The Abaddon Costello Program, starring Bud Abaddon and Lou Costello, brought to you by Camel, the cigarette to cost me or properly aged tobacco.   Explain yourself, where have you been? Well, I was listening to my cousin Hugo giving a very important speech under cold shortage. He said, gentlemen, due to the cold shortage, we must save electricity. I beg you not to use electricity. Please don't... Did they listen to him? No, the warden threw the switch anyway. Never mind your cousin Hugo. Do you realize there's been a woman waiting for you here for the last hour? Oh, there you are at last, Mr Costello. I could hardly wait till you got here. I've been simply dying to see you, and at last here you are. At last here we are. You and I, based on...  Mrs. Adelso, what brings you to California? Patterson, New Jersey. Abbot, did you hear that? You want me to be mayor of South Patterson? I'll be another luck warden here. It was a great man. They call him the little flower. What is the same thing with me? Oh, people would call you the little flower? Not a big stinkweed. I'll run. We was a man who was handsome and intellectual. In that case, slow me down for a walk. Mrs. Adelso, can't you get somebody that's better qualified than Costello to run for mayor? Well, my husband was thinking of running, but he's such a busy man. You see, he has a seat on the stock exchange, and he also has a seat on the city council. Your husband has two seats? Yes. Does Ripley know about this? I'm going right out now that you are leaving on the midnight train. Wait a minute, Costello. You can't run for public office. You don't know anything about politics. Oh, sure. Do I come from a family of politicians? Am I Uncle Artie Stebbins with a politician in Texas? What did you run for? Huh? What did you run for? The border. Oh, no. The mayor, Mary, you have to be educated. How high did you get in school? How high did I get? I never cut your stuff. No, no, no, no, no. I mean, did you go to high school? Oh, yeah, I went for a whole week. Did you learn anything that would help you? Oh, sure. But you can't make a career out of nothing. I bet you don't even know the alphabet. Oh, yes, I do. Let's hear it. The alphabet is A, B, Q, W, Z. Where did you learn? Where did you ever learn the alphabet that way? When I went to get my eyes tested. I can't see that. Come on. We're leaving for Paterson to join you tonight on the midnight train. You ready to go, kid? Wait a minute, Costello. Here we go. Choo-choo. Wait a minute. Let me play Choo-choo train. You just can't... I'm going to Paterson. And you keep quiet, please. Never mind where you're bound for. You can't just leave on a train like that. Have you got a reservation? A reservation? What do I look like? An Indian? No, no, no, no. If you're going all the way to Paterson, you'll have to have a Pullman. You know, old someplace to sleep. Oh, that's easy. I eat garlic. That's all right. What has eating garlic got to do with getting a place to sleep? I just breathe in the conductor's face and he gives me a wide burp. No, no, no. I'll tell you what you do, Costello. Now, in order to save money, we'd better get a couple of upper burps. Yeah, but I don't want an upper. I want a lower. But, Costello, do you realize that if you buy a lower, you'll find it's much higher than an upper? Oh, sure. Everybody knows that when you... What did you say? I said that a lower is higher than an upper. A lower is higher than an upper? Oh, certainly. What are they doing? Running the trains upside down? Of course not. The lower is the more desirable burp. Therefore, if you want to go lower, you'll have to go higher. If I want to go lower, I have to go higher? Why should I go higher when I want to go lower? Costello, I'm trying to tell you they sell the upper lower than the lower. Because when you sleep in an upper, you have to get up to go to bed. I have to get up to go to bed? That's right. Who's paying for my burp? Well, you are. And there ain't nobody in it for me? No. Then why do I have to get up? Oh, look, Costello, I've already explained it to you that way. Look, unless you go higher for a lower, then you're stuck with an upper and you'll have to get up when you go to bed. And you'll have to get down when you want to get up. Let me smell your breath. Can't you understand anything, you dummy? If you want to go lower, you have to go higher because the lower is higher than the upper. And the reason the lower is higher than the upper is because the upper is higher up than the lower. Ah, you mean that the upper is lower than the lower because the lower is higher than the upper? No, you've got it. Now I've got it. The airline in the United States and at practically any populated point, look out of the window and there would be a place covered by this great survey of doctors I want to tell you about. A survey so thorough that it covered 113,597 doctors, doctors in every state of the Union, doctors in every branch of medicine. So thorough it took the combined efforts of three leading independent research organizations. What cigarette do you smoke, doctor? That was the query. And the results? Well, the cigarette named most was camels. Again, the rich, full flavor and cool mildness of camels' superb blend of costlier tobacco is one nationwide recognition. Yes? According to a recent nationwide survey, more doctors smoke camels than any other cigarette. Well, camel fans everywhere, Carl Hoff and the orchestra play seems like old times. Let's write pants. Oh, my brother's wearing them. He's delivery boy for the meat market. Well, why don't you get the pants back from him? It's sunburned on his afternoon delivery. He's packing now. I'm taking all my sporting equipment along. My old golf clubs, my old baseball club, and... Hey, by the way, have you seen my old bat? Yeah, I saw it last night in front of the place. Wait a minute. The bat I'm talking about was shellac. That's the one. I'm the baggots, man. Good. Take all this luggage down the railroad station, please. Okay. Oh, boy, this thing is heavy. What have you got in this old beer barrel?  Here, baggage man. Take this trunk downstairs first, please. What? I'm not gonna carry that big, heavy tank down those stairs. Ah, you don't have to. Just step into the elevator here. I'll open the door for you. Step in. Thanks. Before I leave that elevator. Look, Costello speaking. Mr. Costello, this is a Hollywood movie star, and I hear that I'm going back east on the same train with you. Gee, you are? Yes, and just remember, if you want anything, just whistle. Who is this? Lauren Bacall? No, Lassie. Come on, Costello. Come on, we better get down. Will you listen to me, please? Never mind her. We better get down to the station and get our tickets. Come on. We got plenty of time. I want to say goodbye to all my friends, and I mustn't forget my little pets. I must say goodbye to my parrot. Goodbye, Polly. Goodbye. And my little goldfish mini. Goodbye, mini. Thank you. Goodbye to Jack and Henry. Jack and Henry? Yeah, they're my first of been Henrietta. Let's be on our way. Hey, let's stop here, rabbit. This is where my girlfriend, Tessie, came for your lift. See, what have you done to your legs? Well, yes, but Tessie, striped wallpaper. Oh, boy, what brings you to my door with a suitcase? Well, I came to say goodbye, Tessie. I'm leaving for the east tonight. I'm going back to run for mayor of South Patterson. Oh, isn't that wonderful, Louis? You and I should get married. I've always wanted to be a mayor's wife.  Too old? I'm just on the shady side of 30. You've been in the shade too long. I'm on your north side. Hey, look, Costello. There's the actress, Bessie May Muccio, driving up to the curbs here. Hello, Mr. Albert and Mr. Costello. Where are you going with the traveling bog? Traveling bog? Oh, sure, rabbit.  Water, Bertle, and shaving sup. The razor bleeds will shave off your waskers. Costello's going back to his hometown in New Jersey to run for mayor. Can you imagine that? Oh, my, you're going that far away. Well, I must give you an appropriate farewell. Goodbye, my cute little fog. One more friend to say goodbye to. Let's stop and see, Scotty. Say, Scotty, what's the idea of having all your winter shades down in the daytime? The house is pitch dark. Well, my wife's father and mother came to visit me three nights ago. I've kept the house so dark, they still think it's the same night they got here. Is that good? It's wonderful. They've missed 11 meals already. Hey, Scotty, I come over to say goodbye. I'm going back to my hometown in Patterson, New Jersey to run for mayor. Oh, would you be going through Pomona? Uh-huh. Would you mind dropping off the suitcase when you get there? What's in the suitcase, Scotty? My son Angus is going to a Boy Scout camp. Well, how will a poor boy get home? Well, I took the needle out of his compass. Every year he gets lost in the mountains and the searching party always brings him home. Come on, Costello. We've got to get down to the railroad station. Hey, here's a cab now. Pardon me. Cabby, are you engaged? Nobody, but I'm going steady. Never mind. We want to catch the train for Patterson, New Jersey. Okay, jump in and I'll take you to the Union State. The Union State. The Union State. Union Station, Santa Fe Depot. Come on, get us down to the station, please. Ah, don't worry. I'll catch you down there before you can sit. Jack Robin. Jack Robin. Jack Robin. Robinson? Glad to know you're Robinson. Please get this cab started. Okay, buddy. The Santa Fe Depot is only a few minutes from Hollywood. We've been driving for two hours. Yeah, the meter says $37.  