1 00:00:04,120 --> 00:00:07,160 Speaker 1: Get in touch with technology with tech Stuff from how 2 00:00:07,200 --> 00:00:13,720 Speaker 1: stuff works dot com. Hey there, and welcome to tech Stuff. 3 00:00:13,760 --> 00:00:16,680 Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer at 4 00:00:16,680 --> 00:00:19,480 Speaker 1: how Stuff Works and I love all things tech. And 5 00:00:19,600 --> 00:00:23,760 Speaker 1: today we're gonna talk about the Oracle story. Oracles a big, 6 00:00:23,800 --> 00:00:27,440 Speaker 1: big company, and this is inspired by my recent trip 7 00:00:27,720 --> 00:00:30,800 Speaker 1: to Sweet World eighteen. I flew out to Las Vegas, 8 00:00:31,000 --> 00:00:34,480 Speaker 1: Nevada and was part of that conference. I am back 9 00:00:34,640 --> 00:00:37,159 Speaker 1: in the Atlanta studio as I record this, So if 10 00:00:37,159 --> 00:00:39,800 Speaker 1: you're listening to this and you're thinking us sounds like 11 00:00:40,360 --> 00:00:43,800 Speaker 1: the normal type of episode, that's why. Also I want 12 00:00:43,840 --> 00:00:46,319 Speaker 1: to let you guys know we're going to step up 13 00:00:46,360 --> 00:00:49,720 Speaker 1: the production schedule for Tech Stuff, so you're gonna start 14 00:00:49,760 --> 00:00:53,720 Speaker 1: getting new episodes pretty much on a daily basis, at 15 00:00:53,800 --> 00:00:57,760 Speaker 1: least four new episodes a week and a rerun on Saturday's, 16 00:00:58,200 --> 00:01:01,600 Speaker 1: maybe more than that, depending up on how our scheduling goes. 17 00:01:02,040 --> 00:01:05,000 Speaker 1: But we're experimenting with a new format to see how 18 00:01:05,000 --> 00:01:06,960 Speaker 1: well it works, and I'm curious to hear what you 19 00:01:07,040 --> 00:01:09,600 Speaker 1: guys think about it. But I'm really excited about this 20 00:01:09,640 --> 00:01:11,200 Speaker 1: because it means I get to do the thing I 21 00:01:11,240 --> 00:01:14,080 Speaker 1: love to do more often, which is awesome. All right, 22 00:01:14,160 --> 00:01:17,200 Speaker 1: let's talk about Oracle. It's a huge name in the 23 00:01:17,240 --> 00:01:21,759 Speaker 1: tech space. It's a software company that frequently ranks right 24 00:01:21,760 --> 00:01:25,679 Speaker 1: behind Microsoft in the largest of such companies in the world. 25 00:01:25,800 --> 00:01:29,040 Speaker 1: So in the world of software, Microsoft's number one and 26 00:01:29,280 --> 00:01:32,080 Speaker 1: Oracles right behind it number two. And while most of 27 00:01:32,120 --> 00:01:35,959 Speaker 1: Oracles products aren't the kind the average person accesses on 28 00:01:36,000 --> 00:01:39,039 Speaker 1: a regular basis. You know, you think of Microsoft and 29 00:01:39,040 --> 00:01:41,000 Speaker 1: you think of things like Windows, and you think of 30 00:01:41,040 --> 00:01:45,840 Speaker 1: their suite of productivity software, things like Word and Excel. 31 00:01:46,680 --> 00:01:51,240 Speaker 1: Oracles business isn't really about the average customer, like the 32 00:01:51,280 --> 00:01:54,320 Speaker 1: average person is being a customer. Instead, it tends to 33 00:01:54,400 --> 00:01:59,440 Speaker 1: be a business that sells products to other businesses. Um. 34 00:01:59,480 --> 00:02:03,320 Speaker 1: It's history and its founders have very interesting stories. So 35 00:02:03,360 --> 00:02:07,440 Speaker 1: to begin with, let's start with the most famous of 36 00:02:07,520 --> 00:02:13,160 Speaker 1: oracles co founders, a man who has an incredible reputation 37 00:02:13,680 --> 00:02:19,280 Speaker 1: for being uh flamboyant, and he speaks his mind and 38 00:02:19,440 --> 00:02:23,080 Speaker 1: he can be incendiary in some cases. We're talking about 39 00:02:23,200 --> 00:02:28,200 Speaker 1: Larry Ellison. Now, Ellison's story is the stuff of legend 40 