Yeah. Unfortunately, bias is a real thing. And technology reflects society. It doesn't invent the bias. In some cases, it inadvertently compounds it. But what we like to try to do is really just look out for that and try to make sure that we're validating things and trying to make sure that any data that's being collected, that it's necessary. If we're doing a particular thing where we're trying to figure out crime patterns, race isn't going to have anything to do with that. There's no need to even include that variable. Let's just take that out, right. Gender is not going to have anything to do with that. Religion, sexual orientation, any of that stuff doesn't matter. That's not going to change the fact pattern. So it's always good to take those things out in your analysis unless they're going to inform something. The other important thing to remember is, any action anyone takes, the computer doesn't make them take that action, right. You need probable cause to arrest someone. You can't just go and arrest someone because the computer said they probably did it, right. The computer is an investigative tool to help us be a little more efficient in our processes and to think and to understand and to make sure we didn't miss anything. But we, as humans, still have a responsibility to do our due diligence, to do a good investigation, to make sure that we truly can defend our recommendations and our analysis that we're putting forward. So I wish bias wasn't a thing. It has been since the beginning of time, as far as I know. And it's up to us as humans in partnership with what we're getting from the computer to make sure that we feel good about how we're using that data, how we're presenting it, and how we're going about that collection and doing the best we can to control for it.
MELANIE 27:13	Yeah. So, just to kind of add a little bit onto that, I think Erica nailed it, but when looking at the operational side where I come from and small data, bias is huge in that process. If you're relying on one or two individual analysts, and there's no system to kind of check that bias, then the end product is part of that. [laughter] Yeah. Their views on the world will come through in that. And so that's not good for anybody, especially the end user of that information. There's Americans on the ground using this intelligence to conduct operations. So, if an analyst doesn't recognize their bias or even the fact that bias exists, that's a problem. And so, having a tool like Alteryx where you completely take that out, like Erica was saying, there's factors that just don't need to be taken into account. So, from my point of view, that's where I would say bias comes into play.
WILL 28:13	Well, and I think it's something-- just this whole conversation is like, any human interaction, there's going to be bias present. And I think just kind of recognizing that that bias is going to be there, whether it's positive or negative, it's part of it. And so trying to remove that is essentially impossible from your interactions. But being able to remove it when you're analyzing something is really important as well, where you can say like, "Okay. There was bias here, but let's try to take that out," when we're looking at kind of the actual data and the results of an interaction of whatever kind it is.
ERICA 28:47	It can affect your sample, right. So, sometimes, it's impossible to take it out. "I wish they had patrolled a larger area. I wish they weren't only looking at this neighborhood. I wish they weren't only looking at this group of people." It is tough when that goes in. I don't want to acknowledge that doesn't exist. But again, that's where we as humans have to step in and just make sure that it's fair.
WILL 29:08	Yeah. Try to neutralize as much as possible, realizing that it's not a perfect system. Because life is not a perfect system, but we can do what we can to make it as close to that as we can. So I am fascinated by all of this work and your stories that you all have shared. I think it's really cool to think about kind of the big data, the small data, the art of the possible. So this is something that I think we're going to intersect on a little bit, even though I have already been chided for not listening to Serial yet. But Erica, I know that you're a huge true crime fan. Can you share some of the side projects and use cases that you have worked on in the area?
ERICA 29:42	Yes. So I'm a total nerd, and my work is also my hobby. So, sometimes, I like to just kind of go and think about, "Hey, if crimes happened today, could I have solved them?" right, or, "Could someone have solved them?" or, "What would it have looked like in today's environment with these great technological advantages that didn't exist in the past?" So there's a good Netflix special, or there was, on Ted Bundy. Did you guys happen to see that? I think Zac Efron was playing Ted Bundy, and they kind of just talked about it, and it was like, "Oh, Ted Bundy, right." So I was thinking about Ted Bundy and how many people he has killed, which is an insane amount of victims that Ted Bundy had over the span of years, and I was thinking, "Okay. Well, would he get away with that today?" Do you guys think he would get away with that today and have his spree go as long?
WILL 30:30	My guess would be no. Like you said--
ERICA 30:31	Why?
WILL 30:31	--digital footprints are a huge thing at this point.
ERICA 30:34	Exactly. I mean, he had that very distinctive car. He had that VW Bug. And there were descriptions, right. And there were witnesses. And it took them a while to figure out who he was. And then I started thinking, "Okay. We've got all these different crime scene locations, used the same car." We were talking about that podcast, My Favorite Murder, a little earlier. And I remember someone writing in and being like, "Oh, actually, I was in the car." They got away. They were one of the early escape victims. Yet, I digress. Sorry. Okay. So very distinctive car. And now, we have license plate readers all over the place, and we have traffic cameras all over the place. And that data is pretty public. So what I was able to do was scrape all of the crime scene locations and put them in chronological order, right, and then scrape from a map all of the locations of the red-light cameras and the license plate readers in Washington state and in Oregon because that's kind of where the early crimes occurred. And there was a description not too far into his spree. I think it was four or five crimes in when he hit the lake is when they really started to identify this car.
ERICA 31:40	And kind of what I was found was, hey, if you really, A, just looked at the cameras around these locations, you would see a similar car, right. We have the ability now to do image recognition and object detection, and we could actually go through and classify all the cars, right, and be like, "That's a Ford. That's a Bug. That's green. That's yellow." We would have seen a pattern of that car, or at least that very distinctive-looking car, that model being around all of these crimes. It would have been pretty, I don't want to say easy, but easier today to have gotten that vehicle description a little faster, just with all the technology that's around. The other thing is, okay, so, now, we've narrowed it down to this car, right. Now, we can look at those license plate readers and start to get those tags, right. Because eyewitnesses are somewhat unreliable. You see something crazy, whatever, getting a tag is not as common as one might think, but cameras get them. So it's quite possible with technology that we would have got there faster. And I just find that riveting. And again, the data [laughter] is on the internet. The analysis doesn't take programming like it used to, right. You could just sort of like, "Load this. Load this. Find commonalities," and the computer does it so fast. And I don't know. That's my favorite part of this job and of this world and of this life. And that's why it's a hobby. Because just having those moments of, "Oh, my gosh. Look at that. Look at what the computer found. And I pretty much just pointed it to it, and it put it all together," blows my mind every time. Every time it happens, it blows [laughter] my mind.
