Fort Laramie, starring Raymond Burr as Captain Lee Quince, specially transcribed tales of the dark and tragic ground of the wild frontier, the saga of fighting men who rode the rim of empire, and the dramatic story of Lee Quince, Captain of Cavalry. This one's fresh killed. And fresh skin, sir. How many buffaloes we found this way? We come on ten with this one. The men are fanning out, looking for more. They wouldn't be far away if there are more. They're right dumb, aren't they, Captain?  Well, couldn't call them crafty, but they're half-blind. Can't see trouble when they're heading right into it. Little tenant Cybert's back from the agency yet? Well, yes, sir. He brought the wagon. They're loading carcasses in it back by the wall. They better get a move on. The meat'll cook in this heat. Captain, you got the feeling there's something wrong? Wrong? Well, I've seen engines kill buffalo before, lots of them. But I never seen them leave this much meat on them. Maybe agency life is making them lazy, Gorse. Maybe their bellies are too full. Now, you don't think that, Captain. I sure don't. I'm gonna talk to Mr. Cybert. Oh, uh, are all of them cut this way? I think so. I didn't rightly study them, though. Then study them. All of them. Let me know what you find. Yes, sir. Have any trouble getting the wagon, Mr. Cybert? Oh, oh, no, sir. The agency ain't glad to know we were bringing meat in. That seemed odd to you. Well, no, sir. I never saw an Indian agency that couldn't use food. Neither did I. Oh, excuse me, sir. All right, man. You can move the wagon. I'll pick up the rest of the carcasses. Just a minute. Yes, sir. I'm gonna take a look at these. Hold on a minute. All right, man. Carry on. Yes, sir. A lot of waste there, sir. Yeah. Yeah, a lot of waste. How far did the agency? About five miles? That's right. You went there. You got the wagon from the agent. He said they'd be glad to get the meat. That all he said, Mr. Cybert? I think so, sir. Oh, one thing he said when we first rode up. Yes? He asked us if we'd been engaged to battle. Uh-huh. Said that early this morning, you heard a lot of gunfire. Yeah, I bet they did. Captain, wait, sir. Yes, Sergeant? Carcasses all of them, like you said. They're all cut the same way. Skinned with the hump ribs cut away? And that's all. The men locate anymore? No, sir, just the tent. According to Mr. Cybert's, the Indian agent claims he heard a lot of gunfire this morning. Well, it was a clear morning. The sound would carry all right. You saw the wagon tracks, Captain. Yeah, I saw them. Tell the men to get a move on with their loading, Sergeant. Form a detail to haul the carcasses to the agency. Yes, sir. We'll rendezvous at the fork of the raw hide and proceed back to Fort Laramie. Yes, sir. Captain Quince, what about the wagon tracks? All right, Jenkins. You see these tracks here? The fresh ones? The wagon that was just here. That's right. Now, over here. There. You see those? Yes, sir. They're not as fresh, but you can sure see them. Our wagon wasn't over here, Captain. And it wasn't down there where they're loading now. Or over yonder where the last carcasses were found. Well, that's right, sir, but... Indians don't hunt buffalo with wagons, Mr. Cybert's.  From its horns to its chips, Indians use all the buffalo. You think white men did this, Captain? I'm thinking white men. And if buffalo hunters are moving up to the high plains, we got trouble, Mr. Cybert's. That's reservation land, Captain. That didn't make much matter to them, Major. You seem very sure this is the work of buffalo hunters, not Indians. If it's Indians, they've changed their whole tradition of hunting buffalo and killing them. I tell you, these were fresh-killed, and the only meat gone was the hump ribs. Well, that's the best meat. To you and me, yeah. But the Indians eat everything in a buffalo, including... I know, Lee, I know. What they don't eat on the spot, they take with them, even the horns. Always use the horns for tools, implements, don't they? Well, always. I still hope you're wrong, Lee. It's a small hope, but it's there. I'd like to be dead wrong, but I saw too much. And the Indian agent heard too much. The battle? Remember, Texas, to get a clear morning, you could hear those buffalo guns roaring for miles. Enough of them? Sound like a pitch battle. Wonder if they're still packing those old sharps 50s. They're awful heavy. Gotta be. They shoot out slugs, 125 grains of powder, 600 grains of lead, sometimes more. The army struggles along with 450 grain slugs. We're not killing buffalo. No, we're not. You know the position the army's in as well as I do. White men aren't allowed on reservations to hunt, to mine, to anything. We can warn them if we see them before they move into Indian territory. If we catch them there, we can run them off, bring them back to the guardhouse. But we gotta see them first. We may not see them, Major. Until it's too late, we may not ever see them. And then the army will be in another position. What other position? Fighting a war. Here, sirs, we can load it. Powerful heart, you're sitting here.  I hear. Hey, soldier, let's hear the subtlest storm. That's it, mister. Much blithe. You got yourself some knife there, ain't you? Sharp as your eyes, soldier. Straight blade, huh? This one has got them curved too. They're nice. You like curved knives better, do you? I like what I need. Sometimes I need a straight blade. Sometimes I need them curved. What kind of man's got a need for knives, straight blade or curved? You golden me, soldier. I'd be a fool to go to man sharpening a fine knife. You would.  Fine edge coming. Fine edge. It's your business, cutting things? Let me show you that curved blade, soldier. Now, look at that. Isn't that pretty the way it half circles? You think it's pretty. It fits your neck, soldier. Right close and neat like. Now, that's what I call pretty, the fit of it. Pretty enough? Looks dull to me. It gets dull, cutting. Before I cut a man's throat with it, I'd see it was razor sharp. I will. I'll tender that right now. But I'll keep that straight blade handy. In case I run into a soldier who wants to go to body. I knew a man like you once. Looked the same, acted the same, talked the same. He was from Texas. This man I knew. A lot of good men from Texas. This man, he was a skinner. A lot of good men are skinners. This man, though, he got himself killed. How's a man gonna get himself killed, skin and buffalo? He made the mistake. This Texas man going into engine territory, went up into the engine nation, got himself killed. You don't know nothing about skinning. I heard about this, man.  Dumbs can be.  I make $50 a month of my keep. With that, I get 50 cents a hit on every buffalo I skin. You do it fast, mister? After I do it, the more money I make. I'm not sure I'd admire to see you at your work. Yeah, you would. I would. I never seen a real good skinner at work. You mean? You wanted to please a body. You could tell him how you said about your work. You thinking about turning skinner? Oh, I don't think I got the gift for it. Of course, I'm a will in hand and all that. How are you unthinking? I'm not too good to tell the truth. You might make a skinner's that. The thinking part, what's done of it, that's the hunter's job. Old Jake Cuppey there. He's got to find the herd. Do the shooting. Jake Cuppey? In the subtlers, he's buying lead now in powder. He's got a line on a big herd. Where? What do I care? A big herd, soldier. He'll get me there and do the killing. What I got to do is traipse after him and skin him. You was going to tell me how you manage that. You see, he worked with a good hunter. That comes first. Old Jake Cuppey, he's good. He shoots them right in the lights. Lights? The lights, the lungs. Now here, I thought a good hunter would take aim on his heart. The heart? No. You hit one in the heart. Even square in the heart. He's going to run all over on you before he dies. Charging around, pouring the earth, carrying on. Don't need a skinner wasting his self-moving all over. I can see that. You hit one in the lights, soldier. He may take a step at you, but no more than that. He drops right on the spot. You know how I mean? Skinner don't go to first one spot, then another. Well, he don't waste his self. I understand. And a gift you talk about. I got it for fair. I come on him. At first, I rip him down the belly from the throat to the tail. With a straight blade. More than likely, yeah, yeah. Then I cut down each his legs. Go around his head, clean up to his ears. Listen here. I figured the curved blade there.  