00:02:28,560 --> 00:02:30,880 Speaker 1: or maybe a fairy tale in some ways, because he 41 00:02:31,000 --> 00:02:35,120 Speaker 1: rose from poverty to become one of the richest people 42 00:02:35,639 --> 00:02:40,680 Speaker 1: in the world, and he has a reputation for being headstrong, unconventional, 43 00:02:40,800 --> 00:02:44,560 Speaker 1: and at times in his life living like a rock star. 44 00:02:45,600 --> 00:02:49,240 Speaker 1: Biography about his life has the title The Difference between 45 00:02:49,360 --> 00:02:52,200 Speaker 1: God and Larry Ellison, which is a setup to the 46 00:02:52,240 --> 00:02:56,560 Speaker 1: punchline God doesn't think he's Larry Ellison. I could do 47 00:02:56,600 --> 00:03:00,160 Speaker 1: a full episode just on him and his anti but 48 00:03:00,160 --> 00:03:03,080 Speaker 1: I'm gonna try and limit that a little bit and 49 00:03:03,120 --> 00:03:07,400 Speaker 1: focus mostly on his behavior directly tied to Oracle, though 50 00:03:07,480 --> 00:03:10,880 Speaker 1: expect some of Ellison's actions to creep in now and 51 00:03:10,960 --> 00:03:13,880 Speaker 1: again because they had an impact on the company that 52 00:03:13,919 --> 00:03:17,160 Speaker 1: he co founded. He was born in nineteen forty four 53 00:03:17,520 --> 00:03:22,720 Speaker 1: to nineteen year old Florence Spellman. Spellman was unwed and 54 00:03:22,800 --> 00:03:27,079 Speaker 1: Ellison never met his biological father. His mother handed Ellison 55 00:03:27,240 --> 00:03:32,480 Speaker 1: over to her sister, Lillian and her sister's husband, Louis 56 00:03:32,800 --> 00:03:38,320 Speaker 1: Louis Ellison. Larry's aunt and uncle adopted him, and according 57 00:03:38,320 --> 00:03:41,720 Speaker 1: to Ellison, the family took their last name from Ellis 58 00:03:41,840 --> 00:03:47,840 Speaker 1: Island after the father or the his uncle really Louis 59 00:03:48,000 --> 00:03:53,600 Speaker 1: or Louis after his family immigrated to America from Eastern Europe. Now, 60 00:03:53,680 --> 00:03:57,600 Speaker 1: according to Ellison himself, his childhood was pretty rough. His 61 00:03:57,680 --> 00:04:03,280 Speaker 1: adopted father undermined Ellison's self worth and confidence. Apparently, he 62 00:04:03,280 --> 00:04:06,480 Speaker 1: would say frequently that Larry Ellison was good for nothing. 63 00:04:07,160 --> 00:04:11,280 Speaker 1: Ellison had trouble in school. He was described as intelligent, 64 00:04:11,360 --> 00:04:14,320 Speaker 1: but he didn't do well with authority figures. He wasn't 65 00:04:14,360 --> 00:04:16,479 Speaker 1: really crazy about being told what to do and win. 66 00:04:17,320 --> 00:04:21,039 Speaker 1: But he was very smart, and when he graduated high school, 67 00:04:21,120 --> 00:04:24,600 Speaker 1: he first enrolled in the University of Illinois, but after 68 00:04:24,680 --> 00:04:27,520 Speaker 1: a while he dropped out, and then he enrolled in 69 00:04:27,560 --> 00:04:31,120 Speaker 1: the University of Chicago, but after a while he dropped 70 00:04:31,200 --> 00:04:34,120 Speaker 1: out of that as well, and at least the first one. 71 00:04:34,240 --> 00:04:37,400 Speaker 1: He dropped out for good reason and that his adopted 72 00:04:37,440 --> 00:04:41,279 Speaker 1: mother had passed away and he wanted to leave school 73 00:04:41,640 --> 00:04:44,320 Speaker 1: to be back with his his family and to pay 74 00:04:44,360 --> 00:04:47,760 Speaker 1: his respects. He made the decision in the mid nineteen 75 00:04:47,880 --> 00:04:51,520 Speaker 1: sixties to head to California and try to make a 76 00:04:51,560 --> 00:04:54,200 Speaker 1: living out there, and at first he did odd jobs. 77 00:04:54,400 --> 00:04:57,000 Speaker 1: He also bought a book on programming and began to 78 00:04:57,040 --> 00:04:59,839 Speaker 1: teach himself how to do it. According to an account 79 00:04:59,839 --> 00:05:02,960 Speaker 1: he gave to the Smithsonian, he never once took a 80 00:05:03,000 --> 00:05:06,760 Speaker 1: class in computer programming. He was completely self taught and 81 00:05:06,800 --> 00:05:10,440 Speaker 1: in nineteen seventy three got hired on at the Ampex Corporation. 