WILL 33:15	It kind of reminds me of, even like when they found the Golden State Killer a couple of years ago.
ERICA 33:21	The DNA.
WILL 33:21	My friend was in that Reddit community that had been doing a lot of the searches and sharing stories and everything and just that collaborative kind of-- even that just being a forum, technology allowing people to connect those dots, let alone using data mining and everything like that, to be able to fully connect dots more quickly. It is really kind of insane how much technology has allowed us to really step up on doing that. And you're right. I think it makes a huge impact on preventing kind of the sins of the past from occurring again.
ERICA 33:51	Serious hats off to those in the '70s during that time who didn't have it. I don't know how they solved anything. To me, they're super heroes. I have no idea how policing was done. No. That's not true. But definitely much harder. Definitely much harder. And you didn't have as many advantages as you have today.
MELANIE 34:09	I would be interested to see the difference between how long killing sprees used to go on versus now. Do we even have real serial killers now? I don't know.
ERICA 34:22	Funny, you should ask. I Googled that recently. I had the same question. And apparently, yeah, [laughter] there's a terrifying amount out there. But yeah, I don't know. I don't know, like longevity. That would be an interesting research project, right, to just sort of see how that's changed over time.
WILL 34:37	I mean, SVU will eventually run out of subject matter if they go away entirely. So we will be forced to just watch reruns, but I feel like that is a fair trade for the safety of the general public.
MELANIE 34:47	I agree. It's a great show.
ERICA 34:50	The SVU laundry stealers or some sort of real estate.
WILL 34:53	Right. Exactly. We'll just lower the stakes a little bit, [laughter] less murder and more petty crime.
ERICA 34:58	You stole my yogurt out of the community fridge.
WILL 35:00	Ooh, I like that. [laughter] And then I would like to follow up with one more question for you as well, Melanie. So your helicopter story that you shared was super impressive, especially when it's not necessarily what you're expecting to do when you first get there. Do you have any other stories about your time overseas?
ERICA 35:20	Bonus challenge, no PowerPoint in your story. [laughter] You're not allowed to say PowerPoint.
WILL 35:26	[inaudible].
MELANIE 35:27	That's a hard one.
ERICA 35:27	Got it? Okay. [laughter]
MELANIE 35:29	My brain just short-circuited there for a second. [laughter] Well, I will say that there is nothing like the first time you see camels running around in the wild. That is a trip. But no, see, a lot of my stories have to do with flying around in helicopters. I will say that Afghanistan is beautiful. It's just got this almost kind of melancholy feel to it where there's a sadness, but it's so beautiful. There's the red desert, the mountains. It's amazing. But yeah.
WILL 36:08	Also, I'm here for another helicopter story if you have one, too.
ERICA 36:12	Or gossip, military gossip, like who is--
MELANIE 36:15	Girl.
ERICA 36:16	--doing crazy things over there.
MELANIE 36:17	Girl.
WILL 36:18	Everyone [laughter] is doing crazy things over there.
MELANIE 36:19	It's insane. [laughter] It is the Wild West over there. So you know what? You've heard of drones. Obviously, everybody's heard of drones. There are ones, though, that are not remotely piloted. They actually have people in them. And so they're just small airplanes, all this equipment, whatever. I just happened to meet this guy at the gym or something, and he is an analyst for one of those reconnaissance aircraft. And I'm like, "Oh, that's cool. So what's it look like?" And so he's showing me all the parts on it, and he's telling me how to use them, and he's like, "Do you want to go on a ride?" And I was like, "Hell, yeah, I want to go on a ride." So this turned into me basically doing ISR collection in the airplane for five hours. You're just flying around so high that people can't even see you or hear you. And he let me control the cameras and stuff. And so doing that a few times was an incredible experience that is like nothing you will ever see again. It's incredible. But I saw wild horses when I was up there. Yeah. It's an incredible view of the world, I will say that.
ERICA 37:38	Do you feel different? Does your body feel different?
MELANIE 37:42	Not really. No, not really, but it's really loud. You can't hear anything. It's very peaceful. But other than that, anybody on this call who is a veteran who is deployed knows about The Green Bean, and that is a lifesaver. Getting a cappuccino at The Green Bean was a little piece of home, and I think that would resonate with a lot of people.
WILL 38:02	I can imagine that. Those little things that you take for granted here where we kind of have anything on demand become precious things over there when they're not readily available. So I would imagine that resonates with a lot of people. But honestly, getting to ride in a drone sounds incredible. I feel like they should sell rides like that in Vegas or something like that, but.
MELANIE 38:24	It was quite the experience. And I think what I learned from my time in Afghanistan is, look for reasons why you can do something or why you should do something. There's so many people out there that want to be so quick to say, "No. We can't do that," or, "That's not possible." Why? "Why is that not possible? Tell me why, or I'm going to go do it, because I know that I can do it." So that's just kind of a mantra I bring with me now.
WILL 38:51	I think that's such a good takeaway, in general. Don't cancel your own abilities before you figure out either why you can't do it or figure out a different way to approach something because a lot of it really is perspective in how to do that in the long run.
MELANIE 39:04	Yeah, for sure.
WILL 39:06	Awesome. Well, thank you both again for sharing that. I feel lame in comparison now, but I get to talk to awesome people like you all, so I will take that any day of the week.