I right away set to roll the skin back. Just first started. Then I draw a rope tight on the little flap of his neck that's free, see? Uh-huh. And I make the other end faster the team and, you know, I kick them up. Then pulling that away, shook that high right off in that animal. And that's a sight. I'll tell you that's a sight. I just bet it is. $0.50. Every time I do it, I skin this artist as high as $0.50 a day. Now that amongst the... Well, old J Copy usually does that counting up for me. I guess you think a lot of Mr. Cuppey, huh? What I gotta think are him. I like Skinner-Soldier. That's what I like. You putting up here at Ford Larimer's spell? Tonight, anyway.  As long as you're here, I just want to learn all I can from you. That's all. It's a good life. A lot of good men are skinners. Jake Cuppey, mister. How's that? Your name. It's Jake Cuppey. You don't want to steal up on a man a disease captain. Mind make him edgy. I make you edgy, mister. I'm getting over it. Sit down as long as you're here. Oh, here, I'll move my rifle aside. You got your eye on it, too. I've seen Big 50s before. I declare it opens a man's eyes, stopping off at an army post. First you tell me I'm welcome to put up with enlisted men here, and then the only ones that come poking around are officers. That's all?  Lieutenant claimed he'd never seen one before. Mr. Cybert's never saw a buffalo hunter before. Well, he's seen one now. Where do you find them? Like him, so full of book learning. We find all kinds, mister. Yeah, well, you found one there. Now, he's up on all the law in these parts. I'm not talking about your army law now. I'm talking territory law. I think that's how you said it. Something about there's a time of year you can't shoot through what Lieutenant calls wildlife. There's a law. About hunting? First territorial assembly passed it. It's called wildlife conservation. Well, I declare it. And here I thought the army was a shooting outfit. It is, mister. Now, I'm going to tell you what I told the Lieutenant. You're going to make laws out here. You make them about the engines. But you leave a white man to his work. You hear? Must be you've shot up all the herds in the South Plains. Oh, I wouldn't take all the credit for that. Others got their due coming. I'm gnawing at you, Captain. Same way you're gnawing at me. You spoke your peace. You're wrong, mister. That's another thing. I'm almost never wrong. There's a treaty law that says you can't go into Indian territory. That means all the land north of Fort Laramie. I'm getting to my word about the army. Ain't they doing any killing no more? We're obliged to warn you. If you do go in, we can't protect you. I just don't recollect Aston for any protection.  He's hunting for a real sporting man. I saw some of your slaughter the other day. That's real sporting. Now you hear me what I say. I get paid on how many buffalo hides I ship. That's fine. Now then, folks in the East, they're developing a taste for buffalo meat. All I gotta do is get it to the railroad. And that's fine. I get paid for that, too. I'd hate to have to fight a war. On your account, mister. Maybe I'd be on your side. I'm good at shooting. Now tell you what. You figure price on Indian hides. Indian meat. Maybe I will be on your side, Captain. This is Kid Carson country, isn't it, Captain? Along the Powder River? He was up here, sure. On the bottoms of the Powder. It was black with buffalo then. Well, the big herds are still up this way, aren't they? The Indians think so. That's good enough for me. And for Jake Cuppey, apparently. You take men like Kid Carson, now he was a trapper, a hunter, but you hear good things about him. The Indians like him. You're not comparing Carson to Cuppey, are you, Mr. Cybert? No, sir, I'm trying to figure out the difference. Both seem to be after the same things. Maybe, maybe. The early trappers, the hunters, the mountain men, they learned a lot from the Indians. Made friends with them, like you say. But more, they came to hunt like Indians hunt. You mean they hunted as they had need? More that they knew what conservation meant even then. But if you kill more than the herd can bear young, you'll run out of quarry.  I hope we find him, Captain. I hope we find him. In time, Mr. Cybert. The wagon tracks we're following, Captain. Now, what about them? It looks like they stopped just ahead, sir, right at that line of trees. Patrol, hold! They could be in there, Captain, Cuppey and Guffey. They could, Mr. Cybert. Come on, Gorse. Yes, sir. Sergeant Gorse and I are going to move flat into the trees, Mr. Cybert. Now, the patrol will stand the covers. Yes, sir. One shot out of those trees and you move in. Right, Captain. All right, Sergeant. Run and crouch down to the brush. Then we move flat in our bellies. Yes, sir. Let's go. Some high-bed wagons like Gophie have. They move through here better than we do, Captain. I can't see Cuppey making a camp here. I can't see him coming in here. Over the army's warning. Just about to the trees, Gorse. Don't straighten till we're in them. Yes, sir. All right, now. As thick as they look, Captain. Head there, Gorse. The wagon. It's Gophie's wagon, all right. Some hides here in the bed. His team's gone. Must be thinking to drag the hides back here. From how far away, I wonder. I don't know. I'm trying to figure them, Captain. I can see they might hide the wagon so as we couldn't follow its tracks, but we can track horses who's just as well. Not this way, Gorse. Green sacks, well, sure. Yeah. They fix green sacks to their hooves that muffles the sound. Leaves almost no hoof prints. They're smarter than they act, Captain. Are they, Gorse? Huh. Buffalo guns. That's one sound they can't muffle. Come on, Sergeant. Fred and five miles at least, Captain, and no sound to guide us for the last three. Don't need sound with a sign like that ahead, Mr. Cybert. That brown haze like dust? It is dust. It means a big herd. Probably been stampeded. There's bottom land just after that rise where a clear creek feeds into the powder. We'll make for that. Yes, sir. At the gallop. I said it was a big herd. But it's like a massacre. Must be a thousand buffaloes. It is a massacre. That much killing of anything without cause. It is a massacre. Well, Jake Cuppey, he couldn't have shot them all. He could shoot enough with Goffy helping. Likely the rest were stampeded to death. Slaughter, that's all you can call it. I don't see how it could happen so much of it. Buffalo don't have much eyesight. They count on smelling signs of danger. Cuppey's trick is to shoot from far enough away so they can't smell him. We better... We better go down there, Mr. Cybert's. Cuppey, would he cause all this and then hide out, Captain? He might. Known we'd be coming after him. Known he and Goffy couldn't hope to haul them all out before we got here. You seen any that's been skinned? No, sir, not a one. Captain Quintz? That explains a lot