82 00:05:10,520 --> 00:05:14,440 Speaker 1: Ampex is an electronics company. It started out making electric 83 00:05:14,520 --> 00:05:18,760 Speaker 1: motors and generators in the nineteen forties. By the nineteen seventies, 84 00:05:18,760 --> 00:05:21,760 Speaker 1: when Ellison had joined, the company had diversified and started 85 00:05:21,760 --> 00:05:26,400 Speaker 1: making various types of recorders like magnetic tape recorders such 86 00:05:26,440 --> 00:05:29,599 Speaker 1: as eight track or sixteen or twenty four track recorders. 87 00:05:29,960 --> 00:05:33,560 Speaker 1: Larry Ellison's supervisor at Ampex was a guy named Robert 88 00:05:33,800 --> 00:05:38,440 Speaker 1: Bob Nimrod Minor. Bob Minor was a first generation American 89 00:05:38,600 --> 00:05:41,960 Speaker 1: born in nineteen forty one. His parents came from Iran 90 00:05:42,120 --> 00:05:45,080 Speaker 1: to live in the US in the nineteen twenties. Minor 91 00:05:45,160 --> 00:05:48,400 Speaker 1: had attended the University of Illinois at Urbana Champaign and 92 00:05:48,480 --> 00:05:52,680 Speaker 1: graduated with a degree in mathematics. Bob Minor had a 93 00:05:52,760 --> 00:05:55,680 Speaker 1: deep understanding of computers and would end up being the 94 00:05:55,760 --> 00:06:00,440 Speaker 1: lead engineer for Oracle during those early days. The third 95 00:06:00,480 --> 00:06:04,760 Speaker 1: co founder of Oracle was another Ampex employee named Ed Oates. 96 00:06:05,240 --> 00:06:07,919 Speaker 1: He was born in nineteen forty six and graduated with 97 00:06:07,960 --> 00:06:11,160 Speaker 1: a BA in mathematics from San Jose University in nineteen 98 00:06:11,240 --> 00:06:15,120 Speaker 1: sixty eight. Together with Minor and Ellison, he would found 99 00:06:15,160 --> 00:06:19,160 Speaker 1: what would become Oracle. Now, alright, I should say that 100 00:06:19,200 --> 00:06:21,480 Speaker 1: at the very beginning here that there are a lot 101 00:06:22,000 --> 00:06:27,080 Speaker 1: of conflicting reports about the actual order of events that 102 00:06:27,160 --> 00:06:31,479 Speaker 1: I'm going to describe next. But based upon my research, 103 00:06:31,880 --> 00:06:36,479 Speaker 1: this is how I think things unfolded. Now. I say think, 104 00:06:36,600 --> 00:06:40,359 Speaker 1: because again, if you research this stuff, you're gonna find 105 00:06:40,400 --> 00:06:44,000 Speaker 1: a lot of different versions of this story. Some suggest 106 00:06:44,080 --> 00:06:48,760 Speaker 1: that Ellison joined the fledgling company a few months after 107 00:06:49,000 --> 00:06:52,520 Speaker 1: Oates and Minor founded it. Others say that Ellison was 108 00:06:52,640 --> 00:06:57,000 Speaker 1: the central role of founder in this company. I think 109 00:06:57,000 --> 00:07:00,880 Speaker 1: the truth is probably somewhere in the middle. First, Ellison 110 00:07:00,960 --> 00:07:04,600 Speaker 1: left Ampex in nineteen seventy six and joined another company 111 00:07:04,680 --> 00:07:08,719 Speaker 1: called Precision Instruments to take the position of vice president 112 00:07:08,760 --> 00:07:12,320 Speaker 1: of research and development over at Ampex. Bob Minor and 113 00:07:12,400 --> 00:07:15,120 Speaker 1: Ed Oates decided they wanted to form their own business, 114 00:07:15,560 --> 00:07:19,480 Speaker 1: so they left Ampex and they create They contacted Ellison. 