ERICA 39:18	You're the best dressed of us.
MELANIE 39:21	Totally. Yeah. [laughter]
ERICA 39:23	Yeah. Exactly.
WILL 39:24	I just want to say, Sergeant Goulette, thank you for your service, and Doctor Reuter, thank you so much for everything that you've done as well. You're both [inaudible] rad, and it's really awesome to work with you, [laughter] and I hope we can bleep that out because I'm sorry I curse like a sailor, [laughter] and I think I did this in the last episode, too. But it's been an absolute pleasure speaking with you both today, and if there's anything else that you want to add as a wrap-up, please feel free to do so right now. I would like to cede the floor to both of you.
ERICA 39:50	Just share what you're doing. If anyone has anything, and they want to talk about, "Hey, is this possible?" oh my gosh, we love nerding out on that stuff. So, yes, we technically work in sales, but we're not commissioned sellers. We're solutioners, and we just like nerding out. So, if anyone has ever wanted to ping something on LinkedIn or send us a note to our email or our community profiles and be like, "What do you think of this?" trust me, we'll be like, "Oh, my gosh. That's so cool. You could do it this way. You could do it that way." We're all into the nerd-outs. [music]
MADDIE 40:26	Thanks for listening. For more on the projects mentioned by Erica and Melanie or to just nerd out with them about all things Alteryx, check out our show notes at community.alteryx.com/podcast. And if you've never stopped by our online community, please come join us. We have over 300,000 members from around the world that love to connect and learn from each other. We'd be thrilled to see you there. Catch you next time. [music]

MADDIE 00:01 Welcome to Alter Everything, a podcast about data science and analytics culture. Today, we're going to talk about how data is used in law enforcement and in the military. [music] Our first guest is Sergeant Melanie Goulette, an intel analyst with over six years of experience in the US military and is now a sales engineer at Alteryx. MELANIE 00:21 And here I am. I'm on a helicopter. I have an interpreter. He's telling me what these people on the ground are saying. I'm able to locate them, and I tell the pilots where these locations are at, slew your cameras, all this stuff is going on. And at the end, I'm the one that has to parse out the data. I'm the one that has to remember everything that happened. I have to take notes while I'm in a helicopter. MADDIE 00:45 You'll also hear from Doctor Erica Reuter, sales engineering manager at Alteryx, with a background in managing a police department intel unit. ERICA 00:54 When you watch The Sopranos on TV, and you see those charts with all the strings attaching people, and you get the organization of the crime family that way, you do that with technology now. MADDIE 01:05 And finally, our guest host today is Will Machin, team lead for community management at Alteryx. WILL 01:12 You're both [inaudible] rad, and it's really awesome to work [laughter] with you, and I hope we can bleep that out, because I'm sorry, I curse like a sailor, [laughter] and I think I did this in the last episode, too. MADDIE 01:21 While this conversation focuses on the experiences of two United States citizens, our global audience will also benefit from their tips for how to keep your data and the data you work with safe, as well as important reminders of how bias can harm your analysis. Let's get started. [music] WILL 01:45 Awesome. Hi, my name is Will Machin. I am a team lead for community management here at Alteryx, and I am guest hosting today's episode. We are very lucky to have Erica and Melanie here with us today. ERICA 01:58 Will, so, technically, Doctor Reuter and Sergeant Goulette, if you want to be fancy, because I know you're very sensitive about your last name and-- WILL 02:07 I am. It's very true. ERICA 02:08 --credit. WILL 02:09 Much appreciated. Today we have Doctor Reuter and Sergeant Goulette with us to talk about a topic that I think is really interesting. We're going to be talking about public sector usage of Alteryx. And a lot of times, our products are often thought about as positioned in the finance industry or just kind of business analytics, but there's so much more depth to the uses that you can have. And you all have some really, really fantastic experience and information about it that I think is just going to be very interesting for everyone to hear. So, with that, I will let you all go ahead and introduce yourselves to give a little more background and in a far more appropriate fashion than I would be able to. MELANIE 02:47 Well, thank you, Will, for the introduction. My name is Melanie Goulette, aka Sergeant Goulette. I have been in the military for almost six years as an intel analyst. I'm in the Army National Guard. And so my full-time job used to be a geospatial analyst as a contractor for the Department of Defense. And then, way before that, I was also a teacher for the military. So those are kind of my three main gigs, you could say. I just joined Alteryx back in November, and I am a public sector sales engineer. I work for Erica. I'm very excited to be here. This is all new to me, and I feel like a fish out of water, but it's in the best way possible. ERICA 03:32 I really should have gone first because she's a tough act to follow. But my name is Erica Reuter, and I used to manage an intelligence unit for a police department. I had a lot of roles in law enforcement because they like to rotate us around a bit. But in the end of my career, I was doing intel work and helping support our investigators, our detectives with capturing bad guys. Towards the end, it kind of got to the point where the industry wasn't satisfied with capturing bad guys. We wanted to stop people from being victimized in the first place. So we started dabbling into predictive analytics and trying to figure out like, "Hey, how can we kind of just be in the right place at the right time as much as possible and get some things and stop people from having to go through some terrible ordeals?" So I learned how to do that, and then I got recruited by the tech world to teach other departments how to do the same sort of thing. And now, here we are at Alteryx where we're sort of continuing to work in the state, local, education, and federal sectors. So super excited to talk to you about our personal experiences, what we've seen other people do, and the intersection between technology and public safety because it's a fascinating field. WILL 04:46 It really is. And just in some of the prep calls that we've done for this episode, it's just kind of shed a huge amount of light on like, "Oh, there are capabilities far beyond what I'd even thought of," like working with a lot of our customers and community. So, Melanie, can you share with us a little bit how analytics and data is used within the military space, in general? MELANIE 05:07 Yeah. And that's a huge subject, especially with the military as a whole. It's kind of hard to know where to start because really, the whole entire military relies on big data, anything from administrative, budget, finance, personnel, supply, logistics. Everything relies on data management. I come from the operational side, which definitely relies on data, but it's less of a big data picture and more