Okay. God, don't tell me how to drive this cab. I got a map right here on the floor by my feet and that black line right there leads right to the Santa Fe Depot. Well, hurry up and get us there. Hey, driver, where in the world are you taking us? Yeah, $68. Where's the Santa Fe Depot? Right here. We'll be out Santa Fe Depot. Thank heavens. Come on. Hey, wait a minute. This isn't the Santa Fe Depot. That sign over there says Pismo Beach. Pismo Beach. Pismo Beach. Yes. Hey, I've got the map on the floor here by my feet. I've been following that black line. My shoe came untied. I've been following that black line. My shoe came untied for the last two hours. I've been following my shoelace. Right at this moment in your presence is a great authority on cigarettes, meaning, ladies and gentlemen, your T-zone. That's T for taste and T for throat. Let your taste judge the rich, full flavor of camel's superb blend of costlier tobaccos. Let your throat give you its reaction to camel's cool mildness. Like millions of smokers, you too will find that camel is your favorite cigarette. Camel is a favorite too with many, many thousands of doctors. Three leading independent research organizations check the cigarette preferences of 113,597 doctors all over America. The cigarette most named was camel's. Yes? According to a recent nationwide survey, more doctors smoke camel's than any other cigarette. Here is camel's lovely Amy Arnell with a song that says...   Uh, yes There's a big black thing that pulls them It goes choo-choo and You guys have been bringing too much of that traveller's aid No, no young man What time is the next train leave? Well, we don't know We have a wash out on the line Why don't you take the wash off the line and let's go Oh, never mind him Let's go over to the ticket winner Come on I've gotta have a lower You must get me a lower You've gotta get me a lower Who are you? I'm just an old pajama top No money, Crustella You get the tickets while I take care of the baggage I'll be right back away Well, I guess this is the line Hey yo, Flint What are you trying to squeeze in here for?  My tickets The super chief will be leaving in a few minutes Super chief, super chief Will be leaving on track four Nothing happened How do you like that? I'm pleased you go to the Andrews sisters The super chief is ready for passengers Where are the tickets? Well, I haven't got them I have to stand in this line You dummy, that isn't a line for the ticket window It isn't I wondered why all those people were asking me if I had any nickels Hey, that phone booth is awful busy No wonder the phone booth is busy Look who's in there It's that French girl, Titi Leblanc The railroad station I'm going to Kansas City to visit my aunt Monsieur Costello Would you hold this package while I get the money for my ticket? I have the money right here in my stocking Not of America, never had branches like that Costello's going back east to run for mayor of South Patterson, New Jersey Yes, V.P. I wish you could go back with me and help me with my campaign You could ride around a big truck dressed in a bathing suit And that would make a big hit with the men voters Oh, how could I possibly appeal to the men in a bathing suit? Don't mind her, folks She still plays hopscotch Monsieur, you did not mention how you liked my outfit Oh, that's a lovely dress, V.P. Uh-huh, I made it myself I like to put some of my personality into each dress Sister, you've got it all in that one What kind of a dress is that, V.P? V-neck V-neck?  We're next to the ticket office now, come on, get up there Hey, Abbott, look who's behind the ticket window It's Melonhead Why, Melonhead?  Costello, are you going by buffalo? No, we're going by train, yes, no I know you're going by train Tell me, do you want an upper or a lower? That's a difference Well, if you want to go lower, you'll have to go higher Because the lowers are higher than the uppers Wait a minute, wait a minute Look, Melonhead, can you get the two of us into a compartment? Well, I'm sorry, Abbott But I only had one compartment for two people And I had to put 12 sailors in it How could you put 12 sailors into a compartment for two people? Pied pants And will you hurry up with those tickets? Costello's going to Paterson Paterson? Costello, what is the purpose of this passage to Paterson? Well, eh, will you repeat that? I said, what is the purpose of this passage to Paterson? Are your current expecting you? Give you a shower bath some time Southern or Southern, Ralph? Well, I don't care as long as I go through Bashville, Annie, Wyoming Bashville, Annie, Wyoming? Yeah, there it is, right on the map there That's the thing there Where? Where do you see Bashville, Annie? There's Bashville, Anne Oh, excuse me, that's Cheyenne Cheyenne Come on, let's go, Costello Just a minute, boys, before you get on the train How about a five pound box of herchy bars? Ladies' girdles, pure nylon stockings Brand new pre-war tires and fresh country butter Oh, boy, I'll buy some Oh, selling, I'm buying How about the West? Hey, bad boy, let me help you with that big bag What big bag?  Still to get on the train Hey, look, what is that guy doing over there by the engine? Goodbye, old pal You're the best pal I ever had I love you, I love you Hey, you, what's the idea of patting and kissing that engine? This engine has taken my wife back to Chicago Yee-hoo! Uh, conductor, we are Abbott and Costello Fine, fine, we have a special car for you right here Step right in Are there any pretty girls aboard? I'll say, what cares? Well, Costello, we're underway at last Ruff to Patterson Gee, Abbott, it's crowded and stuffy and just pulming Yes, it's so dark in here, you can't see anything Yeah, where are the girls? I want to look at those pretty calves Where are your girls? And now, tonight's salute to the men in the armed forces who won through to victory Tonight we hail the 7th Armored Division heroes of Metz and Vit the Ruler Since the beginning of the war, the makers of camels have sent more than 150 million free camels to our fighting men overseas But now with demobilization and progress free camels are sent to service men's hospitals instead This week the camels go to Veterans Hospital, Montgomery, Alabama U.S. Army, Halloran General Hospital, Staten Island, New York U.S. Naval Hospital, Newport, Rhode Island U.S. Marine Hospital, Port Stanton, New Mexico and Veterans Hospital, Reno, Nevada in your honor, men of the 7th Armored Division United States, twice a week our rebroadcast to practically every area in the world where our men are stationed and to our good neighbors in Central and South America And I'll hear about Abbott and Luke Costello with the final word Well, folks, we weren't kidding tonight on the level Yes, folks, we're going back east to start the ball rolling for two new Luke Costello Junior Youth Foundations for the underprivileged children Yes, folks, next Thursday night we'll be broadcasting from New York Oh, pardon me, gentlemen, I'd like to... Wait a minute, who are you? Well, I'm just an average radio fan Is it true that you're going to broadcast next week from New York? That's right Is Bob Hope going to New York too? Oh, no You mean to tell me that you will be telling jokes from New York or Bob Hope would be out here telling jokes from California? That's right Heaven help the poor people in Kansas City Good night, folks Good night, everybody Good night Next week for another great Aberdeen Costello show brought to you by Camel Cigarette And remember, try camels in your tea zone See if they don't suit your taste, your throat, to a tea C-A-M-E-L-S Do pipe smokers appreciate choice tobacco? Crimp cut to burn cool? Especially treated to remove tongue bite? They certainly do For Prince Albert is smoked in more pipes year after year than any other tobacco Try Prince Albert in your pipe You'll really notice the difference Saturday night, be sure to listen to Prince Albert's Grand Ole Opry You'll hear Red Foley, Grand Ole Opry's sensational new romantic singer Remember, Grand Ole Opry Saturday night on NBC with the duke of a duke, Minnie Pearl and Red Foley We'll end at this very same time Next week, when the Aberdeen Costello show for Camel Cigarettes comes to you from Radio City, New York Thursday night is another all-star night on NBC Stay tuned for Rudy Vowley over most of these stations This is Ken Niles in Hollywood, wishing you all a pleasant good night For camels It's them being seen, the National Broadcasting Company


The speaker of the House of Representatives, Femmi Bajabiamila, is advocating effective information management as a vital tool for national development. Bajabiamila said this on Thursday at a two-day workshop on information as a strategic tool for national development in Abuja. He said this while the calendar two-day workshop opened. He said there is a need for a review of law's guiding information dissemination and management to meet current realities. Hate speech and other forms of misinformation and disinformation can quickly have a devastating real-world effect. Therefore, country misinformation by whatever proper and legal means are available to us is not a theoretical question, but a responsibility that goes to the heart of our ability to continue to exist as one nation in peace, unity and prosperity. Let us be aware that in trying to prevent the worst consequences of misinformation and hate speech, there is a danger of going too far in ways that smaller the marketplace of ideas and deprived citizens of their free speech rights. That would be most unfortunate. We as a people, community, and government must act ourselves for what purpose, to what end, and in which manner, we move from present phase of development of our nation to the next. Unfortunately, we as Nigerians have engaged ourselves mainly in social media and then tourism and economic gain until recently the strength, when the certain developments at one point would not show us the strength in our unity.


Bodlerize The arrogant writer could not believe someone wanted him to Bodlerize his novel by changing some of the unpleasant language.