of things. I come on their horses first down further. They're shot full-air, it's two. Both of them are still warm, Captain. They haven't been dead long. Thousand dead buffalo. Two dead men. That's a lot of death, a lot of waste. The engines must still be around, Captain. Yeah, they'd still be around. Up in the hills, likely. Those arrows, sir, they're in Cuppey and Goffy and the horses, but not the buffalo. The Indians weren't after buffalo, Mr. Cybert's. Come on, let's move out. Captain, we'll have to fight the Indians for this. Not today. Not this patrol. But this isn't the last of the buffalo hunters. Moral come all the time, and we'll fight wars over it. We've got to just leave things this way? The sooner we go, Mr. Cybert's, the sooner the Indians will move down and get the meat and the hides. Sometimes all a man can do is turn, walk away. Fort Laramie is produced and directed by Norman MacDonald and stars Raymond Burr as Lee Quince, Captain of Cavalry, with Vic Perron as Sergeant Gorse. The script was specially written for Fort Laramie by Kathleen Height, with sound patterns by Bill James and Ray Kemper, musical supervision by Amarigo Marino. Featured in the cast were James Nussar and Barney Phillips. Jack Moyles is Major Daggett and Harry Bartell is Lieutenant Cybert's. Company, tension, dismiss. Next week, another transcribed story of the Northwest Frontier and the troopers who fought under Lee Quince, Captain of Cavalry. A viewer youngster of school age, right now for the new fall term, parents and citizens will discover that the enrollment in their community schools has increased tremendously. That means an acute shortage of teachers, school rooms and supplies. Help your youngsters and others in your community by joining up with your local civic and educational groups. Act now to correct the great shortage of teachers and equipment. CBS Radio urges you to help make your community schools fit for your community youngsters.


Wrigley's Spearmint Chewing Gum. The refreshing, delicious treat that gives you chewing enjoyment presents for your listening enjoyment, John Lund as... Johnny Duller. John Old Mainard, Johnny. Oh, hello, Mr. Mainard. Haven't talked to you in a long time. Want to go to work? Sure. What is it? We ensure a miss Isabel James, Tulsa, Oklahoma. She's been killed. How? She'll leave as soon as you can, Johnny. Don't take me long. See you at your office in an hour and you can fill me in on the details. The makers of Wrigley's Spearmint Chewing Gum bring you John Lund and another adventure of the man with the action-packed expense account, America's Fabulous Freelance Insurance Investigator. Yours truly, Johnny Duller. For a refreshing taste, plus chewing enjoyment, treat yourself to delicious Wrigley's Spearmint Gum.   The chewing itself helps keep your throat pleasantly moist. Best of all, you can chew and enjoy refreshing Wrigley's Spearmint Gum almost any time and any place. Keep a package handy right in your purse or pocket so you can chew a stick whenever you want it. For a refreshing taste, plus chewing enjoyment, treat yourself to delicious Wrigley's Spearmint Gum. Millions enjoy it and you will, too. Expense account submitted by special investigator Johnny Duller to Home Office, National Life and Casual Insurance Company, Hartford, Connecticut. The following is an accounting of expenditures during my investigation of the Isabelle James matter. Expense account item one, $103.65, plain fare and incidentals between Hartford and Tulsa, Oklahoma after receiving from you the necessary information concerning the case. I arrived in Tulsa the next morning, registered at the hotel and went directly to the police station where I introduced myself to Captain Clifford Kissig. Yeah, got a teletype from your company. Said you'd be in this morning, good trip. Fine. You're investigating the Isabelle James murder. That's right. I was hoping you could give me some help. I'd sure like to, but it's got us stumped. We've had three others like this already. Three others? Yeah, all the same. Isabelle James was the fourth. Looks like Tulsa's got to jack the ripper. All with her throat's cut? Yeah, four killings in the last three weeks. You're after a madman. Yeah, pretty smart madman, haven't got a lead. Not a one? Always picks a lonely spot, never a witness, never anyone who saw anything or heard anything. What's a you as a knife? The lab thinks it's a razor, straight razor. Got the town a little jumpy. I can understand. But we'll get something. Sooner or later the killer will make a slip or somebody will tell us something. What happens in the meantime? We just got to pray there ain't no more killing. How far is Dawson from Tulsa? Not very far. Going over to see the dead girl's uncle? Yeah, he's the beneficiary. I found the policy in her belonging. I was the one notified your company. You know the uncle? Had him come down and identify the body. How much does he get? 10,000. Well, he can use it. Just an old farmer. Well, I'm going to run over and see him. All right. How long are you going to be in town? Well, I'm being paid to investigate a murder. I guess I'll be around until somebody catches a killer. Captain Kissig advised me where I could rent a car. And a half hour later I was driving a small coupé out of the Tulsa city limits heading for Dawson. The dead girl's uncle, Morley Parrish, lived a few miles east of Dawson in an old rundown farmhouse that was in the middle of six or eight acres of parched earth. He was a man in his late fifties, weatherworn and thin. He met me at the door with a look of suspicion. What do you want? Mr. Parrish? Yes? My name is Dollar. I represent the insurance company that covered your niece's life. I'd like to talk to you about it. About what? About your niece, her debt. She's dead. What's there to talk about? You're the beneficiary. You get $10,000 from the insurance company. Come in. Sit down. I get... How much are you saying? $10,000. You want a drink? Well, I don't... I got a jug of whiskey. I've been saving it. You see your name is... Dollar. What company you work for? National Life and Casually. I get $10,000. That's right. Yeah, I have a swig. Oh, now you swallowed wrong, huh? Yeah. Oh, give me that. Well, no wonder. I didn't shake it up. Shake it up? Oh, sure. Gotta shake it to make it smooth. You're sure that didn't come with a fuse in it? Emmett Willis made it himself. Brung it by last month. Yeah, you tried now. Well, I really don't think I... Oh, go ahead. You got a bad sample. Okay. You see how much smoother it is? Yeah. Well, you just got to shake it up. No, I'll have it. Ah, yes. Oh, my... Well, that's right. Tasty. Yeah. Let's talk about your niece, huh? All right. Let's talk. You know why anybody would want to kill her? Well, it's that fella that's been killing all them other girls, ain't it? Yeah, I guess so. That's what the police say. Well, it seems to me he don't care who he kills. Just as long as it's a girl. Another swig. No, no, thanks. Your niece left you when she was 16. Didn't she? Yeah, I'll take a moment to show you how you're... Ah, yeah. Yeah, 70. 