of a specific. So, if we have a specific target, we need things or information on just that target. And so the challenge is finding all of those sources of data. So, there, we have this volume issue. We have these systems issues where they don't talk to each other. And then, on the operational side, it takes so long to find that information. So, really, from top to bottom, left to right, the military is just driven by data. WILL 06:11 That's really interesting. We're talking about big data, and that's something that has been such a buzzword for such a long time. But I think it's a really cool contrast there to talk about how the small data is also really important, especially when looking for a specific target or a specific instance. Do you have any stories or examples that you're able to share about that? Is that all kind of redacted at this point? [laughter] MELANIE 06:34 Well, I did deploy to Afghanistan in 2018 and '19, and obviously, that era has kind of concluded. And so it's not that it's so sensitive anymore, but when I was there, I was an all-source analyst or am an all-source analyst in the military. And so we're kind of known for being PowerPoint rangers. We take everybody else's information, and we compile it into PowerPoint reports. And we're aware of that. We know our reputation. But I had a very different experience in Afghanistan. I had a very small section that I worked in. My captain was very proactive. He was very passionate about intel, and he was also an Apache pilot. So my unit is an Apache unit, and he was just balls to the wall all the time. And so, when we got to Afghanistan, he said, "We're not just going to sit around and be PowerPoint rangers. We're going to figure out how to affect this war." Because Afghanistan was known as the 21-year war, essentially. So, every time there's a new administration that would come, a new leadership, they would restart the strategy. So we got to Afghanistan, and we're like, "How do we fight this war? What do we do?" And so we kind of pioneered a new intelligence collection method while I was there. We took what's called a V rod, which is basically an antenna that collects push to talk, so like radio traffic. So it could be similar to a police radio here where people listen in on it. So we took this machine that people would use to listen to radio traffic, and we attached it to a helicopter. So we attached it to the outside of a Black Hawk. And what we would do is, we would take these full-on helicopter assault packages, usually called a half helicopter assault force, and what we did is called it a false half. So we would take two Chinooks, two Apaches, two Black Hawks. One of the Black Hawks would have this machine on it. And we would fly over a village that was supposed to be a Taliban village, pretending like we were going to insert a team to conduct an assault. But really, what we were doing is flying around, taking video, and listening to these radios to see what their reaction would be. MELANIE 08:49 So what we were able to do is identify when people on the ground identified the helicopters, identified which direction they were going, and communicated that to the village. By the time we would get to the village, they would already know we're coming, and then we would be able to see how many people there were, what weapons they had, where did they go when they thought a helicopter assault force was coming? And so this really filled in a lot of the gaps that they needed to kind of conduct some of the more off-hand's targeting, like striking, basically. So, in the process of that, we realized that there's so much information here, and we don't know what to do with it. We're just all-source analysts. We're just PowerPoint rangers. And here I am, I'm on a helicopter. I have an interpreter. He's telling me what these people on the ground are saying. I'm able to locate them, and I tell the pilots where these locations are at, slew your cameras, all this stuff is going on. And at the end, I'm the one that has to parse out the data. I'm the one that has to remember everything that happened. I have to take notes while I'm in a helicopter, and I have to get in touch with this interpreter, who it's probably not easy to get a hold of, and see if he can go through the tapes again and all that kind of stuff. So, really, it came down to just me and the couple people I had around me to figure out trends, to analyze what these people were saying, and when and how that correlated to the assault force and all this stuff. So it was just a lot. It's a lot of information. And that's on the operational side, which is small data. It's not even big data. It's just, there's no way to really catalog this, analyze it, look for anomalies, changes, that kind of stuff. So, long story, short-- ERICA 10:35 Is there no way? [laughter] There's a way. MELANIE 10:37 But there is a way. [laughter] And I didn't know that. And so, when I went to interview with Alteryx and create my demo, I was like, "Holy cow. Where has this been my whole life, this product, this program?" Honestly, I was like, "I could see this being used in so many different ways on the operational side." So that's my Alteryx plug. WILL 11:00 I love that. That's so cool. MELANIE 11:00 That was a good story. [laughter] WILL 11:02 I mean, talk about learning on the fly, quite literally, when you're expecting to be a PowerPoint ranger, like you said, and then you're in a helicopter in kind of a live situation that provides safety for God knows how many people and helps every aspect of the tactical deployments and everything. That's incredible. Okay. So, switching sides a little bit here, Erica, can you share a little bit how analytics and data can be used within the law enforcement space, specifically? ERICA 11:33 Yeah. But it's going to seem so boring now. Yeah. We use analytics a lot. And you can think about all kinds of different aspects of crime, different aspects of society. If you think of drugs, for example, I'm super passionate about narcotics investigations. I'm super passionate about the war on drugs. I know, Nancy Reagan, whatever, but people die. And I think all of us probably know someone within one degree, if not two, who've had their lives destroyed by drugs. So the thing about it is, drugs are a business, right. And there's data behind every single business. And when it comes to things like this, it's not necessarily about making an arrest. We could arrest someone and take them off the street, and that's great. And then they bond out, and then they go back to doing their thing tomorrow. That's fine. Really, what it's about is shutting that business down, setting up a RICO investigation, seizing all those assets, taking all their money, getting them to the point where they cannot start that business back up again. And that comes down to data. You have to be able to prove that it's a business, so doing things like network analysis. And when you watch The Sopranos on TV, and you see those charts with all the strings attaching people, and you get the organization of the crime family that way, we do that with technology now, and we do that with drugs, and we do that with burglary rings, and we do that with all things like that. When we're looking at social media, when we're looking at financial data and money laundering, there's just so much that goes