And then y'all, so, for all my Dragon Ball Z fans, we got some news here. I'm going to read it in the Dragon Ball Z announcer's voice. Uh-oh, the next Dragon Ball Z anime movie has a title in the villain. And it's not good news for Goku. Uh, it says in order, it's Fukatsu, no F, whatever. And it's needed, and indeed, the first look at the movie reveals the return of Goku's most iconic foe, Frieza.  I never liked Frieza. I always hated Frieza. Um, Frieza's like, I don't know, Frieza, put it this way.  He was like a transvestite. He didn't know if he was gay or not. His name ended with an A. You know, not too many men's names end with an A.  I don't know. But the rest of the arc, he just looked like he was wearing lipstick.  You know, I just, before he bulked up later on before Goku cut him in half and all that stuff. But that says, look, Ann got this art in official movie summary from V Jump Magazine. And it says, an earth where peace has arrived. However, remnants of Frieza's army, Sorbet and Takoma, from the Japanese word for egg, arrive on the planet. Their goal is to revive Frieza with the Dragon Balls. Their dastardly wish is granted. The F that plans its revenge against the Saiyans is revived. Excuse me, as in Battle of Gods, it appears Fukatsu will be considered an official part of the Dragon Ball Z canon. Hmm, but I assume Frieza will come back several million times stronger.  Um, let me see. Seeing as Goku has gotten rather more powerful since the original, god damn, since he original battled the bad guy. Yeah, I knew I was reading it right, they wrote that wrong. Also note the return of Beerus, the unusually chill god of destruction from the last Dragon Ball Z movie. On the left of the movie, poster buff. The movie is set for a Japanese theatrical release on April 18th, 2015. Which means we won't get it until later on that year or the next year. There are no other details yet, but given how the last fight between Goku and Frieza went on the TV show, I expect the movie to be 45 hours long. Yeah, that fight was long as hell.  My favorite villain, as far as the series goes, because you know how the movies, like, they almost were like separate storylines. And it's like they didn't talk about them in the series, like the villains and what happened in the series. They didn't like, you know, it was like they were almost separate in a way. But still canon, I don't know. But my absolute favorite villain from the series was Cell. Perfect Cell.  I really liked him, you know what I mean? Just the way he laughed, his talk, the way he talked, everything was just really funny to me about him. And he was strong as hell, he had all their powers.  Like with, you know, like with Seth in Street Fighter 4 and Shang Tsung. You know, he's able to morph and everybody get all their powers. I always hated characters like that. But for Cell, it worked. Something about him, it really worked. That was something I could let go. He is my absolute favorite villain. Besides if you want to say Vegeta, you know what I'm saying? Vegeta is my absolute favorite character, period. Next would come Goku, but as far as villain goes, someone who never changed, became good, you know, that stuff. I'm going to have to say Cell. So I want you to post your links below. You post your comments below, let me know which one, which villain is your favorite in the series and in the movies. And movies is Broly. That, that third movie they did with him never happened as far as I'm concerned.   But that first and second one, your Broly is incredible. Broly could probably be anybody there. You know what I mean? Be anybody in the series, you know what I mean? But, alright y'all, let me know what you think of the movie coming out and what do you think of Frieza returning. So let me know what you think about Frieza returning and who's your favorite villain in the series and in the movies. Alright?


weekly YouTube live like yours to have a conversation with others. I think it's much more fun. Sorry. Oh, there we go. Good. My Yeti picked up. What did you say? Weekly like? I said, welcome to our YouTube YouTube, weekly YouTube live. I said every week, I should do this style. It's more fun. But I don't know why it's not linked to the right thing. Let me check. I see my team didn't link it. It says live. Can you see me live? It should be live. This is delay. This is delay. So I was live. Okay, cool. Hey, guys. Yes. I was like, it's not even live. Cool. We have a special guest today. Let me play one minute countdown timer. Cool. So welcome, guys. Hello. Hello. And we have everybody here. Welcome. Okay. All right. Hey, guys. This is Dr. Nian C. Lee. Welcome. Welcome to our weekly YouTube live today. We have a special guest, which is Ben. And Ben is also the owner of a brand which is called Seattle Data Guy. He's a very popular brand on LinkedIn. He also has his own YouTube channel. Quick introduction regarding what we plan to do today. And quick introduction. Hey, if you haven't, it's the first time you come to our channel. This is Dr. Nian C. Lee. And I am a director of product featured in Forbes and have helped 100 people blend the Dream PM job offer in fan companies, a unicorn startup and continue to get promoted as a product leader. Every Wednesday, we try to provide some free coaching to teach people how you're able to actually advance your career as a product manager or even break into product management. And today, we do want to welcome our guest as well. I do like your cat. Ben, I think he can stay. Yeah. And so I started chatting with Ben and I started to change the style of our YouTube live, start bringing more guests. And because I believe it's much more fun to have a third-party conversation and also share with you guys the real life experience. What does it look like to work with part managers from different functions? So behind scene stories is also very valuable and especially Ben himself, years of experience working as a data engineer, working for meta. He knows the insider, inside out of different big tech companies, how can they use data to make data-driven decisions build amazing product and from the engineering perspective. And of course, he also has his own data consulting company and very excited to learn about all the adventures he had, of course, very, very popular YouTube channel. Everyone should just follow him, just search Seattle data guy and find on LinkedIn or just find out in the description this video with hacking in all our posts. You should be able to find him. Awesome. So let's do this without further ado. Let's talk about today's topic, which is how the product managers actually work with data engineers together to build amazing product. So Ben, can you quickly introduce yourself? I've been making lots of introductions. Why don't you quickly introduce yourself? And then we jump into today's topic. At the same time, people will comment on the chat whoever is here, come and say hi in the chat, what's your name, where you're from, and what specific questions you have regarding data and product management and the combination between both. Okay. So Ben, yeah, turn it over to you. So tell us more about your background. Yeah. Yeah. I mean, I think you covered some of it, but yeah, I've been working in data engineering for the last, I think like eight or nine years at this point. Originally started working at like a hospital and then a healthcare startup, Facebook. And then all throughout that time, I'd been consulting at the same time. And so at this point, I'm just consulting and helping companies either set up their data infrastructure, set up their day strategy, kind of help them move forward, you know, so they can get the most out of their data. So that's my current focus. Awesome. So Ben, let's dive deeper regarding how the relationship between data engineers and PM work has changed throughout different experience you have, because you already work for a smaller company regarding you mentioned in the healthcare startup all the way to the one of the biggest tech companies. So can you tell us how the radiation had changed between small companies and big companies between data engineers and product managers? Sure. Sure. I mean, I think overall, at smaller companies, you know, the relationship generally was a little tighter, I think. And to some degree, I think that's because at this specific company, the product and the data engineering were very interconnected in terms of like what we did was directly going into the product. So instead of like generally at some companies where data engineering might just be part of the process of collecting data that then informs, you know, product managers, which features are doing well or things of that nature. In this case, the literal product was often being supported by the data engineers. So like the work that I was doing was actually being put into the product itself. So I think that was like one of the key differences is like, well, the actual product here, we're not just trying to gain information about the product. This is the product, right? And so I think that was kind of the key difference. To some degree, that could be more of the company that I work for, unless of the difference. Are you saying that when you're working for startups, your closer to product was able to really directly influence the product even much closer compared with when you're working for Meta? Am I right? Did I interpret correctly? Yeah, I think that's true. I think the other thing that was different was that the data engineering that I was doing, like the stuff I was building was literally going into the product itself. Whereas generally a lot of times your work done as a data engineer is tracking features that software engineers have created. So creating whatever pipelines to track whatever software engineers have created that then just goes to data scientists. And then data scientists use that to kind of inform their discussions with product managers. Can you tell us the differences between data engineer and data scientist? I personally was really confused about those two terms. I saw one person can play both roles, but through our sign conversation before this talk, looks like they are doing something slightly different. Can you tell us the differences? Sure. And I think for a while, there was definitely this expectation that data scientists do everything. When the role came around, it was also the era of Hadoop and a lot of things that were changing in the data management space. So there was this expectation that data scientists would both do Hadoop-type work as well as their data science work. And I think that's kind of when people realized it's really hard to do both. And so they ended up kind of specializing, whether it was on purpose or on accident, they kind of became this natural bifurcation between data scientists and data engineers. So data engineers shouldn't be the people who build and own the data sets that then data scientists use and rely on. That way, there's a little more focus on what's actually getting done. So which means, for example, the latest all the AI talk track regarding Cheshire BT is in the news every single day. And myself also use it a lot. I also make several YouTube videos about it. So if we talk about data scientists trying to leverage data to create