70, that again. She ran off to Tulsa. You see how much after that? Not much. Maybe once or twice a year. When was the last time you saw her? The other day in the morgue. No, I mean before that. Ah. Oh, my. Well, that was about a month. She didn't write or... Oh, look, Mr. Police, they ask all them questions. I know it. And you got to ask them all over again, huh? If you want to get your $10,000. Well, okay. No, she didn't write. She never wrote. At least in the last five or six years, she never wrote. When she first got to Tulsa, she used to write and on in. Last time I seen her, she didn't say anything about what she was doing or who she was seeing or anything. So, I can't very well help you find out who killed her. Come on, how a swig. No, thanks. I'm in a rented car. You know, she would shoot herself. And once I opened the jug, it gets finished. And you better finish it. Naturally, I will. Oh, man, oh, man. Delicious, huh? Oh, you bet. I left before he finished the damage on. It was getting dark and he stood on the porch, leaning against the post and waving goodbye between the last few swallows. Back in Tulsa, I went to the hotel where I took a hot shower, then stretched out on the bed to relax for a few minutes before going out to dinner. I smoked a few cigarettes and had just about decided to have some food sent up to the room when the phone rang. Johnny Duller. This is clear. Huh? Oh, hi. Got back from Dawson about 40 minutes ago. What did you think of the old boy? Quite a character. Thought if you weren't doing anything, you might like to drop down the station. You got something? Yeah. What makes you think so? When he got too close, he began screaming and he ran. She gave us a pretty good description about 15 minutes ago.  The girl I identify him? Yeah. Well, it seems to me you're going to need more than that. His name's Story. S-T-O-R-E-Y. My Alvin Story. He hasn't said anything interesting. But you think he's it? Yeah. I think so. Nothing definite except the razor and his action, but I just got a hunch. What's he say about the razor? Not much. Admits it is. Says he was just carrying it in here. I was just taking a walk. And you weren't following the girl. I told you I wasn't. I told you I was just taking a walk. If the girl thought I was following her, well, I can't help that. I wasn't. I was just taking a walk like I said in the first place. Hello, Captain. Hello, Alvin. Back with someone to relieve Sergeant Hattuck? I'm not tired, Alvin. Well, you're going to be if you keep on like this because I've told you the truth and I'll just keep right on telling it. All night if you keep asking me. Have a cigarette, Alvin. I told you I don't smoke. Honest, Captain, this is just a waste of time.  We've got a lot of time. Now let's go through it again, Alvin. Where did you get the razor? Well, I bought it. Where? At a hardware store. You can check it. I bought it at a hardware store about three weeks ago. I used it to shave with, not to kill anyone.  I'm not the one you want.  We never said you were, Alvin. But you think so? Just because that girl thought I was following her. Oh, weren't you? No, I told you I was not following that girl. You were on your way home? Yes. You told me before. Yeah, I was on my way to a show. Yes, I wasn't on my way home. Keep asking me all these questions. I get confused and made a mistake. What show were you going to see? Well... What show? Well, no one in particular. I was just going downtown to see what was playing. You were headed downtown? Yes, to see what was playing at the shows. The girl says you were following her. Well, I don't care what the girl says. She's lying. I wasn't following her. But you were walking behind her. Yes, I... I might... Yes, I was probably walking behind her. Well, she was going in the other direction from town. Well, then I wasn't behind her.  Police sergeant named Haddock kept working in the suspect. Quietly, persistently. Alvin Story, a tall, frail-looking man, dressed in blue jeans and a leather jacket, sat behind the table trying desperately to be calm and anticipate the sergeant's next question. After a half an hour, the captain and I left and went upstairs to his office where he fixed coffee. Cream and sugar? Black will be fine. Well, what do you think? I don't know. He's a strange one. Yeah. If I had to pick types, I don't know. It's hard to tell about anybody in a police station. Maybe he was following the girl. She starts screaming her lungs out and he panics. The law picks him up, finds a razor on him. Maybe he's not the killer at all. He knows he looks guilty, so he gets good and scared. Guys act awful funny and make a lot of mistakes when they're scared. He just carries a razor around with him. Well, isn't it possible? Oh, yeah. But I still think he's our killer. Well, I have to admit I'm inclined to agree with you. But there's always a chance he's not. You never know. Kissing. Yeah? Okay. Well, we know now. Story? Yeah. He just confessed. No matter what kind of work you do, it's a real help to chew delicious wriggly spearmint gum right while you're working. When you're warm or tired, for instance, the lively, full-bodied spearmint flavor is really refreshing. It helps keep your mouth and throat feeling cool and moist. Chewing on that smooth, good-tasting piece of wriggly spearmint makes the time pass more pleasantly, too. It seems to make your work go smoother and easier. Keep a package or two of wriggly spearmint chewing gum handy all the time. Enjoy chewing wriggly spearmint while you're working and at other times. That's wriggly spearmint chewing gum. Healthful, refreshing, delicious.  Alvin's story still sat at the table in the dim, bare little room. He looked tired, but he looked relieved. A stenographer was set up at one end of the table while Sergeant Haddock leaned against the wall and smoked a cigarette. Captain Kissig crossed to the table and sat on the edge of it, facing the suspect. Can we get this thing over with, Captain? Can we finish it up and let me go lie down? You know, the stenographer's ready. Tell us about it. Well, what's there to tell? I killed him. I killed all of them. Isn't that enough to say? That's what they'll hang me for. Anything else I say won't make any difference.  I don't know. You know something I really don't know. I just wanted to. First one, I saw her and I just wanted to. I guess I thought about it before I saw her. Yes, I used to lie in bed and think about it. I used to dream about it, too. I used to wake up and feel like I'd really done it. Sick all over and scared. Felt so terrible. Like I feel now, kind of. Yeah. It's like a dream now. Right now it's like a dream, but it isn't. Tell us about the first one. I have to. It'll help. It's kind of hard to remember exactly. I bought the razor and I waited for it. On Garvey Boulevard? I guess so. Try to remember. Yeah, it was Garvey who was late at night. What night? The night of the 11th. Maybe. I think so. I think it was Tuesday night. That's right. And I killed her. You knew her? No, not really. It's hard to explain. Well, did you know any of the other three girls? Two. No, with the last one it makes four all together. No, three. Now, think about it a minute, Alvin. There were only three. I ought to know three girls. No, now try to remember. I don't have to try and remember anything. There were three, just three. One, two, three. I know. Why would I want to lie? I'm not saying you're lying, Alvin. I even know the names. I cut the pictures out of the paper. Tell me the names, then, Alvin. Well, certainly. Mary Knapp, Virginia Vitello, and Thelma Greer. I know all of them. I kept a record. What about Isabel James? Who? Isabel James? Oh, yes, she was in the papers the other day. That's right. Somebody killed her like the others. I read about it. I thought it'd be blamed on me, but it didn't make any difference. One or ten, what difference would it make? For a half hour, they questioned Alvin's story. Time and time again, he admitted the three killings. And time and time again, he denied any connection with the fourth, the murder of Isabel James. Expense account item two, $4.95. Breakfast for Captain Kissig and myself. After which, I returned to the hotel and crawled into bed. A lie detector test would be given to Alvin sometime late in the afternoon, so that gave me at least six or seven hours to catch up on my sleep. I left a call at the desk, turned