on right now that crime is so much more organized than it used to be. And people who are committing crimes are so much smarter, I mean, maybe not smarter. I guess criminals have always been smart. Society has always been smart. But it's evolved. And now, there's just so many high-tech ways to do crime. And there's just such a digital footprint in everything we do. So the intersection is pretty natural, and the work that's being done blows my mind. I don't know how people could think they're going to get away with anything anymore because there's such a digital footprint in our lives. It's very hard to not have a trace of where you've been and what you've been doing. WILL 13:41 Yeah. It's interesting you say that because it's such a voluntary digital footprint as well. People opt into everything, like every app we download. So thank you guys so much for going into a little more detail there. I think that both of those stories are really, really cool. And Erica is saying that's boring. I think not, because you're right, I think all of us at some point or another have had some kind of experience with someone we know that has been super-negatively affected in some aspect of their lives due to drugs and everything. And so, the ability to kind of go in and look at that, like you said, not from an individual kind of bad actor, but looking at it more as an organizational kind of attack and problem, is really a much stronger way to go about it. So I think that's a really, really great perspective. So we've got a little bit of details about both of your background and kind of some of the things you've done there. One of the things we've heard about a huge amount recently in the news and with coworkers, friends on Twitter, on Facebook, on whatever social media you're on, is cybersecurity. And so do either of you have any kind of general, quick tips for our audience about their personal data, the data they work with to make sure it's secure, to make sure that people are being safe and making kind of informed, intelligent decisions whenever they're dealing with those things? ERICA 15:07 We have a little saying around here, "Dance like nobody's watching. Encrypt like everyone is." WILL 15:12 Ooh, I love that. [laughter] ERICA 15:14 So encryption is always huge, right, and just understanding that nothing's ever private and being very careful and checking, naturally, the sources of the emails that are coming in to you and things of that nature. Melanie is actually getting her master's in cyber, so I'm sure she's got a lot to say on the topic. MELANIE 15:31 Yeah. I know a lot about law and policy and the disconnect between public and private sector and cybersecurity if you ever want to chat about it. But actually, this is kind of something that I'm a bit passionate about when it comes to my military peeps. I have to kind of plug here for them because I've seen, a few more times than I'd like to admit, people putting our soldiers at risk by what they post on social media. It doesn't matter what platform it is. If you're posting about troops traveling or posting pictures, their location is attached to that most likely, and you don't even know it. And so I understand the desire to be proud of your soldier, marine, airman, whoever it is, but you could be putting them at risk. And so that's something that hits very close to home for me, just having seen some of the effects of that loose information out there. So I would just say be careful. Definitely be proud, but maybe wait till your soldier gets home, or just keep it within family, off of social media, and stuff like that. But I mean, other cyber tips, you just can't be too careful. Also, when you get your own modem, router, whatever it is at home, change the admin password. A lot of people, I feel like, don't do that for some reason, and it is the easiest way to get into your home network where you're using your banking information, all your passwords are stored, your phone is connected to it, your cameras are connected to it. Just be safe. Change those passwords. WILL 17:05 Use a password manager. [laughter] So I know that we have chatted a little bit previously about this, but crypto and blockchain is always a huge talking point at this point. Everyone thinks it's absolutely secure, and no matter what they do, they're going to be fine. But I know that you have a story that kind of shows that may not be the case, necessarily, and some steps that might be able to be taken to rectify something when it does happen. ERICA 17:32 So I am far from a blockchain expert, right. I'm sure when I tell the story, you all who know about blockchain are going to be like, "That's not exactly right," but the essence should come through. WILL 17:42 Oh, I don't even know what an NFT is right now, so I'm not going to be the one to call you out. ERICA 17:45 Right. [laughter] So there is a guy that works with Melanie and I, and he's my favorite kind of technical person, in that, he's sneaky smart. You know those people that you talk to them, and they're just totally normal, and then, after a while, you're like, "Oh, you're smart. I had no idea because you seem so normal." So, anyway, he invests in crypto, and he invested in a crypto project. And the way he explained it to me was, developers make projects where maybe they're making a new coin, or maybe they're making a new security feature, or things like that. And then they put it out, and then people can buy into the project as investors, just like you would a stock, right. But you're buying it, and it's on the blockchain, and you can see all the transactions of everyone who's bought and sold their interest in these projects. So he buys into it. He knows it's a risky one, but it's doing well, so he's happy about it. All right. So, then, a little bit later, the developers reach out to everyone, and they're like, "We got hacked. All your money is gone. I'm so sorry." This is kind of the risk of blockchain. It's unregulated. It's on the internet, and things happen. So he's like, "Oh, we got hacked. That sucks. All of our money is gone." But our associate was like, "Not today. You messed with the wrong person. This seems suspicious." So he actually used Alteryx, a little gentle plug here, and he got an API to get every single transaction on the blockchain, right, which is like millions. It's impossible to just look through this and find patterns. And he basically found that the developers of the project were slowly siphoning money, like 5, 10, 15 dollars at a time through an anonymizer into their own wallet on the other end. So they kind of just made a bunch of transactions and pocketed all the money, and then called it a hack. And they sort of just hacked themselves and drained the account. So he's like, "I got you." He was real proud of himself. And he called his friend at the FBI, and he's like, "Hey, look what I found. Blah, blah." They've opened an investigation. So, hopefully, we'll see some justice, and people like this can't continue to do this to people because whatever, we don't like people like that. Why can't everyone-- WILL 19:51 No. ERICA 19:52 --just be nice? WILL 19:53 Well, I mean, I think nice is overrated, but kind is not overrated, necessarily. ERICA 19:58 Not devious. WILL 19:58 But that's a different subject. ERICA 20:00 Yeah. That's a subject for another episode. WILL 20:01 