like those machine learning algorithms, do you think they're more towards how we use data, which data scientists, not data engineering? Am I right? All the AI stuff is more science. Yeah. I mean, it's definitely more on top of that. Behind that, there are obviously somehow storing that data and accessing that data. And that could be a data engineer. It would depend on how they're actually storing the data. They might just be storing it like in some form of raw form. But my guess is they've done some level of like pre-processing. Like you've done training. They've done all this stuff where they're collecting all this metadata, and then that metadata gets stored somewhere. So that as you're building and testing out that model, you can use that efficiently and easily. So yeah. Very cool. Can you give us specific examples? For example, I think it's easier for the audience. Most of my audience are more PMs. We're not very hacky, but the easier to make it down for us. For example, use some product as an example. Some say what you describe if I interpret correctly. For example, one of the products I launched in the past, which when I spoke on your YouTube channel last week regarding the product use AI, which is machine learning, machine vision to help reduce car crashes, basic smart camera, detect the movement of cars, pedestrians, and figure out when they're about to hit a pedestrian and doing the like action predictions. So all of this, it began with metadata, like collecting, this is the car, this is a pedestrian, and this is also biker, and this is a crosswalk. Those are like metadata we collect. And then we actually at the time when we designed the architecture, we like locally store them. The analytics actually happened on the edge, which inside a smart camera, and then turned into metadata, which equals to, hey, this is like this pixel size equals to a car with confidence of 95% likely something like this is the car. And then with this geographical location, and then it happened to be on a crosswalk equals to this is not safe. And those are metadata, and then we send it to the cloud. You saying that from the data engineers perspective, you guys are the ones who decide how to create those metadata was a format of the metadata. Would we store a store in the cloud store in the edge or sending them between those two places? Is that am I am I right at the data engineer? Yeah, to some degree, that might be something we take on. Nowadays, there's been a further specialization in like things like MLOps. Thinking back to that example, and I talked about like building like a data product, you know, what that product did was like a lot of fraud detection in healthcare and things like that.  And then they handed like, like they did the research, they kind of like figured out what it should be. And then they ended up handing it to us. And, you know, it wasn't ready to go into production yet, like I was like, okay, here's what it should do. And then we implemented it, right? I think there's definitely been a further specialization there where it's like, yeah, now, you know, data engineers don't necessarily do as much model deployment and figuring out exactly like all how features should be stored. Things as much now you've got MLOps and people are more machine learning engineers. We'll take that on. But that's generally what happens, like generally data scientists, depending on the company, but a lot of data scientists do a lot of research. And then they'll kind of talk about their findings. And then some sort of someone that's more on the engineering side, whether it's a data engineer, an ML engineer will likely implement that and figure out how to store it and figure out how it should actually, you know, be operating in real life. Perfect. We, when we teach students, we always use like case studies. Would you be able to tell a specific case that may be a matter? Or your healthcare company, either one, either one to find whatever you feel comfortable sharing without telling too much confidential information, just high level use cases, right? In this case, I'm a data engineer and working with ABCD product. What's my day-to-day look like? I do this and this and this. And then I hand over the data to you this and this. And then when does PM actually come into picture? Can you give us a case that you give us some overview? And for people who actually in and put in comment in the chat, feel free to continue to put your questions here. I'm going to get back to you guys. I see Chris here, Leo. Hey, UG and Anchik. Are you guys, I see your questions here. We'll get back to you guys later. Feel free to put your questions here. Okay. So Ben, yes. Let us know, like specific case studies. So it's easier for people to digest. Yeah, I'm trying to think if there's like a specific sample. I mean, besides, besides the healthcare startup, I mean, at Facebook. Or you can use the healthcare startup either way is fine. Sure. Sure. Thinking through the healthcare startup. Again, like we built several products there. I think while I was there, we built, I don't see the two or three. I don't remember which one it was. I have to like my resume. So yeah, we built several products. And in both cases, like, you know, we kind of had this whole process where first, like, you know, oftentimes, essentially our PM would talk with our stakeholders. For example, we built something for like opioid tracking, tracking like how much people were prescribing opioids to see if there were like people that were over prescribing it. So we could, you know, obviously crack down on that. So, you know, our PM would talk to our stakeholders as well as like professionals in the field. So like actual doctors and dentists and be like, all right, like, what, what, what should I see what's normal to kind of understand what's, what's important, you know, what's important, what should we be reporting on? How should we be reporting on it? Like what would be useful? So they kind of gathered a ton of information. And at the same time, while they were doing that, our data scientists and kind of data and data engineering were kind of working together to prove out that we could basically meet some of these needs. So like stakeholders like we'd like, we'd love to see whatever some sort of heat map of like where over prescription happens. And like, okay, can we do that? Do we have the data for that? Like, do we need to get more data? So we would like go back and do a quick analysis, the data scientists might like, you know, put together some numbers. We might start putting together either some baseline dashboards based off those numbers and just proving that like, yes, this is possible based off the data that we can do. And so I think that's kind of like that first step is like figuring out, okay, what do you what do people want? And then what can actually be done based off the data that we do have for the specific product? And so then after we've kind of like gone through that cycle and been like, okay, we can kind of prove this. And on top of that, not only is it possible, but it's actually useful. Because I think that's the other thing. It's like, well, okay, it's possible. But maybe every like, if you were to put it on a heat map, and look at like whatever average prescription per county, it's the same for every county that's not useful. And so also like, you know, you're going to this that level of like, okay, is this actually useful? If I was an end user. So we kind of went through some cycles with the PM, the data scientists, you know, us as the data engineers, as we're trying to figure out like exactly what things should look for look like. And then once we've kind of like, I think set all that up, then we kind of develop, you know, your project plan, we think like, well, what's the end goal? Like, how do we want to launch this feature? Okay, this is our feature. This is how we launch. We kind of just move backwards from that. It's like, okay, what we'll need to get built to build this whole, you know, kind of product. And then just again, going backwards, and then essentially, we'll kind of develop from there. But that was kind of the general process of how we worked with the PM and that product. In this case, it was probably more similar to that of like a software engineer, I think, whereas like, you know, you might be testing and building products versus I think traditional, again, traditional data engineering at a large thing, you're likely, I like to say, you're kind of the middle child in the world. Well, you know, like the software engineers get to build things based off what the PM says, the data scientists kind of get a demand the data that they want. And data engineers just kind of have to give both people whatever that will make them happy. The software engineers just do what they want. They'll add new columns, they'll add new features, which impact your data model. And then the data scientists will want to analyze those new features, or maybe they want to analyze all features, but then the data's, you know, removed because the software engineers have removed it.  Yeah, I was about to bring up the relationship with software engineers as well. Interesting. Hold on, hold on. Let me break down a little bit. I actually have two questions, two follow up questions. Very, very, very meaningful and eye-opening, by the way. Now we know everything into and behind the scenes, how self such was made in different companies. And so now, Ben, specifically, for your health care case, where did you get those data? Like who won't even give up the data regarding how much like those prescription drugs is prescribing different places? Is the public available information? How do you guys even get it? No, no, it's not public. Under HIPAA, there are, you can, insurance providers can give data to third-party analytics companies. So there are some stipulations there that like, yes, you can totally get claims data if you are, you know, fall under a certain category and then like have met all whatever criteria the government says you must meet, you know, everyone's got to be HIPAA certified after that. There's still criteria after that. It's not like you can go to any analytics company. It needs to still, in theory, go to a specific type. But yeah, so that's how insurance providers are often interested in this as well, because they're like, well, we don't want our people being over-prescribed or, you know, we don't want to be, you know, we don't want to be the cause of something, you know, that actually with opioid, right, like the whole, one of the things that people found out, they're like, I think there's like one city I don't remember where in America that like it was like, they were getting like a hundred pills per day per person in that city, like, like it was something, something like crazy high. And so it's one of those things where it's like there, there is some validity because like, if you're an insurance provider, do you not have a little bit, if you're writing those, like writing those checks to approve that, do you not have a little bit of like, responsibility for being like, that seems weird. And I mean, it goes for everyone obviously, like in that chain. Very high. 100 pills per person per day. It was something crazy. Like you can look it up. There's an article, there's like a few articles about that. I'm honestly pulling that number out. I just remembered looking at it and being like, that is a crazy number. Like, yeah, that's an unnecessary number of pills. So that's like, I think that was one of the points that like, really, if I recall, like hammered home, why, like I think Purdue and several other companies got sued so heavily, Purdue Pharmaceuticals, not the university because it was like, this is, this was clearly, you know, this was obvious guys. So are you saying that the pharmaceutical company who, who produced, who manufactured those pills was, was sued or the doctor who prescribed it was sued? I think it was the actual pharmaceutical companies that, because like there was also some other things where they were like pushing it on, like there was multiple levels of things in there where it's like they were pushing it. They were saying it's totally safe. Like doctors are like, okay, cool. I think doctors were getting like huge kickbacks. So there's like layers upon layers for this. There's, there's a, I think there's a show called like dope sick. If you want to like see it in an entertaining fashion and not just, you know, read about it. But Wow. That's what's going on. And, and then insurance company was ones who actually people pay premium, but insurance company will cover those drugs cost if they prescribe too much and also impacted the health of people living in the city, whatever they ensure they need to pay out more money. That's how the business works, right? So that's why they're very incentivized to crack it down. Yeah, there's, there's multiple levels of why.  