over, and closed my eyes. Bloody dollar. Three o'clock, Mr. Dollar. Oh, uh-huh, thanks. And I'm Mr. Parrish. Parrish? Yes, sir. Okay. Send him up. Yes, sir. Come in, Mr. Parrish. Have a seat. I've been down stairs for over an hour. Oh, I'm sorry. But I was up all night. I told the desk not to disturb me until three. Oh, gee, that's all right. I know you city fathers don't like to get to bed much before the sun comes up. I didn't mind waiting. I was with the police. Oh. I've been working with them on the death of your niece. Oh, is that right? Well, uh, that's the reason I come to Tulsa to see you. I was wondering when I was gonna get the, uh, get the money. Well. See, I got a chance to get me a right smart section of land, trade in the place I got now, plus eight thousands real goodbye. Oh. Well, Mr. Parrish, it might be some time before you get the money. Oh, how come? Oh, there's a routine that has to be followed. I have to finish my investigation. You're still investigating? Oh, sure. You see, your niece's death is still unsolved. Well, is that fellow just killing all them other girls? It certainly looks that way. You mean you gotta catch him before he can pay me? No, but I've gotta make sure that he's the one who killed your niece. You think maybe he isn't? Well, to tell you the truth, Mr. Parrish.  Not exactly. Huh? I said, not exactly.  Well, how do you know that? The police laboratory report. They can tell if it was a different razor? Oh, no, come on, Mr. Donner. Maybe I ain't the brightest. It's a fact, Mr. Parrish. How do you think they knew it was a razor in the first place? Not just a very sharp knife? Oh, they can tell, all right. Well, maybe the killer ain't using the same razor. Yeah, we've considered that, but we can't tell. He hasn't killed again. Maybe he never will. You mean I might never get my money? Well, now, Mr. Parrish, it's not quite that bad. I want to see you get your money. You've certainly got it coming. But I can't honestly recommend payment to my company until the case is solved. What do you mean until you catch the killer? That or until we're certain the same man that killed the others killed your niece. Well, it seems to me you've got to catch him to prove that. Yeah, unless he kills again. But the same razor he used on your niece. Then we can be pretty sure that he's changed razors. Well, maybe he's got two different ones. Maybe. Well... You have to go? Yeah, I've got to be getting back. As long as I ain't going to get the money right away, there's no sense in hanging around. Don't be discouraged, Mr. Parrish. Just as soon as I'm convinced the killer's changed razors, you'll get your money. Look, Captain, Morley Parrish was just in my room.  A different razor? I think maybe he did it for the insurance. Read all the stories in the paper about the killings and decided to kill his niece. And the Alvin story? Right. Only I didn't tell him that Alvin's story had been arrested.  He thinks your police lab proved that Isabel James was killed with another razor. And he quickly came up with a solution that the killer had changed razors or had two of them. So what? I think he'll go out and prove it. Thank you.  Well, so do I, but it's the only way we could prove anything. Where is he? He just left. But, holy cow, if you're riding, he's wandering around little... facts. He'll go back to his farm in Dawson first. What made you think so? He has to get the razor, doesn't he? Ten minutes later, Captain Kissig picked me up in his car and we drove well over the speed limit getting to Dawson. Just west of Old Morley's farm, we pulled off the road and turned off our lights. Well, the house is dark. Where is he? Still on his way from Tulsa. We got here pretty fast, Captain. Yeah, we did, didn't we? Come on, let's walk down to the house. He have a car? I don't know, but I doubt it. I didn't see one the last time I was here. Darling? Hmm? What if you're wrong? What if you guessed wrong? What if he did have the razor on him? Well, that's a pretty good question. The night was warm and the big red moon. We walked down to the old farmhouse while a coyote howled way off in the distance. We found a spot by the side of the house where we could see the road and still be hidden in the shadows. We waited for Morley Parrish to come and get his razor. About an hour later, the old man came walking down the road and went into the house. After a few moments, a light flared in the back room. We could hear him moving around and the light went out. Hold it. Who's there? Who are you? It's me, Mr. Parrish. Mr. Dollar? This is Captain Kissig with me. This came down to see you. Well, I got business. I got to be going. In a minute. There's a drink in the house, another jug behind the stove.  I'll be right back. In just a minute, Mr. Parrish. Look, I got a hurry. Where are you going? I got business in Dawson. You're going to walk? Oh, sure. I always walk. I hitchhike if I get a lift. We've got a car. We'll give you a lift. No, I don't want to put you in no trouble. No trouble? Mr. Parrish, what did you pick up in the house? What? Nothing. What have you got in your pocket? Nothing. What do you want? You ain't got no right to do... Do you own a straight razor, Mr. Parrish? You better give it to us, Mr. Parrish. And be careful how you do it. I've got a gun pointed at you. Well, you knew it all the time, huh? I had a hunch. I hear you.  Yeah.  Oh, there ain't no difference after the first one. I sure could have used that money. Gee. Man, oh man, that was a wonderful little farm, but... Oh, I just guess you can't beat them scientific police methods. I sure thought I had it all figured out, too. We going to go now? Yeah. What's going to happen to my farm? They'll sure hang me, and I ain't got no relatives to take care of it. The state will take care of it.  There's no sense in wasting it on some stranger who wouldn't appreciate it. We took old Marley Parrish back to the station where he gave us a complete confession. He'd killed his niece for the insurance the way I'd figured. When we told him that Alvin's story had confessed that afternoon, old Marley just shook his head and said something about policemen being a whole lot smarter than most folks given credit for. Expense account, item three. $11.80, dinner for me and Captain Kissy. After which, I returned to my hotel, turned in, and got a good night's sleep. Expense account, items four and five. $89.45, car rental and hotel bill. Item six, $125.19, plane fare and incidentals back to Hartford. Expense account total, $335.04. Yours truly, Johnny Dollar. Remember friends, for refreshing taste plus chewing enjoyment, treat yourself to delicious Wrigley's Spearmint Chewing Gum. The taste of fresh spearmint is cooling and delightful and there's lots of it in every stick of Wrigley's Spearmint Gum.  You'll enjoy the good chewing too because Wrigley's Spearmint is so smooth and pleasant to chew on. There's nothing else quite like it. Next time you're at the store, stop at your friendly merchant's display of chewing gum and get a few packages of good tasting Wrigley's Spearmint Gum. Always keep some handy for refreshing taste plus chewing enjoyment. That's Wrigley's Spearmint Chewing Gum. Healthful, refreshing, delicious. Yours truly, Johnny Dollar. Brought to you by Wrigley's Spearmint Chewing Gum. Stars John Lund in the title role and was written by Blake Edwards with music by Eddie Dunstetter. Featured in tonight's cast were Joe Duvall, Parley Bear, Howard McNear and Clayton Post. Yours truly, Johnny Dollar. Is produced and directed by Jaime Delvalle.  This is Charles Lyon inviting you to join us again next week at the same time when from Hollywood, John Lund returns as... Yours truly, Johnny Dollar. This is the CBS Radio Network.