Exactly. But what I've learned from this is, make friends with someone at the FBI. So, if I do need to call them, [laughter] I know who to call. MELANIE 20:09 That's a great point, Will. Yeah. I think that's the key takeaway here. ERICA 20:12 I feel like they have other channels, but yeah. WILL 20:15 I mean, I would assume so. [laughter] So that's such a cool story. And I think it's such a really interesting point and perspective on being able to kind of do your own work sometimes to get the ball rolling when something's happened. And sometimes, you have to take those first couple of steps yourself, and then, having that kind of literacy and knowledge can really help that. Even if it's not as advanced as what he did, necessarily, just being able to do some investigation and everything like that can be super helpful. ERICA 20:44 Honestly, what he did, though, it just took him a few hours. All he had to do was download all the transactions, and then say, "Hey, computer, show me anything where there's a lot going between more than one account. Find the pattern for me." That's it, just a little, "Hey, computer, figure it out." So it's not as hard as people think it is. Sometimes, it is. I'm not going to say it's always super easy, but in some cases, it's really not that bad. Definitely worth dipping your toe into. WILL 21:10 Yeah. And it's pretty crazy. We, essentially, legitimately live in the future now with the way that data and technology and everything is just so easy and accessible, which kind of leads me into my next question for you all. Are there any specific initiatives that you guys are working on within public sector to really help with kind of the betterment of the sector, in general? Because I think a lot of times, people think of data and technology working together to be kind of scary, or it's, "Big brother is going to watch us," but there's so much good that can come out of it, too. And I think that you two would be perfect to share some examples of that. MELANIE 21:44 Yeah. And so I'll start on that. Erica might have some more to add. But really, what we kind of want to focus on is like health system integration. ERICA 21:56 Basically, it's an alliance between the military, academic resources, major universities, and technology vendors. And we're all coming together to kind of research how we can help integrate data for war fighters to give a good continuity of care and get all these systems better integrated, so we have a more holistic view of what they need when they need something. And I'm sure Melanie could speak a little bit better, more intelligently than I, as to why there is a gap there. MELANIE 22:25 Yeah. So, before you join the service, there's the MEPS program that you have to go through. While you're in the service, you either have care provided by the military if you're on active-duty orders, or if you are Garda Reserve, then you have TRICARE Reserve Select, and then you have your choice of providers. And then, when you go to get out of the military, you have your healthcare, post-military. You have the disability system. And none of those systems talk to each other. So you have to take everything from one system, get the reports, and physically give it to somebody in the next system. There's just no continuity there. And a lot of times, it ends up with gaps in care. And that's what I've seen a lot around here, especially where I live. There's a huge veteran community, and there's gaps in care, and they may not know how to fix that or how to go about getting that care that they need. So, if we can start to solve that problem, where these different systems are talking to each other, and it's not on the veteran to go figure out what to do-- well, I mean, part of it is on them, but also, we should be taking care of them. The military, the government should be taking care of them. And so I think if we can start to head in that direction, that we can make some big changes there. WILL 23:50 I think that's hugely important. I used to live in DC and just was pretty involved for a while with the veteran community, and it is such a huge issue. These are not exactly super-transparent policies. I mean, even standard healthcare stuff, you try to figure out, and I have no idea. I have to call Cigna on a regular basis. So, when you're switching between programs, and the government's involved as well, it becomes pretty obtuse to try to navigate. So the fact that there is some way, or you guys are working on something that can help with those transitions is a massive improvement, I would say, already. I mean, I'm really excited to hear and see where that goes as well in the future because it's something that affects a large number of people that may not necessarily have the resources to hire out for help sometimes or know who to even reach out to for help, occasionally, because calling a call center is not always going to fix that problem for you. So what else would you guys want our listeners to understand about the use of data and analytics from a safety perspective? We always talk about how data literacy is really important, and that the ethical usage of data is really important, and bias is a big conversation right now. And I think that that could be something that's looked at because people always think of data as just black and white. So there's no bias. But collection of data can include bias, like reporting of it, and how it's presented can also show that. And so we'd love to hear your perspective on that, about that usage in the public sector and just kind of from a safety perspective, in general. ERICA 25:24 Yeah. Unfortunately, bias is a real thing. And technology reflects society. It doesn't invent the bias. In some cases, it inadvertently compounds it. But what we like to try to do is really just look out for that and try to make sure that we're validating things and trying to make sure that any data that's being collected, that it's necessary. If we're doing a particular thing where we're trying to figure out crime patterns, race isn't going to have anything to do with that. There's no need to even include that variable. Let's just take that out, right. Gender is not going to have anything to do with that. Religion, sexual orientation, any of that stuff doesn't matter. That's not going to change the fact pattern. So it's always good to take those things out in your analysis unless they're going to inform something. The other important thing to remember is, any action anyone takes, the computer doesn't make them take that action, right. You need probable cause to arrest someone. You can't just go and arrest someone because the computer said they probably did it, right. The computer is an investigative tool to help us be a little more efficient in our processes and to think and to understand and to make sure we didn't miss anything. But we, as humans, still have a responsibility to do our due diligence, to do a good investigation, to make sure that we truly can defend our recommendations and our analysis that we're putting forward. So I wish bias wasn't a thing. It has been since the beginning of time, as far as I know. And it's up to us as humans in partnership with what we're getting from the computer to make sure that we feel good about how we're using that data, how we're presenting it, and how we're going about that