115 00:07:19,640 --> 00:07:22,600 Speaker 1: They asked him if maybe he wanted to join their venture, 116 00:07:22,960 --> 00:07:26,480 Speaker 1: and Ellison agreed. So while he had joined Precision Instruments, 117 00:07:26,480 --> 00:07:28,560 Speaker 1: he was not there for very long. He left to 118 00:07:28,680 --> 00:07:32,320 Speaker 1: go and found this company and the brand new company 119 00:07:32,480 --> 00:07:38,680 Speaker 1: was not called Oracle, at least not yet. Instead, this 120 00:07:38,760 --> 00:07:44,000 Speaker 1: brand new company was called Software Development Laboratories or s 121 00:07:44,080 --> 00:07:48,120 Speaker 1: d L, and their business model was to become software 122 00:07:48,160 --> 00:07:52,480 Speaker 1: engineers for hire, so companies would contract with them to 123 00:07:52,600 --> 00:07:55,760 Speaker 1: build out software packages that those companies needed on a 124 00:07:55,840 --> 00:07:59,400 Speaker 1: per job basis. They would be contract workers. You need 125 00:07:59,440 --> 00:08:02,840 Speaker 1: a platform of programs developed, call us, we'll do it. 126 00:08:03,680 --> 00:08:07,800 Speaker 1: They rented out a an office out of Santa Clara, California, 127 00:08:07,840 --> 00:08:11,080 Speaker 1: with nine square feet of office space and all they 128 00:08:11,080 --> 00:08:15,120 Speaker 1: needed at that point, we're customers. So while they started 129 00:08:15,120 --> 00:08:18,720 Speaker 1: looking for business, ed Oates was looking around and he 130 00:08:18,760 --> 00:08:21,000 Speaker 1: came across a paper that was written back in n 131 00:08:21,600 --> 00:08:27,080 Speaker 1: seventy by a computer scientist in the UK named Edgar F. Cod. 132 00:08:27,480 --> 00:08:31,239 Speaker 1: Cod proposed using a model for information that would allow 133 00:08:31,320 --> 00:08:36,160 Speaker 1: a database to organize data by its relationship with other data. 134 00:08:36,240 --> 00:08:39,480 Speaker 1: And you would do this by organizing all the information 135 00:08:39,520 --> 00:08:43,680 Speaker 1: into tables with columns and rows, and each row would 136 00:08:43,720 --> 00:08:48,440 Speaker 1: have a unique identifier attached to it, and the rows 137 00:08:48,480 --> 00:08:53,320 Speaker 1: will be called records or sometimes called tuples. Columns would 138 00:08:53,400 --> 00:08:57,560 Speaker 1: represent attributes, so you would have a column that describes 139 00:08:57,640 --> 00:09:01,400 Speaker 1: some sort of feature that could apply to the various 140 00:09:01,480 --> 00:09:04,920 Speaker 1: records the various rows in this table, and each column 141 00:09:04,920 --> 00:09:07,520 Speaker 1: would be a different feature. So let's say that you're 142 00:09:07,520 --> 00:09:12,000 Speaker 1: talking about a physical product. One column might indicate the 143 00:09:12,080 --> 00:09:15,760 Speaker 1: location where that physical product is. Another column might be 144 00:09:16,520 --> 00:09:20,120 Speaker 1: the price of that product, or another one might be 145 00:09:20,200 --> 00:09:23,720 Speaker 1: the color of that product or whatever that might be. 146 00:09:23,880 --> 00:09:25,880 Speaker 1: And using this kind of approach, you could build a 147 00:09:25,960 --> 00:09:28,480 Speaker 1: really useful database that could allow you to look at 148 00:09:28,760 --> 00:09:33,040 Speaker 1: data in many different ways by structuring queries. So let 149 00:09:33,080 --> 00:09:36,720 Speaker 1: me give you a simple example so that I can, 150 00:09:36,760 --> 00:09:40,680 Speaker 1: you know, explain what this means. Let's say that you 151 00:09:40,760 --> 00:09:44,800 Speaker 1: are a huge roller skate tycoon, which means you you 152 00:09:44,880 --> 00:09:49,200 Speaker 1: sell roller skates and you're incredibly successful, not that you 153 00:09:49,240 --> 00:09:52,840 Speaker 1: sell really big roller skates or that you are in 154 00:09:52,960 --> 00:09:57,400 Speaker 1: fact a giant who wears roller skates. Now, in your business, 155 00:09:57,720 --> 00:10:00,280 Speaker 1: you decide you want to see which lines of roller 156 00:10:00,320 --> 00:10:03,559 Speaker 1: skates are selling best in your stores in San Francisco. 