Welcome back to Drinks Made Easy because cocktails don't have to be difficult. Today we're taking a look at a really easy cocktail, the Rum Sparkler. One of the things I love about this besides how easy it is is you can just pull out all the alcohol elements and just use a bit of seltzer if you happen to have guests who are either children or not drinking. But without any further ado, let's make a cocktail. But if you haven't already please go ahead and click on the subscribe button and the bell icons to be notified every time we release a new video. To make the Apple Rum Sparkler we'll start with two ounces of dark rum. Next we're going to add one ounce of apple juice and a quarter of an ounce of light runny honey. Now light runny honey is going to be one part honey to two parts water. Cap that off a new shape on full of ice and give it a quick shake.  Top that off about two ounces of champagne or sparkling wine. Give it a quick stir. Garnish with a wheel of apple and garnish with a sprig of mint. And easy as that, you have the Rum Apple Sparkler. This is also a great drink that if people aren't imbibing you can always just take out the rum and add a bit of seltzer. And that way this drink can have a lot of versatility if you're entertaining a number of people. This is a delightful cocktail. Now a lot of people when they see the ingredients of having honey think of it being really honey for but because it's light runny honey the little bit of honey actually rounds out all the flavors and brings them together. It's a simple delicious and effective sparkling wine cocktail. Check it out and let us know what you think or if you have any modifications that you like when serving a drink like this. Cheers from Drinks Made Easy.


at Big Data SV 2014 is brought to you by headline sponsors, WAN Disco. We make Hadoop invincible and Actian, accelerating Big Data 2.0. Okay, welcome back. We're here live in Silicon Valley for Big Data SV, Silicon Angle and Wikibon's theCUBE, our flagship program where we go out to the events, extract the signal from the noise. I'm John Furrier, the founder of Silicon Angle from Jeff Kelly, analyst at wikibon.org. I'm my co-host and our next guest is Anna Smalltree, director at Treasure Data. Welcome to theCUBE. Thank you so much. Thanks for having me. To Treasure Data, one of the fast growing stuff. We've been watching for a while, but just all of a sudden busted out of nowhere. Just it's almost like they were storing all this data and then boom, straight up in growth and a lot of traction. So first question for you is, where did all this traction come from? Was it just pent up energy? Just kind of waiting to be launched? Tell us a little bit about Treasure Data right now. Yeah, so Treasure Data has a really unique solution in this market. We offer, it's essentially software as a service for big data. So we have technology to help people acquire data and to store it, and then we give different interfaces for analysis. But a lot of our secret sauce is in our acquisition technology. So we focus on data that's created very, very rapidly and we get it into our cloud environment. There was a lot of pent up demand about that. So about that issue of how to stream data into an environment and make it quickly available for analysis. So a lot of our early customers came to us because of this acquisition, the streaming capability, and they also wanted to focus on what they did best. So their core business, analyzing their core business and not necessarily worrying about the data infrastructure so much. So all that, the big bet was on the ingestion side, right, was that pretty much? The ingestion side and the storage side. So we're really good at data management at huge, huge scales. And then rapidly making that data available for analysis. So that people, rather than worrying about building the infrastructure, maintaining it, monitoring, getting the pages, they can just focus on what I call the fun part. So doing all the analytics at the other end where you get value from the data. So kind of, yeah. I mean, I think we've been covering the cloud and big data and we've been talking about, well, when are these two going to really kind of merge? And Trader Data is one of those companies that's actually making it happen. So, you know, first we should point out that you and I used to work together at Tech Target. So we're having a slightly surreal moment here on theCUBE. It's always fun on theCUBE. It's great to watch. It's great to watch. You never know what's going to happen, exactly. So yeah, tell us a little bit about Trader Data in terms of the different ways you kind of deliver your service. Because no, it's not just kind of one size fits all. You guys approach it in a couple different ways. So kind of lay that out for us. Yeah, so we do essentially have one primary service, but people use it in very different ways. So as I mentioned before, we tend to talk about it in three phases. So data acquisition, data storage, and data analysis. Some people are using that all in line. So they're streaming their data into our cloud environment and then they're doing their analysis in the cloud. They're keeping it all in a cloud environment. Other people are putting us as part of a larger data ecosystem. So perhaps using us to ingest all that data that's coming in very rapidly to store it at scale. So billions and billions of rows, sometimes 10 billion rows a day. So that's the kind of scale we're talking about. And they might then do some aggregations to bring down the size of the data and then export the results to another system internally where they might combine it with other data or bring it into another analytics environment or use an on-premise analytics tool. So we have these different models, one where we can fit into a larger data ecosystem and one where it's really the entire end-to-end solution being used in place. And where a company chooses to go might change over time. They might start in one place and then hopefully as they get addicted to treasure data, they're going to start to expand their use of it. But we really try to make it open for integration into existing ecosystems, but also a full end-to-end solution. So if you just want to use that as your primary analytics and data management solution, you can do that too. So providing end-to-end cloud storage is interesting. And certainly as a SaaS, it's a nice business model. We've always been supporting of that. And we love it, it's great scale and it's agile. But I got to ask you, a lot of people have been throwing that under the bus with the whole Nervonix implosion of late. Nervonix was big cloud storage and they went out of business and then literally had two weeks, people that moved their data around. How do you guys address that issue with customers? Well, we love the cloud, but I'm not sure about the data. Is there a product that you guys have there? How do you solve that conversation? So a few different things. We are committed to data portability. So you can export your data from treasure data anytime you want to. We're not trying to lock you in or charge a fee or make it difficult to get your data back. So people will do that on a small scale when they're just doing queries and pushing the results out, maybe to do some other things with that data. People could do it anytime they could take all their data. We hope they don't, but they could. And we're very much committed to being an open platform for that. I think the other main difference is this issue of acquisition and ingestion of the data. So there's a lot of cloud storage platforms where in order to get your data into the platform, you need to use FTP, you need to use bulk imports, and still FedExing disks. It's still a very, very popular way to get data into the cloud. And in fact, I found some news stories about cloud providers announcing the capability to take your mail. And now new capability, we can receive your disk and load it into our cloud environment. So our data streaming technology addresses a very big pain, which means you don't have to stage it and land it and then figure out how to get it into the cloud. But as that data is being created, our treasure agent technology sits right on the servers, right on the web server or the application server and streams that data every few minutes into our environment. We provide reliability, compression, filtering, and transformation of that end node. So when the data gets to the cloud, it's available for analysis within just a few minutes of being created. And it's also, you're not trying to push this huge bulk of data up a small pipe, but you're doing smaller bits of data on a more rapid basis. We've seen great success, but like Splunk, for instance, customers love that product, just allows it to sit there, and then new stuff kind of gets enabled out of that, once they have that functionality. So I want to ask you the same kind of question. For you guys, have you seen some use cases where, because once people get the data and they can act on it, some new insights come out, can you give some examples of where you've seen that happen on your end with your customers? Yeah, so I think people have different ways that they're approaching this.  