collection and doing the best we can to control for it. MELANIE 27:13 Yeah. So, just to kind of add a little bit onto that, I think Erica nailed it, but when looking at the operational side where I come from and small data, bias is huge in that process. If you're relying on one or two individual analysts, and there's no system to kind of check that bias, then the end product is part of that. [laughter] Yeah. Their views on the world will come through in that. And so that's not good for anybody, especially the end user of that information. There's Americans on the ground using this intelligence to conduct operations. So, if an analyst doesn't recognize their bias or even the fact that bias exists, that's a problem. And so, having a tool like Alteryx where you completely take that out, like Erica was saying, there's factors that just don't need to be taken into account. So, from my point of view, that's where I would say bias comes into play. WILL 28:13 Well, and I think it's something-- just this whole conversation is like, any human interaction, there's going to be bias present. And I think just kind of recognizing that that bias is going to be there, whether it's positive or negative, it's part of it. And so trying to remove that is essentially impossible from your interactions. But being able to remove it when you're analyzing something is really important as well, where you can say like, "Okay. There was bias here, but let's try to take that out," when we're looking at kind of the actual data and the results of an interaction of whatever kind it is. ERICA 28:47 It can affect your sample, right. So, sometimes, it's impossible to take it out. "I wish they had patrolled a larger area. I wish they weren't only looking at this neighborhood. I wish they weren't only looking at this group of people." It is tough when that goes in. I don't want to acknowledge that doesn't exist. But again, that's where we as humans have to step in and just make sure that it's fair. WILL 29:08 Yeah. Try to neutralize as much as possible, realizing that it's not a perfect system. Because life is not a perfect system, but we can do what we can to make it as close to that as we can. So I am fascinated by all of this work and your stories that you all have shared. I think it's really cool to think about kind of the big data, the small data, the art of the possible. So this is something that I think we're going to intersect on a little bit, even though I have already been chided for not listening to Serial yet. But Erica, I know that you're a huge true crime fan. Can you share some of the side projects and use cases that you have worked on in the area? ERICA 29:42 Yes. So I'm a total nerd, and my work is also my hobby. So, sometimes, I like to just kind of go and think about, "Hey, if crimes happened today, could I have solved them?" right, or, "Could someone have solved them?" or, "What would it have looked like in today's environment with these great technological advantages that didn't exist in the past?" So there's a good Netflix special, or there was, on Ted Bundy. Did you guys happen to see that? I think Zac Efron was playing Ted Bundy, and they kind of just talked about it, and it was like, "Oh, Ted Bundy, right." So I was thinking about Ted Bundy and how many people he has killed, which is an insane amount of victims that Ted Bundy had over the span of years, and I was thinking, "Okay. Well, would he get away with that today?" Do you guys think he would get away with that today and have his spree go as long? WILL 30:30 My guess would be no. Like you said-- ERICA 30:31 Why? WILL 30:31 --digital footprints are a huge thing at this point. ERICA 30:34 Exactly. I mean, he had that very distinctive car. He had that VW Bug. And there were descriptions, right. And there were witnesses. And it took them a while to figure out who he was. And then I started thinking, "Okay. We've got all these different crime scene locations, used the same car." We were talking about that podcast, My Favorite Murder, a little earlier. And I remember someone writing in and being like, "Oh, actually, I was in the car." They got away. They were one of the early escape victims. Yet, I digress. Sorry. Okay. So very distinctive car. And now, we have license plate readers all over the place, and we have traffic cameras all over the place. And that data is pretty public. So what I was able to do was scrape all of the crime scene locations and put them in chronological order, right, and then scrape from a map all of the locations of the red-light cameras and the license plate readers in Washington state and in Oregon because that's kind of where the early crimes occurred. And there was a description not too far into his spree. I think it was four or five crimes in when he hit the lake is when they really started to identify this car. ERICA 31:40 And kind of what I was found was, hey, if you really, A, just looked at the cameras around these locations, you would see a similar car, right. We have the ability now to do image recognition and object detection, and we could actually go through and classify all the cars, right, and be like, "That's a Ford. That's a Bug. That's green. That's yellow." We would have seen a pattern of that car, or at least that very distinctive-looking car, that model being around all of these crimes. It would have been pretty, I don't want to say easy, but easier today to have gotten that vehicle description a little faster, just with all the technology that's around. The other thing is, okay, so, now, we've narrowed it down to this car, right. Now, we can look at those license plate readers and start to get those tags, right. Because eyewitnesses are somewhat unreliable. You see something crazy, whatever, getting a tag is not as common as one might think, but cameras get them. So it's quite possible with technology that we would have got there faster. And I just find that riveting. And again, the data [laughter] is on the internet. The analysis doesn't take programming like it used to, right. You could just sort of like, "Load this. Load this. Find commonalities," and the computer does it so fast. And I don't know. That's my favorite part of this job and of this world and of this life. And that's why it's a hobby. Because just having those moments of, "Oh, my gosh. Look at that. Look at what the computer found. And I pretty much just pointed it to it, and it put it all together," blows my mind every time. Every time it happens, it blows [laughter] my mind. WILL 33:15 It kind of reminds me of, even like when they found the Golden State Killer a couple of years ago. ERICA 33:21 The DNA. WILL 33:21 My friend was in that Reddit community that had been doing a lot of the searches and sharing stories and everything and just that collaborative kind of-- even that just being a forum, technology allowing people to connect those dots, let alone using data mining and everything like that, to be able to fully connect dots more quickly. It is really kind of insane how much technology has allowed us to really step up on doing that. And you're right. I think it makes a huge impact on preventing kind of the sins of the past from occurring again. ERICA 33:51 Serious hats off to those in the '70s during that time who didn't have it. I don't know how they solved anything. To me, they're super heroes. I have