And by the time you're 65, you're on Medicaid. So the insurance providers don't care. Like they're like, all right, you gave us our money while you were healthy. And now that you're, you're, you're old and sick, you can, you know, um, yeah, I, I don't have the cells to do product management, but like, yes, this is the, the wonders of insurance and healthcare. Oh, oh, we just learned something new regarding how that, I didn't think that way. I'm just thinking about it right now. We're not getting sick. So don't want to get sick. But yes, once you're older, when you really need to pay people to go to the hospitals, they're off the hook. The government takes over. Yeah, because you're not working anymore. So you don't, you're not on your work insurance anymore, because you're not on your work insurance anymore. You don't need, you're not going to use that, that insurance.  Not Obamacare. I don't know what the actual term is, but that one. But even that, it's, you know, it's not great. So yeah, it's, it's basically the government's job after, after a certain age where it's like, all right, you're on, you're on the government's dollar at this point. Um, no, it's, it's a great, it's a, it's a great business model in terms of like, how much money you can make. I think if I recall, like those, like, what is it, like UnitedHealthcare or whatever, like after, uh, after, um, again, Obamacare went in, but I'm trying to remember the actual name. Um, after it went in, like, like tripled or quadrupled the size of those insurance providers over like 10 year period, um, in terms of like market share or well, uh, not market share, but, uh, whatever, valuation. So yeah, yeah, no, it's, um, it's a quote unquote great business. Um, so. Wow. That's what's going on. Wow. Do we have any comments out to listening right now? There's, there's no secrets here. You know, it's, it's all, it's all there. It's all, it's all, it's all there. Um. But most people didn't know how exactly they, they made so much money and actually tripled their variation or like three times. I don't like, I'm definitely pulling numbers out of here, but I know it's like stuff that if you were to look at, you're like, wow, that is actually, yeah. All right. If I would have invested in healthcare, I would have made a lot of money. Like don't invest in big tech, right? Yeah. I was like, don't even check now. Uh, drop a lot. So now let's talk about tech. Surprise, surprise, surprise. Um, data engineer is the middle child. I was, I was about to ask regarding how do you guys actually work with soft engineers because they're all engineers. So from PM perspective, we group you guys into engineers. Usually when we go into the, how do you work with engineers? Oh, that's how we do it, right? So group all of you guys together. Yeah. So now, so, so make it a little bit, break it down a little bit more. Are you saying that in meta, let's, let's, do you mind mention the type of feature you worked on? I mean, I was mostly working on internal, uh, enterprise, uh, solution. So like I worked on getting like data from like the recruiting solution that we have.  Um, like, not ETS. Yeah. I mean, there's an ETS component, but like also just like your general like, I'm trying to think, like, what would you call it? It's not a CRM.  Like where you're managing all ATX system. Yeah. Okay. Okay. Yes. That in ETS system. So yeah, like basically that. So just getting data on that and pulling it out and like also tracking, like how people are interviewing, how often do they interview who passes, things like that. So, uh, that was kind of the product that, that I worked on. So it was almost more, it was less, um, less about the product itself in this case and more about the process of like hiring people, uh, especially then when like meta at that time was like hiring like crazy. So that was like a major, a major point that they were just trying to to gather talent and figure out the best way to find talent and, um, you know, so, you know. So you build those product and, and focus the like internal product and then specifically are you saying that the car manager constant changing ideas and then soft engineers just keep on deleting columns of data was like, what happened? How exactly guys communicate that? That's weird. Usually you, I assume, well, at least in the interview, we will say the point as an interview. Oh, as a product manager will also define what's best for our customers, what kind of KPI when you track, and then we'll work with our engine and design the best solutions. So are you saying that you do it on the fly and you say delete stuff or changing our ideas and it's, it's not that it's done on the fly. It's that like, especially in things, right? There is an incentive to constantly build and change and try new things, right? Like that's, that's how you get promoted for, for everyone, right?  Software engineers need to build new things.  So some degree it's like the incentive of the process and there is a process, but oftentimes data engineers are like software engineers, I think feel like data, not necessarily data engineers, but like the process of getting data and tracking it can be a hindrance to that, to them building, right? Like for them, for their view, software engineers want to build, right? Like they want to build things that function and then it doesn't necessarily want to connect it. Like they're not going to like think about like, oh, I need to connect this for analytics. It's like, does it work, right? Like does the end user, you know, can they, can they work with this product? Yeah. So basically they build the MVP fast. Yeah. Well, MVP and even just the features like, Hey, it works. Perfect. It's, you know, great. You know, and then later on that some data sciences or some PM might come in and maybe they were, had some metrics early on, maybe they didn't generally they do. But overall that there might be some gaps in terms of what they're tracking because maybe later on they're like, we need to track this or, you know, Hey, we remove this feature or remove this column and I broke all my pipelines. So that's what I mean when I say that it's just like adding in data engineers into the process just feels like a slowdown to, to a lot of people in the whole process. Because like, okay, we could tell you that we're updating this thing and then we could give you enough time to update it or we could just change it and then like, you'll figure it out. So yeah. Wow. Wow. Huh. That's an attitude within the company. But isn't it supposed to be, okay, so I think we can start a secret big tech companies. Isn't supposed to be a collaborative environment and also isn't like that's why people thought, Oh, this will also attack that that's what it's causing, right? So people just keep on trying to do new things and then fix it later on. Yeah, I mean, like, I think that's definitely always a discussion, right? I think this was something that like, people called out in Twitter, like if people are like looking through the code base, they're like, Oh, like someone pointed out this, like, yeah, there's like 10 years of tech debt. And I think this was like employees internally. And, and like, they were saying I was like, well, yeah, because we're incentivized to build new things not to fix old problems. It's not that it's not collaborative. You know, there's definitely a collaboration, I think between PMs, data scientists, software engineers, I think data engineers can be the ones that can kind of get left out. This is why like, I don't know if you know Chad Sanderson, but like he's got this whole concept of like data contracts, which basically is just this assumption that like, hey, from the product, this data will be provided to you. And the only way you can change that is through essentially like some sort of code or some level of governance and not just like, Hey, I made a change. It's like, well, what if we like captured that change and made it like a, you know, some sort of code or version controlled system? Yeah, I always like the way I would often sometimes be reminded when changes were happening at Facebook was like, Oh, hey, we see you're connected to this MySQL database. Well, this column just got dropped. So good luck. Like I get like an update like as it happened. And so my job would usually run at 12 o'clock at midnight. So it's like, well, okay, I could make a change before that, you know, before that happens. But like, it wouldn't be a person. It'd just be like some automated system that's like, Hey, we see you have this, we see you rely on this. So we're just letting you know this has changed. So we dropped it in the middle of the night. Stopping. No, it's not in the middle of the night. I more mean like the pipeline itself will run in the middle of the night. So usually, you know, if they dropped it at 8am in the morning, you'll get that email at 815 from some automated system. And you're like, Okay, I got to change this pipeline before 12 o'clock tonight. And then it's fine. Oh, yeah. And I imagine to some degree, it also depends on where you are. Like if you're probably on the product side, I assume there's much more conversations because breaking a data pipeline that has far greater consequences, where it's like, you know, if it's internal people are probably like, Well, you know, we don't have as much data to deal with. And you know, maybe maybe they feel a little more relaxed. So I think there there are, you know, you're always going to have varying experiences depending on the team you work on. Yeah, I like specifically picked the team because I was like, I don't really want to wake up at 4am and get a call