157 00:10:03,800 --> 00:10:07,040 Speaker 1: So you run a query and you've got this big 158 00:10:07,080 --> 00:10:09,640 Speaker 1: table of data and you're saying, well, I want to 159 00:10:09,679 --> 00:10:13,480 Speaker 1: see the skates that are being sold in our San 160 00:10:13,520 --> 00:10:17,679 Speaker 1: Francisco stores. I want them ranked by most popular to 161 00:10:17,800 --> 00:10:20,080 Speaker 1: least popular, and then I can get a quick look 162 00:10:20,120 --> 00:10:22,480 Speaker 1: at my business and see which ones are doing well. 163 00:10:22,600 --> 00:10:24,680 Speaker 1: Maybe I need to order more of those, Maybe I 164 00:10:24,720 --> 00:10:27,360 Speaker 1: need to order fewer of the models that are not 165 00:10:27,480 --> 00:10:30,480 Speaker 1: doing really well. And so you look at this information 166 00:10:30,480 --> 00:10:33,280 Speaker 1: and you see that the skates that have really good 167 00:10:33,320 --> 00:10:36,240 Speaker 1: breaks on them are the ones they're doing really well, 168 00:10:36,480 --> 00:10:39,400 Speaker 1: which makes sense in San Francisco, because otherwise you're just 169 00:10:39,400 --> 00:10:44,120 Speaker 1: gonna take off down that hill, hurtling to your destiny 170 00:10:44,320 --> 00:10:47,920 Speaker 1: until you just end up in the middle of the 171 00:10:47,920 --> 00:10:51,160 Speaker 1: Pacific Ocean, so you would never be seen again. It 172 00:10:51,240 --> 00:10:53,240 Speaker 1: makes sense that the roller skates would break, so the 173 00:10:53,280 --> 00:10:55,360 Speaker 1: ones that are doing really well. Now this is not 174 00:10:55,520 --> 00:10:59,040 Speaker 1: revolutionary these days, right. We are used to being able 175 00:10:59,080 --> 00:11:03,480 Speaker 1: to create ables in this way where we can create 176 00:11:03,559 --> 00:11:07,960 Speaker 1: different categories of features and then we can sort by that, 177 00:11:08,280 --> 00:11:11,280 Speaker 1: or we can filter by that, so that we're only 178 00:11:11,320 --> 00:11:15,080 Speaker 1: looking at the data that actually interests us, and everything 179 00:11:15,080 --> 00:11:19,000 Speaker 1: else gets hidden away so that it's not distracting. That's 180 00:11:19,000 --> 00:11:22,000 Speaker 1: not revolutionary today, But back then it was. This relational 181 00:11:22,080 --> 00:11:26,520 Speaker 1: database idea was a huge, huge notion, and at that point, 182 00:11:26,559 --> 00:11:32,480 Speaker 1: while cod was suggesting this particular model of handling information, 183 00:11:32,679 --> 00:11:36,160 Speaker 1: no one had yet found a way to implement it. 184 00:11:36,240 --> 00:11:39,680 Speaker 1: In an elegant way. All the different attempts were still 185 00:11:39,760 --> 00:11:42,840 Speaker 1: very much in the early phases. But Oates, having read 186 00:11:42,880 --> 00:11:46,400 Speaker 1: this paper, thought this sounds really really interesting to me. 187 00:11:46,480 --> 00:11:48,440 Speaker 1: I think that we can make a business out of 188 00:11:48,480 --> 00:11:51,800 Speaker 1: this because other businesses are going to want to be 189 00:11:51,880 --> 00:11:55,240 Speaker 1: able to sort their data in various ways. So if 190 00:11:55,360 --> 00:11:58,320 Speaker 1: we can figure out a way to build a software 191 00:11:58,360 --> 00:12:02,280 Speaker 1: platform where we can create eate database software for these companies, 192 00:12:02,880 --> 00:12:07,400 Speaker 1: that might be our entry point into the market. Maybe 193 00:12:07,400 --> 00:12:09,920 Speaker 1: that's how we actually start making our money. So the 194 00:12:10,000 --> 00:12:15,839 Speaker 1: databases in commercial use became known as relational database management systems, 195 00:12:15,960 --> 00:12:19,280 Speaker 1: also known as r D B M s S S so 196 00:12:20,040 --> 00:12:24,160 Speaker 1: are for relational dB for database, M for management, and 197 00:12:24,440 --> 00:12:29,760 Speaker 1: S for systems. And that would really transform data analysis. 