no idea how policing was done. No. That's not true. But definitely much harder. Definitely much harder. And you didn't have as many advantages as you have today. MELANIE 34:09 I would be interested to see the difference between how long killing sprees used to go on versus now. Do we even have real serial killers now? I don't know. ERICA 34:22 Funny, you should ask. I Googled that recently. I had the same question. And apparently, yeah, [laughter] there's a terrifying amount out there. But yeah, I don't know. I don't know, like longevity. That would be an interesting research project, right, to just sort of see how that's changed over time. WILL 34:37 I mean, SVU will eventually run out of subject matter if they go away entirely. So we will be forced to just watch reruns, but I feel like that is a fair trade for the safety of the general public. MELANIE 34:47 I agree. It's a great show. ERICA 34:50 The SVU laundry stealers or some sort of real estate. WILL 34:53 Right. Exactly. We'll just lower the stakes a little bit, [laughter] less murder and more petty crime. ERICA 34:58 You stole my yogurt out of the community fridge. WILL 35:00 Ooh, I like that. [laughter] And then I would like to follow up with one more question for you as well, Melanie. So your helicopter story that you shared was super impressive, especially when it's not necessarily what you're expecting to do when you first get there. Do you have any other stories about your time overseas? ERICA 35:20 Bonus challenge, no PowerPoint in your story. [laughter] You're not allowed to say PowerPoint. WILL 35:26 [inaudible]. MELANIE 35:27 That's a hard one. ERICA 35:27 Got it? Okay. [laughter] MELANIE 35:29 My brain just short-circuited there for a second. [laughter] Well, I will say that there is nothing like the first time you see camels running around in the wild. That is a trip. But no, see, a lot of my stories have to do with flying around in helicopters. I will say that Afghanistan is beautiful. It's just got this almost kind of melancholy feel to it where there's a sadness, but it's so beautiful. There's the red desert, the mountains. It's amazing. But yeah. WILL 36:08 Also, I'm here for another helicopter story if you have one, too. ERICA 36:12 Or gossip, military gossip, like who is-- MELANIE 36:15 Girl. ERICA 36:16 --doing crazy things over there. MELANIE 36:17 Girl. WILL 36:18 Everyone [laughter] is doing crazy things over there. MELANIE 36:19 It's insane. [laughter] It is the Wild West over there. So you know what? You've heard of drones. Obviously, everybody's heard of drones. There are ones, though, that are not remotely piloted. They actually have people in them. And so they're just small airplanes, all this equipment, whatever. I just happened to meet this guy at the gym or something, and he is an analyst for one of those reconnaissance aircraft. And I'm like, "Oh, that's cool. So what's it look like?" And so he's showing me all the parts on it, and he's telling me how to use them, and he's like, "Do you want to go on a ride?" And I was like, "Hell, yeah, I want to go on a ride." So this turned into me basically doing ISR collection in the airplane for five hours. You're just flying around so high that people can't even see you or hear you. And he let me control the cameras and stuff. And so doing that a few times was an incredible experience that is like nothing you will ever see again. It's incredible. But I saw wild horses when I was up there. Yeah. It's an incredible view of the world, I will say that. ERICA 37:38 Do you feel different? Does your body feel different? MELANIE 37:42 Not really. No, not really, but it's really loud. You can't hear anything. It's very peaceful. But other than that, anybody on this call who is a veteran who is deployed knows about The Green Bean, and that is a lifesaver. Getting a cappuccino at The Green Bean was a little piece of home, and I think that would resonate with a lot of people. WILL 38:02 I can imagine that. Those little things that you take for granted here where we kind of have anything on demand become precious things over there when they're not readily available. So I would imagine that resonates with a lot of people. But honestly, getting to ride in a drone sounds incredible. I feel like they should sell rides like that in Vegas or something like that, but. MELANIE 38:24 It was quite the experience. And I think what I learned from my time in Afghanistan is, look for reasons why you can do something or why you should do something. There's so many people out there that want to be so quick to say, "No. We can't do that," or, "That's not possible." Why? "Why is that not possible? Tell me why, or I'm going to go do it, because I know that I can do it." So that's just kind of a mantra I bring with me now. WILL 38:51 I think that's such a good takeaway, in general. Don't cancel your own abilities before you figure out either why you can't do it or figure out a different way to approach something because a lot of it really is perspective in how to do that in the long run. MELANIE 39:04 Yeah, for sure. WILL 39:06 Awesome. Well, thank you both again for sharing that. I feel lame in comparison now, but I get to talk to awesome people like you all, so I will take that any day of the week. ERICA 39:18 You're the best dressed of us. MELANIE 39:21 Totally. Yeah. [laughter] ERICA 39:23 Yeah. Exactly. WILL 39:24 I just want to say, Sergeant Goulette, thank you for your service, and Doctor Reuter, thank you so much for everything that you've done as well. You're both [inaudible] rad, and it's really awesome to work with you, [laughter] and I hope we can bleep that out because I'm sorry I curse like a sailor, [laughter] and I think I did this in the last episode, too. But it's been an absolute pleasure speaking with you both today, and if there's anything else that you want to add as a wrap-up, please feel free to do so right now. I would like to cede the floor to both of you. ERICA 39:50 Just share what you're doing. If anyone has anything, and they want to talk about, "Hey, is this possible?" oh my gosh, we love nerding out on that stuff. So, yes, we technically work in sales, but we're not commissioned sellers. We're solutioners, and we just like nerding out. So, if anyone has ever wanted to ping something on LinkedIn or send us a note to our email or our community profiles and be like, "What do you think of this?" trust me, we'll be like, "Oh, my gosh. That's so cool. You could do it this way. You could do it that way." We're all into the nerd-outs. [music] MADDIE 40:26 Thanks for listening. For more on the projects mentioned by Erica and Melanie or to just nerd out with them about all things Alteryx, check out our show notes at community.alteryx.com/podcast. And if you've never stopped by our online community, please come join us. We have over 300,000 members from around the world that love to connect and learn from each other. We'd be thrilled to see you there. Catch you next time. [music]

This episode was produced by Maddie Johannsen (@MaddieJ). Special thanks to @andyuttley for the theme music track, and @mikecusic for our album artwork.

michaelsull1231 · ‎05-24-2022

dance like nobody's watching, encrypt like everyone is. great podcast!

Alter Everything

Episode Guide

106: Learning on the fly, quite literally

Panelists

Topics

Transcript