that like a pipeline is broken. And I must fix it now. Whereas like the internal team, it's like, Well, if that happened, if something broke, it's like, All right, we'll deal with it later. So, you know, This is what what a surprising to discover what it's required. So once it crazy. So we have audience Andre Andre Andre is actually one of my students inside of PMA. He said, Department of Management, Data Engineering, Healthcare, I'm sad I couldn't get it on time. It was tater for me. Andre, feel free to put your questions in the chat. Okay, we can highlight certain parts that you have your own confusions. Ben can like recover or like, show some insight for you later on. And we also see some audience from Paris. Um, Denver, Chris, Chris is also in Denver. So just like, Ben, you're there as well. Yeah. Yeah. Same, same, same location. Probably that's, that's your friends or your fans. Coming over. This is awesome. Let's see someone. Yeah, several people from Denver, another guy from Denver. Extension today from Denver. Everyone from Denver. Everyone from Denver. At your audience, just say, I don't know if I am. That's good. Good to hear everyone. I mean, I'm in, you know, my, my company, or yeah, my company named Seattle Data Guy. So, but if you look at my LinkedIn, it says Seattle Data Guy now in Denver, I think. So it's not like, there's no secret. D, D, D, D, D, D, D, D, D Guy. Nope. Nope. Nope. So when we keep the brand names, make Seattle Denver, we'll think about it. So when did you move from Seattle to Denver, by the way? When did I move from Seattle? Well, I actually, so in 2018, I moved down to SF. I was in the Bay for a few years and then COVID hit. That's what met her. Yes. Yes. Yes. They were like, you must move down. I was like, okay, fine. I mean, you're, if you're going to pay me to move down. And then I, I, I lucked out and found like a place for 1400 a month. And I was like, all right, we got a place that's not $3,000 a month. This is, this is fine. So, yeah.  Yeah. Talk about the tech move. What about tech in general? Uh, well, as we know, I just mentioned, I was in when working for a tech company, there's more, much more complexity than what it seemed like on the outside. When you move for, move for tech companies, do you think it's worse if you look back, move your entire family there and have a great career and later on move away from Silicon Valley? So what's your career? How do you decide and how you design your career? Do this thing worse if once you look back? Um, I mean, I, you know, design suggests that there was some plan. And I mean, like to some degree, there were things that I think I planned, like I knew I think consulting was going to kind of work out eventually. So I think I was always kind of doing that with that in mind. So I think in terms of moving, I mean, I think it's going to depend on a person's stage in life. It was an easy decision for me. You know, I didn't have, you know, I, I don't have kids. So it's like responsibility was low. I'm like, worst things that happen. I get fired in six months and I have six months more of my lease. And then I go back to Seattle, right? Like, so that's where I was like, all right, this is fine. So, so that, you know, again, with no responsibility, it's totally different. If you have kids and a family, it's right. Like making that move, making that, it's a much bigger risk and thought process that goes in there. Yeah, but I think, you know, if you're special, if you're, you know, at any age you can do it, but if you're younger and you've got like zero responsibility, why not? Why not just go out, take a job somewhere. If you think it sounds fun, if it's interesting, and you can figure out the rest of the details later. I think the biggest thing is like just make sure, I think it's Gary, I don't remember his last name, but he says like, you know, you either got to be learning or earning. And I was like, well, I'm definitely earning at Facebook. And learning. Yes. Yeah. And learning, of course. But like, you know, I'm definitely earning. So, you know, we at least know that one's going to be crossed off. You know, so it's just one of those, like, it seems like a good choice early on, just to just take that on. Yeah. Before I ask the next question, you show me your cat. Let me show you my peacocks. Oh, you have peacocks? Nice. Wow. I was going to ask, are they wild or they're your pets? Do you see it? I can't. And I do need to show off my peacocks. Yeah, I don't know. Can people see my peacocks? Well, I'm blind, I guess. Oh, now I see it. Okay, no, that's moving. I can see it. I was waiting for movement. I'm like, where's it? Where's the moving? Yeah, it's my peacock. No, it's not mine. Well, they come every day. They come every day. It's crazy stuff. Sorry for interrupting. Occasionally they come. I was like, nice, you show up on my YouTube live. This is awesome. Hold on. Let me let me plug in everything. Hey, Ben, I do want to ask you sorry. So I do want to ask you this question. So you talk about moving for tech companies, enjoying tech companies. And now we're going through COVID episodes, right? We're going through recessional past COVID, people that the entire world has shifted. Just like you moved to Denver, I moved to Miami, and discovered peacocks in my backyard, like crazy, crazy stuff going on. Now here's a dilemma. I'm not sure if you fail the same way. At least that's what I heard.  It's very hard to join tech companies now. Or at least they heard the news.  Maybe let me just do as a stub in different industries. Maybe do healthcare or oil gas. But there are two different types of career paths they can choose. So they can work on non-PM functions in tech companies, such as support, or any, or even self-support from data, using data as an example. Or like, if data engineer, they can be like self-support. So they're technical support, right? So they can then get into still join tier one company, Uber and TikTok. They're still hiring. They're still hiring lots of people. For product manager, product manager also think about, well, maybe I can join like, like doing operations for tech company. I have a friend and he works for BCG. He really want to become a PM. Very interesting. He learned a job at Google doing like finance, finance operations. But he didn't take the job. I support that decision. Eventually he joined a startup doing like what he really loves to do. Do you see this dilemma for data space in terms of the whole tech industry in general, what were more impacted in the recession space? Do you think people quit their, the temporary, temporarily past the dream of doing what they love to do? For example, it could be a data scientist or data engineer in a tech company, then they took something temporarily in a different track. Do you see this happening in your industry right now? I don't know if I specifically see that. I think usually what I see is people who are maybe earlier on in their careers, maybe they like want to be a data engineer.  Most people I think go into their data analysis or something similar to that first, just to get some experience in the data world. And then kind of shift it over later on. And that's usually because data engineering just has so many skills that are required that just weren't taught in school. And so you kind of have to do some work on those things. And data analysis or data analyst roles are generally the easiest place to get it. So that's usually kind of like the non data, data engineer role I see. I think the other thing I'm seeing is a lot of people wanting to do more consulting. And that could be obviously some bias compared to what I do. I don't talk too much about consulting on LinkedIn until recently because I had a lot of people reach out to me on it. So that's when I was like, okay, let's talk about this. Let's see if people are interested in doing consulting. So that's something I think I'm seeing more of, I think partially because if even at Facebook I can get laid off, some people are like, well, why not take a risk? Why not work for a startup? Why not start a consulting company? Why not do something for myself? So I think that's kind of a shift that I'm seeing again. And the same thing is like just as much as like consulting is like, well, why not work for a startup? Right? Like if it's the same risk of getting fired, it's like, you know, why not have some fun, do something interesting and new. And there's still a ton of startups being funded. I think I just saw Madrona invest in like a few dozen or a handful yesterday or something. I saw a seed series that was like $7 million for a seed series around. So I'm just like, dang. That's big for seed. These seed series are getting big. I think it's because it's in the, you know, yeah, in the AI space. So for multiple reasons, right? Like the talent is very expensive and things like that. But yeah, it's, you know, there's still a lot of money I think floating around in the startup world. So if you've got some interest there, that's also very open. Yeah, exactly. Actually, so since I moved to Miami, open my entire world view is crazy. So this loss of investors actually during the pandemic moved to Miami and never want to leave because we experienced the winter. The Miami winter, very nice. We never want to move just like me. So when I started talking to those investors and recently told me a deal, we should say surprise, totally surprise. Basically it's an intersection between the crypto and WebStreet. You know, lots of WebStreet. Originally Miami is very pro WebStreet. All the WebStreet people move here and now WebStreet went down. AI went up. There's a company with a combination between AI and WebStreet and just have those kinds of concepts like early rounds or guess what? And like before AI become a thing, you know, like crypto went down for a year, right? Before the AI become a thing and crypto went down, they're not even able to learn some kind of fun. It's like some like 50K paycheck, not paycheck, 50K investment check, right? Nowadays they oversubscribe just because there's AI came up. There's also there are the very few companies who can do a combination between AI and WebStreet. Now they oversubscribes and they don't take investors' money anymore. So those kind of companies continue to grow. Yeah, you're right. When you are like waiting for a big company to hire again, maybe it's a great time to join a small company because you're right. Same kind of risk getting fired anyway. You're losing your job either way. So why don't you do something fun? So because really you don't have that much opportunities anyway to do something fun while we're all doing recessions. It's time to just do anything anyway. Yeah, I think they often say like recessions are the time that people like tend to get their MBAs as well for that reason. It's like, well, might as well do this now. We got the time. So although with MBA costs these days, it's like, I don't know if that's true anymore. It's crazy. I have different opinion regarding MBA. For people who have lost a student who want to become a PM, right?    If your purpose is trying to become a PM, don't get an MBA because only 7% of Harvard MBA became a PM. That was when tech was hot. I'm not saying right now. When tech was hot, they did analysis. Only 7%. And then MIT, 14%. That's it. 1,4. Not 1,4. 