198 00:12:30,160 --> 00:12:32,920 Speaker 1: But that's only part of the picture. So another part 199 00:12:33,040 --> 00:12:37,320 Speaker 1: was thanks to the computer scientists over at IBM. There 200 00:12:37,400 --> 00:12:40,319 Speaker 1: was a guy named Donald D. Chamberlain and another one 201 00:12:40,400 --> 00:12:44,040 Speaker 1: named Raymond F. Boyce. They had also read Cod's paper, 202 00:12:44,160 --> 00:12:47,240 Speaker 1: and they decided to create a type of programming language 203 00:12:47,320 --> 00:12:51,720 Speaker 1: that could manifest those ideas make them actually work. They 204 00:12:51,760 --> 00:12:54,920 Speaker 1: wanted to create a programming language that would end up 205 00:12:54,920 --> 00:12:57,600 Speaker 1: allowing you to create these kind of relational databases. So 206 00:12:57,640 --> 00:12:59,440 Speaker 1: they set to work and doing it, and there first 207 00:12:59,480 --> 00:13:03,480 Speaker 1: such a town was originally called Square, but Square proved 208 00:13:03,480 --> 00:13:06,319 Speaker 1: to be pretty clunky and inelegant. It had a lot 209 00:13:06,320 --> 00:13:08,360 Speaker 1: of limitations to it, so they decided to go back 210 00:13:08,360 --> 00:13:11,559 Speaker 1: to the drawing board and try again. Their second effort 211 00:13:11,960 --> 00:13:17,000 Speaker 1: they called sequel s q L, or sometimes they actually 212 00:13:17,000 --> 00:13:20,319 Speaker 1: would spell it out s e q L, and s 213 00:13:20,400 --> 00:13:24,640 Speaker 1: q L stands for structured Query Language. S e q 214 00:13:24,880 --> 00:13:28,560 Speaker 1: L was supposed to be structured English query language, and uh, 215 00:13:28,640 --> 00:13:30,719 Speaker 1: it was kind of a cheeky reference to also being 216 00:13:30,760 --> 00:13:33,120 Speaker 1: the second attempt to create such a language to make 217 00:13:33,160 --> 00:13:38,200 Speaker 1: these r D B M s is. So the sequel 218 00:13:38,280 --> 00:13:42,160 Speaker 1: language would in fact lend itself well to building this 219 00:13:42,240 --> 00:13:46,560 Speaker 1: kind of database. Now what came next, Well, I'll tell you, 220 00:13:46,960 --> 00:13:50,960 Speaker 1: but first let's take a quick break to thank our sponsor. 221 00:13:57,960 --> 00:14:01,480 Speaker 1: All Right, So we have this concept of relational databases 222 00:14:01,520 --> 00:14:05,280 Speaker 1: that cod had proposed. We've got the sequel language that 223 00:14:05,360 --> 00:14:09,440 Speaker 1: was developed by the scientists over at IBM, and the 224 00:14:09,480 --> 00:14:12,920 Speaker 1: three co founders decided they didn't want to challenge IBM 225 00:14:13,000 --> 00:14:18,280 Speaker 1: directly by creating database systems for mainframe computers. IBMS clients 226 00:14:18,640 --> 00:14:22,840 Speaker 1: tended to be really big companies, like really big ones, 227 00:14:23,560 --> 00:14:27,560 Speaker 1: and they were mostly using these large mainframe computer systems 228 00:14:27,960 --> 00:14:31,880 Speaker 1: that trace their origins back to the nineteen fifties. So instead, 229 00:14:32,320 --> 00:14:34,680 Speaker 1: the co founder said, what we should do is build 230 00:14:34,680 --> 00:14:38,920 Speaker 1: out a database system that can work on many computers. 