So we have some customers, one of our customers is a large retailer, they announced a mobile application, and they really wanted to understand sort of how their mobile users were engaging with the product, how that compared with what people were doing online, and how that compared with what they were doing in the stores. Now I can't talk about the exact results because people tend to be a little closed lips about their analytic results, but what they were able to do is get a well-rounded view of the customer. So kind of that old 360 degree view of the customer thing that we've written so many stories about in our time. And indeed. But being able to get this complete view of the customer and understand where the differences and interactions are in a mobile environment versus a web environment versus a retail environment, where some of those connections were and how to leverage that to make more money for their business. So I want to ask kind of a little bigger picture question, kind of playing up with John mentioned about concerns around the cloud. So we've heard about one of the mega vendors in particular was really pushing the big data, I mean cloud marketing, but we haven't seen a lot of it. Is the cloud ready, do you think? Really for to be a place to store all this data, to do a lot of these workloads. And why is that now, do you think? And why is now the right time for a company like Treasure Data? Yeah, so I do think that the cloud is ready. I think there's some types of data which will always remain on-premises and that might be really sensitive data, really regulatory regulated data, healthcare data about my health especially now. But there's some types of data that are going to stay in those environments. But the cloud, since we've been writing about it really, has evolved to be massively scalable, a lot more secure. Even getting data into the cloud is a lot easier than it used to be. So even the increases in sort of network connectivity and bandwidth and being able to get more pikes into the cloud has made it a lot more ready. And you have this explosion of different service providers, new architectures and new platforms which I think make the cloud an ideal place for big data. I think we're also seeing this sort of shift. It used to be a competency to do your data management to store it all in-house. I think the competency is shifting more to what can you do with the data? And now it's a little bit more commoditized to do data management which makes the cloud a perfect place to do it at scale. So they buy millions of servers or however much it takes to store the different platforms and environments and are able to scale that rapidly. And that's really a core competency of a lot of cloud providers that doesn't need to be your core competency as a business anymore. You can focus on the fun part and getting value. I want to ask you a question. You kind of shift gears kind of the strata conference. I know given your background, I'd like you to get to your editorial perspective if we were editing the show. The narrative's coming out of strata. A lot of noise, a lot of signal, a lot of different conversations, a lot of startups that names I've never heard of. Tons. That company never heard of it. That's going to die. That's going to be gone. But let's be critical. Let's edit the narrative. What is the story, in your opinion, coming out of strata this year? And then talk about your story with treasured data. How's that vector into the bigger picture? Yeah, so I've seen the same thing. A lot of names I've never heard. And as tech journalists, we used to have the unenviable or maybe enviable job of trying to figure out exactly what all these people did and really pushing until we understood that. I really feel a lot of emphasis on getting value from data and doing it quickly. So a lot of these tools are focused on either getting Hadoop up and running faster or getting your data ready for analysis faster. So how can we shorten the time it takes to actually start getting value from data? And that's a place where cloud services can really help. Well, there are a lot more tools for doing data analysis on this big data, so being able to process it at scale. So I think we're feeling a lot of emphasis on how quickly you can do it. A lot more tools to enable you in the sort of big data ecosystem. And I think treasured data fits right into that. We're right in the mix there. We get people into production in days, less than two weeks oftentimes. So we're really focused on how soon can we get you to run that first query. And I think I hear that from different angles, there's people who are trying to get you up and running on premises faster or give you different tools to make it easier to use Hadoop. As we've sort of seen that Hadoop adoption curve go up, people have really started to understand and appreciate that it's hard. It's a little bit like building your kit car from scratch. Like, yeah, you can put a bigger engine in it, but you also still have to build the whole thing. So I think we see a lot of interest in how can I make this easier and faster. So here's another question for you. So, I'd love to get you to extract the data from you. So if you have to put people into like crowd spots or like clusters of crowd around certain topics, I see data science is one you see people really chomping on the red meat on that one. What other areas to see the conversations happening around here at this show? In the big data market right now, I see data science is one. What are the big crowd clusters out there talking about? Big conversation pits of interests. So I think that data movement is a big one. So people figuring out how they're gonna move their data around. And that counts just for collecting the data. So the first stage of ingestion, which I talked about a lot, but also for analysis. So are you gonna need to move the data into another BI or analysis tool? Can you analyze it in place? Even things like sharing data. So how you're moving this data around or not. Whether you can leave it in place and do what you need to do with it and share it. So I definitely got a lot of questions about that. I think there's a core of people who are focused on infrastructure and architecture. And how can we process things faster? So getting the performance out of big data processing that is needed. And that depends a lot on how you architect it. So I would say, and then I think the data science and analytics people are very focused on value. How soon can I get value? Can I use languages like SQL that I already know? How quickly can I start to see results and begin to go? I think that was just commenting earlier. Entrepreneur we've been following. Great guy used to work at Bank of America. Tracetic and successful startup. And loves to talk about some of the trends. But one of the things he meant to comment was if you're a database tooling company you might as well just fold 10 right now. Cause that's beyond where we're at now. More people that want solutions and outcomes. Would you agree with that? And what other areas would you say are, hey, old ideas not translating it to this modern era? Old idea, okay. So I mean, I do think we're seeing a shift to more of a build versus buy decision in the big data space. Partly because of the early experiences of early adopters who felt a lot of pain when some of those early Hadoop implementations. So, let's see, can you rephrase your question? So the database he's come as, the database guy should just not focus just on selling the database tools which is an old business model with hundreds of millions of dollars as vendors out there. We know they are. So the question is what old methods are being kind of put out there today as viable ventures? When in reality the market's way beyond that could be point solutions, white spaces. Like what you guys are doing, I think you guys are going to the cutting edge SaaS with storage, very interesting, you got ingestion. Yeah, the old enterprise data warehouse model, if you will. Yeah. The we've written about it. What are the dying business models that are being displaced? Maybe I'll ask the question. What are the dying business models being displaced by disruptive technologies? Well, so I do think that this issue of building it yourself is a dying business model. You don't have to have your whole own infrastructure. You can build things within the cloud. I don't know that database tooling is going away completely. There's a lot of legacy infrastructures that people still need access to. We talked to tons of people who are still on mainframe technology. So I think that some of those ways of thinking about a monolithic of mainframe or a monolithic data warehouse is going away. So we have these much more distributed environments of tools doing what they do best. But it has to fit in with legacy architectures. You can leverage things like the cloud to add big data capabilities quickly. But it needs to fit into this whole ecosystem. So I would say some things are becoming more preferable than in the past, but we still need to integrate with the past. Well, yeah, I think, you know, one of the things we've been talking about the last few days is I think this year we're going to see fewer announcements around new products and a lot more announcements around partnerships and integration with legacy systems.  