1,4. 14% MIT MBA is a very technical thing. You can put a manager. Not even the Google level of a manager. So in the past, among my MIT classmates, that was years ago. Don't guess how old I was. That was years ago. I only have like three MIT classmates who joined Google from the business school. And then one of them told me that, hey, Nancy, do you know that interview for Google three times? That this is the third time I got in. So it is actually like MBA doesn't give you a competitive advantage. The real competitive advantage is the experience you had. Even if you were for startup, you have launched something amazing. And especially it can be really amazing. So I said, well, during recession, we still turn our startup from almost no funding into next level, creating so many end users. I believe that's a better career path compared to people, oh, you know what? During recession, let me just hide doing like finance operations like at Google or Uber, finance operations. But you got MBA, you can do something greater. Why don't you join the startup, create something really amazing, like amazing product, regardless what your true passion is, could be a data engineer or whatever, um, product manager in those startups. And I think the better career path for lots of people. And people really just bought into the name of a bank company by doing finance operations. What's the purpose of doing something so boring? Well, personally, I think finance operations is the most boring work ever, except like tax preparation and counting juggles. So let's see any questions we have from the audience. Question for BAM, KUG, by the way, this is someone from YouTube, KUG Studio. I love this name. Question for BAM. An example of a good PM interaction and experience or a bad one from your seat that you how can a PM use data to the best? Okay. So two questions. Tell me, tell us, tell the audience examples of your interaction with good PM and bad PM, what does it look like? Then we go to the next one, we should say examples of how data can be used, use the best. Okay. So good PM, bad PM, let's do this. Yeah, I don't know if I've worked with a bad PM per se. Maybe a bad project manager, which is obviously a different thing. Different kind of PM. So it might be similar though, where it's like a good PM, when you have a good PM, you don't notice, but when you have a bad PM, you notice kind of situation because that's the case with project managers. That's how you explain it. If you have a good project manager, you don't notice the project manager or you don't even realize that things are just going. There's a flow and it's good. But with a bad one, it's like, we haven't moved forward for three months. Something is bad. So yeah, I don't know if that's the same with like good and bad PMs. I think, you know, usually I've, you know, people who have been pretty on point and pretty much like, you know, doing a good amount of like, using a combination of data as well as discussions with real people. Because I think it is that combination, right? Like you use the data to drive like a level of the certain products you develop and features you develop. But I think on the same time, you have to talk and understand people. Like I said, I think I referenced that earlier with the healthcare product where it's like, yeah, like, let's actually talk to people and understand what is useful to them. We just give them a number. It's like, okay, can they make a decision off this number? Like, what are they actually doing with it? Okay, if we give them this list, what would they do with this list of people like trying to figure out beyond just, you know, okay, we built this feature, right? Like, okay, but how is it going to get used? Is it useful? So thinking about those things. Yeah, getting the user insight, which is foundation building amazing product. Hey, I wonder what are questions lead to another great question. As as an engineer or data engineer or any kind of data scientist or engineers in total, in general, how much was the interaction with customers? When do product manager actually bring you into those conversations? Yeah, I don't think we had too many direct conversations with customers. Again, we're generally just kind of held in the back. You know, I think maybe a little more at Facebook. I might just because at Facebook, you're expected to have a little more ownership. So to some degree, maybe there's a PM that's kind of helping decide what gets built. But to another degree, it's kind of like, yeah, but you also kind of need to have some ownership of that as well and have some discussions and and be willing to state your opinion. So if Facebook, I think it happened maybe occasionally a little more that you talk with stakeholders and customers. But at the start up, it was like, someone else would go talk to the to the real people, we'll just build whatever needs to get built. What would you wish could have happened? Let's define this. So let's define a really good product manager. What do you wish the good product manager would do to, I don't know, anything to enable you talk to a customer to bring you early in decision making process or even like, I don't know, deliver the KPI earlier. So what would you wish the amazing define the imaginary amazing PM? What would they do in terms of working with you guys? I imagine this is different for everybody. Like I do like getting a little more involved with discussions just because I like knowing the why it's like, okay, why are we building this, you know, not just let's build this. But I also know like, and this is one of the things I think I've even talked about on my channel. It's like some people like data engineering, because you can kind of just hide and, you know, you do your work.  I've done my job. And so I think that you'll find people all across that spectrum where some people want to know why and they'll want to know early. And yeah, it's kind of nice.  So I think that kind of ranges. I see, but from your perspective, you love to know why I get involved in decision making process. Yeah, yeah, I think having that why is always helpful because otherwise you just kind of feel like you're doing stuff to do it, but there's no, you know, like, why am I doing this? Who's, who's this, who's this driving value for? So yeah, it's actually, I think that lead to entrepreneurship of yourself. That's why you start your own YouTube channel, start to have your own consulting business. And I think in general depends on how they, what the definition of successful career, right? So I was like you, when was I started as an engineer, systems engineering, working on oil rigs, can you imagine me oil rigs? Hey, totally, totally. Exactly, the hard hat, the helmet. Yeah, so I feel very disappointed if I was left out in understanding why, if I, if I didn't know what the bigger picture as an engineer, I feel very, very annoyed. I think it's based on what people's definition of long-term career success, that leading to what they believe is a good PM need to tell them what to do. Like, for people who actually don't want to be bothered, probably their definition of successful data, data engineer is to be the expert of creating best data set in a short amount of time, get it done and deliver. For people who want to be growing into entrepreneurial tracks, probably why I want to know why, or I'm just whatever, with a hammer in the tool set, you don't even know what I'm about to build together. I think that that's the difference. Cool. So now let's move to next question. This audience have a really good question regarding, from your seat, how can PMs use data the best? I'm trying to think, like this is such a broad question.  I mean, and engagement is kind of like this baseline metric that everyone can use. I think on the flip side, there's defining like your true North Star metric, but also making sure you think about whatever your countermetrics are. I think this is something that sometimes can get missed, right? Like in countermetrics, generally are like, oh, well, if our goal is growth, okay, cool.  But like, when you look at churn, you're like, wow, we're losing people very quickly. I think that's usually the classic example. But yeah, I think having that, and then maybe, you know, especially now as we're getting into a world where people are trying to be hopefully a little more concerned about more than just, you know, the numbers, you know, thinking about, you know, what other impacts are you having besides like growing products? Like, okay, we're growing a product, but we're, you know, with like opioid, that's a good example, right? Like, okay, we're selling more. Yeah, but we're selling, you know, one of these towns in these cities is getting 100 pills per day per person or something crazy, right? Like, that's not a good growth thing. Like, so I think, I think also thinking about what are the negative effects of whatever your positive metric is, your true North metric is. So yeah, this is awesome.  This is amazing. Actually, I was doing here. She is a and many of these people actually all women surprised. Well, I have a male man in my program, but happened to be all the data of many students, they became data product manager. Yeah. And yeah. And some of them land job offer in a healthcare industry, some of them in the like, like a fraud detection industry. And also some of them then offer from like payex, those kind of like travel industry Expedia as a data product manager, which is similar to sounds like what you described, like they define what the data product look like and trying to understand what the North star metric different things with own data product.  Exactly. I would say North star metric. It's like, boom, my mind is amazing. Yeah. Just say what PM the same phrases we're using in our terminology as well. This is amazing. Awesome. Cool. So then let me see. What are the questions you we have? We also have questions from LinkedIn. LinkedIn people may need to say hi, Chris. Hello, hello. Thank you for hosting today's band. Thank you. Thank you for joining us. Awesome. Okay, great. Cool. So we are towards the end of this talk. Anybody if you like today's talk, make the panel to make sure to comment in the description and let me know if you want to do more of those kind of like bio chat, fire chat style of our YouTube live and if an additional question for BAM please comment below as well. Make sure to share this video with any like people who are who are interested in the intersection between data and product management. And also one last question to you, Ben, how can people find you if I have more for our questions and in general? Yeah. I mean, you can, you can pretty much Google the Seattle data guy and you'll see my probably newsletter, blog, YouTube, all on it, et cetera, et cetera. Awesome. Cool. Awesome. We're also going to link Ben's YouTube channel in the description of this thing. And we also have one for LinkedIn. We'll link the proper one for each channel and feel free to reach out to him as well. Thank you so much for joining us, Ben. Thank you so much for your valuable time and insight. Awesome. Yes. Thank you. Thanks for having me. Great. Cool. All right. Talk to you soon. Have a good day. See you guys now. Let me end my streaming.