231 00:14:39,480 --> 00:14:42,400 Speaker 1: Many computers are still pretty big, right they're not. They're 232 00:14:42,480 --> 00:14:44,720 Speaker 1: bigger than what a personal computer would have been. Like, 233 00:14:44,880 --> 00:14:47,880 Speaker 1: especially the many computers back in the nineteen seventies. They 234 00:14:47,920 --> 00:14:52,000 Speaker 1: were still large. Uh, they were less expensive than mainframes, 235 00:14:52,040 --> 00:14:54,800 Speaker 1: but they were also less powerful and they were more 236 00:14:54,840 --> 00:14:57,360 Speaker 1: frequently used by mid sized companies. It just made more 237 00:14:57,400 --> 00:15:00,560 Speaker 1: sense to go with many computers than may frames. Now, 238 00:15:00,600 --> 00:15:03,880 Speaker 1: the personal computers, those we would call micro computers, they're 239 00:15:03,880 --> 00:15:07,760 Speaker 1: even a size smaller. So the co founder said, well, 240 00:15:07,800 --> 00:15:10,000 Speaker 1: IBM is probably not going to go for that market. 241 00:15:10,440 --> 00:15:14,880 Speaker 1: They tend to concentrate on large companies, not mid sized companies. 242 00:15:15,400 --> 00:15:19,320 Speaker 1: So if we tailor a business for mid size companies, 243 00:15:19,800 --> 00:15:23,400 Speaker 1: there's probably a lot of opportunity there, and we don't 244 00:15:23,400 --> 00:15:27,480 Speaker 1: have to worry about IBM wanting to compete directly against 245 00:15:27,640 --> 00:15:31,320 Speaker 1: us or acquire us. We can do business our way. 246 00:15:31,400 --> 00:15:34,160 Speaker 1: And so ed Oates convinced his partners that building out 247 00:15:34,240 --> 00:15:37,240 Speaker 1: databases using the sequel language was the way to go, 248 00:15:37,560 --> 00:15:40,160 Speaker 1: and so the team got to work building their very 249 00:15:40,200 --> 00:15:45,160 Speaker 1: first software product, which was called Oracle. But there's a 250 00:15:45,200 --> 00:15:47,880 Speaker 1: bit more to it than that, because it was called 251 00:15:47,880 --> 00:15:52,280 Speaker 1: Oracle for specific reasons. So the software gots name from 252 00:15:52,320 --> 00:15:56,160 Speaker 1: a project that was being run by the first customer 253 00:15:56,480 --> 00:16:01,840 Speaker 1: SDL ever had. Remember STL stood for Software Element Laboratories. Well, 254 00:16:02,600 --> 00:16:08,200 Speaker 1: that customer was the little US agency called the c 255 00:16:08,480 --> 00:16:13,080 Speaker 1: i A, that is, the Central Intelligence Agency. That was 256 00:16:13,120 --> 00:16:17,480 Speaker 1: the first s d L customer, and the CIA had 257 00:16:17,520 --> 00:16:21,320 Speaker 1: a special project they were looking to complete called Oracle. 258 00:16:21,880 --> 00:16:26,120 Speaker 1: So what was the project about? Why did they need 259 00:16:26,160 --> 00:16:32,200 Speaker 1: a relational database? Well, who's to say it's classified? It's 260 00:16:32,200 --> 00:16:35,080 Speaker 1: probably cloak and dagger stuff. I do not have the 261 00:16:35,120 --> 00:16:37,960 Speaker 1: proper clearance to find out what exactly was going on. 262 00:16:38,040 --> 00:16:41,920 Speaker 1: It was all redacted. But STL took the project and 263 00:16:41,960 --> 00:16:44,280 Speaker 1: they had two years to complete the work and create 264 00:16:44,280 --> 00:16:47,400 Speaker 1: a relational database for the c i A. Bob Minor 265 00:16:47,720 --> 00:16:50,400 Speaker 1: did most of the work and creating the architecture for 266 00:16:50,480 --> 00:16:53,000 Speaker 1: the database, and they were able to turn in their 267 00:16:53,040 --> 00:16:56,000 Speaker 1: project a year ahead of schedule. They spent the following 268 00:16:56,080 --> 00:16:59,960 Speaker 1: year adapting this database approach so that they could create 269 00:17:00,320 --> 00:17:03,440 Speaker 1: a commercial product that they could sell to other companies. 