There's so many moving parts from the integration to the analysis to the output. And then we've got legacy systems, as you say, that aren't going away. Mainframes are still around. You know, there's companies like the Sync Store, which is kind of, it was a mainframe company that's reinventing themselves. And they've been working on kind of offloading some of that mainframe data to big data and Hadoop, whatever. But talk a little bit about treasuredata as I guess your partnership strategy. And a little bit how you do that integration, whether it's from the legacy architecture that people have in their data centers. And then, you know, with the end output, whether it's somebody like Tableau or somebody other BI players. So the first integration point is around ingestion. And that's how we're getting data from the places where it's being created into our system. We have some very unique data acquisition technology that I mentioned earlier. So that's sort of a point of integration. But that acquisition technology is key because it can run on a lot of different kinds of servers. There's actually many different targets that I can output to treasuredata being one of them. So that's one integration point. I think another one is our ability to take data in multiple forms of streaming data or bulk import. Another integration point is this ability to export to your existing environment so that you can, as I mentioned earlier, the case of landing a lot of big data, doing some aggregations to bring it down in size or just get at what you want, and then you can export that to your current environment. And then a big one for us is that we integrate with the front end analytics tools. So our core competency isn't taking in that data, data management, and then making it available for analysis. But we partner with people like Tableau. We recently announced with them a couple weeks ago a formal partnership. So Tableau does the visualizations in the front end. So they are able to reach into treasuredata, either Tableau in the cloud, working with treasuredata in the cloud, or even Tableau on premises, working with treasuredata in the cloud. So this allows people to augment their Tableau environments with new big data capabilities really quickly. They're not the only BI provider we work with. We also work with Metric Insights, specifically on our gaming solution, and that's for digital gaming analytics. This is a really sort of big area. And then we have several other BI providers. We can really support any BI tool. We have ODBC and JDBC drivers. And as our customers request them, which is more often happenings that pushes out into the greater business and analysts hear about treasuredata and say, I could have big data capabilities in two weeks. Yes, I want that. But if we can take their existing tool, their Tableau, whatever interface they're used to working with, and just give them new data capabilities, then they've got an environment they're familiar with. Now they have more data they can work with. Golden, they have a lot more that they can do. So I think we're just about out of time, but I want to ask, so what's going to happen this year with Treasuredata? What's kind of on your roadmap to the extent that you can share? As John pointed out, you guys kind of just hit the scene really in a big way recently. So I think people are just like, where are you guys going with this? What's on your roadmap, and what are some of your big priorities this year? So we've had incredible momentum with our service. Like I said, it's software is a service for big data. It's a managed service environment. So that just sort of as a standalone solution has been extremely popular. And that's why in the last year we quickly passed one trillion rows of data loaded into our service, two trillion and three trillion. So we've had this incredible momentum. We have over a hundred customers now and that's our service being launched a little bit over a year. So the last year has been incredible momentum with our basic Treasuredata service. This year we'll be announcing new solutions. So these are things where we've configured the data collection and we've configured dashboards working with our partners on the other end to provide a complete solution in certain vertical industries. And the two you'll hear about next from us are digital gaming as I talked with. They have so much data. They're collecting data about every interaction a player does in the game. Every move, every purchase when they abandon. So they have tons of data. So digital gaming is a big solution we'll announce. Also advertising technology. So all those clicks and impressions and where we put things and which creative to use you'll hear more from us around that. And there's a few other industries that we have our toes in. I do think increasingly internet of things is what you'll associate with Treasuredata. So we have some early pilots working with sensors so much is instrumented now. And there's sensors in a lot of places that aren't even turned on for lack of a better word. So they're there, they're ready to collect data but people haven't had a place or the wherewithal to actually collect them. So internet of things is where you're really gonna see us in the water. We're definitely gonna be watching that. We've done some research with GE and their industrial internet movement. So that'll be really interesting to watch. And I think it's a really smart move to focus on verticals and solutions. That's what is done. So that's what people want I think. And especially as we kind of move into the early mainstream adopters and big data, they don't want to put together their own to do clusters and do a lot of this integration work. They want solutions. And that's where, yeah, and that's what you talk to you can talk to a business person who signs the check and that's good for the market and the industry, so. Yes. All right, well thanks so much for coming on theCUBE. We really appreciate it, Treasuredata here live inside theCUBE in Silicon Valley. Big data SV hashtag, big data SV. And we'll be right back with our next guest after this short break.


On Sunday, Letcher County Sheriff's Office announced that Mary and Randy Cornette had gone missing and is now seeking information from residents to contact him. Tuesday, Mountaintops spoke with Sheriff Mickey Steins about Cornette's disappearance. Over the weekend, we received information that the family had made a post that he was missing. I reached out to his daughter. She had informed me that she had not contacted law enforcement yet. She was hoping that he would see that on Facebook. So we got all the information off of her, made a post also of details, you know, who he is, how, the way, all that, where the family had last seen him at. We had actually had an interaction with him last Wednesday at Deputy did. We received a complaint that a male subject in the pain gap area that had made an attempt to get in the vehicle. Once the deputy gets up there and reaches out to the individual, it's this gentleman. He says that he's hitchhiking, that he thought they had pulled over to give him a ride. That's why he went up to the vehicle. He was not intoxicated or impaired, no warrants, no drugs, no nothing on him. He asked the deputy if the deputy would give him a ride to the gas station at the top of the mountain, the Virginia Kentucky border. The deputy said yes, took him up there. I had several people say that they had seen him at that gas station that evening at four or five o'clock. The deputy probably took him there around two. Fast forward to some comments and information we got yesterday that we was actually told that some people seen him at the Irvine gas station in a vehicle. Botsford PD was trying to make contact with that vehicle and him for us and was unable to locate the vehicle. So but the people from yesterday said they were 100% sure it was him. So we're kind of that gives us hope that nothing's wrong and that he's safe. We just wish he would contact us or his family. If you have information leading to Cornette's whereabouts, you can call us at your county sheriffs at<PHONE_NUMBER>. From out on top news, I'm Joel Corjol.