Mary Barakam, it's alongside Brian Cashman. Brian, baseball is coming back in 2020. Was there a point in time when you thought you would never hear those words? Of course.  And there's a lot of question marks along the way. And unless you were in the negotiating room, you had no idea if there was really something that was going to play out or not. What are some of the protocols that are in place right now to try to keep people as safe as possible? Wow, there's a ton of them. More than we have probably to talk through on this Zoom call. Major League Baseball has implemented a hundred and some team page protocol agreement where, you know, clearly social distancing and testing and intake testing and is vitally important. You know, you're transforming a large facility in our case, Yankee Stadium now into a much larger clubhouse, a much larger training room and utilizing the entire facility to ensure the safety of all personnel, players, staff members and support personnel. And so it's based, it's definitely going to be a challenge for a lot of people. Doug B. Hart, who runs our facility, has been doing a Yeoman's job of trying to make sure this all works. As you know, we tried to make Tampa our home for Spring Training 2.0 until the COVID outbreak hit in Florida. So we had to transition up to Yankee Stadium last second. So once you got the two facilities in Florida ready, now you got that practice in so he's doing New York as we speak. Brad, how will it work? What are some of the logistical challenges involved in making this work for the players? Well, I mean, it's the biggest thing is to try to people, you know, make sure that you're in a position to stay COVID free, or as COVID free as you possibly can in a pandemic environment, you know, because you're going to have people that will test positive, regardless.  Clearly, thankfully, in almost all cases that we've experienced thus far, the symptoms have been really mild. You know, and so we've been able to thankfully avoid something severe that you've seen in the public arena throughout the world at times. And we're very thankful for that. But, you know, but yeah, our medical crew, whether it's Mike Shucker and Tim Lentech along with, you know, Dr. Lee from New York Presbyterian, you know, they're really doing an amazing job of trying to make sure that the facility is clean, ready to go, and the safety standards are in place that will protect all. Brian, what will the schedule be moving forward? They're coming in understanding on Wednesday to get tested. What will you do thereafter? Well, we essentially we started our intake testing protocols. And so, you know, I got mine, and much of our staff members on Saturday. And then they have continued yesterday, which was Monday at Yankee Stadium, and they'll continue throughout the rest remainder of the week because trying to get people from all over the world back to New York, and then get through the intake testing procedures that Major League Baseball has set up. You know, where there's a saliva test and a, and an antibody test, for instance, and then they send all those results out to Utah and then the lab, which is I'm sure slammed currently right now as they process all these teams is consistently coming FedEx packages of samples, you know, it takes about 48 hours minimum, if not longer. And then once you're clear, you're in. So thankfully, I can report unclear. And, and so far so good on on our testing, but we, we still have a, you know, the player population, most of which have to have to get their clearances, a lot of them have taken their tests, but we're still waiting for the end results on those. Has anybody in New York, New York so far that you know of in the organization tested positive? We have COVID positive tests, you know, since, you know, the pandemic hit, obviously, whether it's through our minor league player pool, our major league player pool or staff player pool and other ends front office so we've experienced like I think every walk of life, you know, positive COVID tests but thankfully from that we've really only had and it was back in spring training we really only had one employee, for instance, it was one employee that really was struggling for a good 10 days with it and needed some hospitalization that was back in March. But everybody else that has tested positive for COVID, their symptoms are extremely mild or, or really no symptoms at all and more of a surprise they actually tested positive. And, and sometimes you're testing because you get in contact others who had COVID and to some sums dismay the test results have come back which is why you have COVID or you've been exposed to COVID so. Yeah, we've we've experienced positive COVID tested throughout the organization. When do you expect the workouts to begin. I think on a limited basis we could have something as early as Thursday you know people, you know, who have passed and get some some limited workouts in at the facilities as we're continuing to try to get up and running but either the official day will be Friday or Saturday we're still letting stadium ops do their walk through and finish off the sterilization of the stadium and all that and all avenues so certain certain parts of the park will be more ready than others but I think come Saturday at the latest and maybe Friday at the earliest would be the first official. But again the question mark is how many of our personnel will have gotten the test results back to have full intake. And those results allow us to have a you know as close to the full squad as we possibly can. I imagine the workouts are going to be a little bit different than they were in the regular spring training so Brian what will be different about what you guys are able to do when everyone is in fact clear. Well, you know, because we had to pivot, you know, last second from our player development facility at Himes and the major league facility at GMS field. Those are going to be our two locations initially but then when the outbreak rage rage the way it did down in Florida. We pivoted last second so we're going to utilize Yankee Stadium for the entire unit to start out because Granton which will be our alternative facility will not be ready for a good seven to 10 days or more. So we'll utilize the busy clubhouse the auxiliary auxiliary clubhouse and the home clubhouse will utilize the concourses and the seating and the dugouts.  So we're going to maximize the footprint of Yankee Stadium to the benefit of our players health as we move forward and manage this, you know, large contingent that is going to experience spring training 2.0. Guys have been working out but it's not the same as being on the field and competitive play what's your level of concern about additional injuries because guys were ramped up stopped and are now starting again in a quick fashion. Well it's of course it's going to be a concern. I mean obviously a smaller and there's a reason we've had a six week or more spring training forever and and you know there isn't a custom level of ramping players up and and and so players have in most cases I think done as good a job as a possibly in their isolated environments to just try to stay as close to physically ready as they possibly can but you can substitute that for game reps. And so I think Aaron Boone and our, our staff are going to try to, you know, get as close as they possibly can to simulate some game actions over the course of this three week period and, and that's going to, you know, put a stress on, on all aspects of the body. Obviously designed to get them ready, but it also expose those who might not be ready and, you know, we're certainly going to try to do everything our power to avoid the injuries that will come but they will be coming no matter what for all franchises. In a smaller work, we zone of three weeks and getting ready for a 60 game sprint schedule over I think it's like 66 days and so it's, it's going to be a challenge. Our medical team and training staff obviously are, you know, looking forward to meeting that challenge the best of their ability but, but it's definitely last time we did this was, you know, obviously in the strike short the season, and there was some high level of injuries getting out of the game in season because of it. Do you anticipate intra squad games and competition against other teams in the area prior to the first game of the season or will it simply be your guys playing against each other. I think definitely inner squad games. That's not a medic without a doubt and then from a baseball operation standpoint we are open to doing, you know, taking advantage of the three exhibition games that we have the ability to play if we can find a partner, and I have to say just, you know, the northeastern GMs about those possibilities but at the same time I don't have clearance yet from ownership and or our stadium ops. I think it's a great opportunity for a walk through for a stadium ops if we can play some exhibition games. So I think there's check boxes that can be checked in a positive way for preparing, you know, for a real, you know, you know, competition, you know when the season starts and so our stadium ops would get ready and go through a walk through that way and I think it's from the baseball standpoint. Any games we can play against an opponent prior to the lights camera action starts would benefit us from a baseball standpoint because inner squad can only take yourself so far, but the actual opponent, you know, that's not yourself. You know, that's where you're really going to, you know, get some growth I think going to benefit from it and so obviously when our season starts I want to hit the ground running and be 100% certain that we are as ready as we can be. Not that anybody's going to be as ready as they can be but but I think those exhibitions would be important to do so but we're still talking through that matter. The news trickled out the other day that Aaron Judge had been swinging a little bit. Can you update us on his status? Where is he at right now? Is he ready to play in games? Well, I think the next coming weeks will determine that. Where he's at physically is he feels good.  And so I think, you know, this next three week period you'll see him right away being dropped in the deep end of the pool and facing live pitching and seeing where that takes us. So, there's a great deal of optimism that as long as there's no setbacks that he showed at this early point, you know, prior to spring training 2.0 starting it appears that, you know, we can dream that he, his words will ring true when he said that he would be ready for opening day, despite this injury. And because of COVID and the delayed of our season that that that looks like it is a real possibility and hopefully it can be. Will John Carlos Stanton, Aaron Hicks, James Paxton said he had been throwing some bullpens. Do you expect those guys to be ready to go at the start of this new season? Again, without setbacks, I think there's a lot of optimism of Paxton appears to be fully healthy and his workload and rehabbing from his off season surgery that happened late and and and in terms of Aaron Hicks, his reconstruction of this Tommy John I don't think as much of an issue as as evaluating over the coming three weeks where he's at the physical condition standpoint because again these game reps, same with Gene Colestanton, these game reps he's I stand I believe is is healthy and you know, probably definitely DH consideration, you know, as long as the next three weeks go well, but in terms of Hicks in terms of Stanton in terms of judge in terms of all these players I think that the bigger area of concern or issue would be where they at in their physical conditioning side. And, you know, with the stop and start type sport sporting activity baseball promotes on the defensive end on the on the offensive end, you know, you know, where all of a sudden you got to kick it in the gear and from a stagnant position and how your body reacts to that on a day in and day out I think that's going to really tell us a lot so I think there's optimism that all those players and all of our players for the most part should be, you know, knocking on that door is being game ready by by the bell ringing but I think the three week period that we have will be taken advantage of evaluating if that's truly the case. Brian, this is going to be a season like we have never seen before, knowing that it's more of a sprint as opposed to a marathon. How does that change your job right now.  We didn't approach, you know, we're in this thing to win it. We didn't approach it from a development standpoint for prospects other than we do have prospects on our 40 man roster that, you know, you know, still have some growth side and development side as they come up through the minor league system, but we didn't add any non roster high end prospects that were either coming right out of the draft or, or, you know, recent signs there was a lot of speculation players like a Jason Dominguez or things of that nature we didn't do any of that because ultimately the eyes on the prize which is we have a 60 game sprint in a COVID environment to try to qualify for the playoffs and take a shot at, at a 2020 World Championship title and, and we felt it was best served by, by, you know, hoarding as many players that are in a position to contribute at the major league level now. And, and because of the anticipation of injuries the anticipation of, you know, being exposed to COVID from time to time and that we're going to have to adjust on the run that this roster would be best set for, you know, people that can, can hopefully hit that as much as we possibly can rather than, you know, try to develop talent that, that we're harnessing for the future so that's how that's basically how I think from the front office standpoint we've approached this thing. You're ready to go? I mean we're trying to be, we're trying to think of everything that we possibly can, and we're trying to stay connected to, to the other clubs, to kind of cross check what they're doing versus what we're doing and, and keeping our ears to the ground, whether it's scout on scout or, you know, GM to GM or manager or coaches to manager and coaches on the, in the other environments to find out to make sure that there isn't any stone we haven't unturned and, and if somebody's got a better idea or a good idea or a good practice that we have utilized to this stage that we can quickly adopt it to so we're going to be as ready as we possibly can and we're looking forward to testing the waters. Brian, thank you so much for the time. I look forward to seeing you at the ballpark, even if it is from six plus feet away. Same here.