270 00:17:03,800 --> 00:17:06,520 Speaker 1: So essentially, they said, well, we did this for the CIA, 271 00:17:06,720 --> 00:17:09,000 Speaker 1: let's just adapt it so that we can sell it 272 00:17:09,080 --> 00:17:13,240 Speaker 1: to anyone, really, any organization or a company that's out there. 273 00:17:13,680 --> 00:17:17,120 Speaker 1: So they decided to stick with the name the project 274 00:17:17,200 --> 00:17:20,439 Speaker 1: name the CIA project, which was called Oracle, and use 275 00:17:20,560 --> 00:17:24,240 Speaker 1: that to name their product, their software, their database software 276 00:17:24,400 --> 00:17:28,000 Speaker 1: thus became known as Oracle. By the way, there is 277 00:17:28,040 --> 00:17:32,600 Speaker 1: an allegation out there that Oracle actually started out as 278 00:17:32,640 --> 00:17:36,200 Speaker 1: a Russian software product that the c i A lifted 279 00:17:36,560 --> 00:17:41,320 Speaker 1: as in stall, and then handed over to SDL. I've 280 00:17:41,359 --> 00:17:46,000 Speaker 1: seen no confirmation of that allegation anywhere, and I'm inclined 281 00:17:46,040 --> 00:17:49,800 Speaker 1: to consider it outright false, as it really serves as 282 00:17:49,840 --> 00:17:52,600 Speaker 1: a huge injustice to the people like Bob Minor who 283 00:17:52,640 --> 00:17:55,680 Speaker 1: actually worked really hard to build out this database software. 284 00:17:56,160 --> 00:17:58,160 Speaker 1: But I just wanted to acknowledge the fact that there 285 00:17:58,280 --> 00:18:00,359 Speaker 1: is a rumor out there. I just don't think it 286 00:18:00,400 --> 00:18:04,639 Speaker 1: has any real credence. Also, the version that Ellison, Bob 287 00:18:04,680 --> 00:18:09,679 Speaker 1: Minor and Oates made commercially available wasn't just Oracle. It 288 00:18:09,800 --> 00:18:15,119 Speaker 1: was actually called Oracle Version two. So why was the 289 00:18:15,200 --> 00:18:18,320 Speaker 1: first version ever offered in the consumer market, known as 290 00:18:18,440 --> 00:18:23,000 Speaker 1: Version two. Well, it's because Larry Ellison thought no company 291 00:18:23,119 --> 00:18:26,680 Speaker 1: or organization would want to buy Version one of any 292 00:18:26,760 --> 00:18:30,520 Speaker 1: kind of software platform. They would worry about it being unproven, 293 00:18:31,119 --> 00:18:32,960 Speaker 1: and so he said, well, why don't we just call 294 00:18:33,119 --> 00:18:37,680 Speaker 1: this version two? Will bypass the problem. It was still 295 00:18:37,720 --> 00:18:40,840 Speaker 1: the first version of the Oracle software, it just had 296 00:18:40,920 --> 00:18:44,360 Speaker 1: the name Version two, which is sort of like forming 297 00:18:44,440 --> 00:18:48,040 Speaker 1: a brand new musical band and then calling your first 298 00:18:48,080 --> 00:18:53,600 Speaker 1: album your greatest Hits album, which is funny. There's a 299 00:18:53,600 --> 00:18:55,760 Speaker 1: lot of hutzpa there. In fact, hutzba is one of 300 00:18:55,800 --> 00:19:00,240 Speaker 1: those words that often gets used to describe Ellison. But 301 00:19:00,920 --> 00:19:04,320 Speaker 1: that's why the first version of Oracle was called Version two, 302 00:19:04,480 --> 00:19:06,920 Speaker 1: even though it was technically the first one. The company's 303 00:19:06,960 --> 00:19:09,600 Speaker 1: first hired to help them build out this software was 304 00:19:09,640 --> 00:19:13,720 Speaker 1: a programmer named Bruce Scott, and he started so early 305 00:19:13,840 --> 00:19:17,760 Speaker 1: with the others that he's frequently referred to as the 306 00:19:17,840 --> 00:19:22,240 Speaker 1: fourth co founder, but technically speaking, he was the company's 307 00:19:22,280 --> 00:19:26,280 Speaker 1: first hire. Scott worked on the first several versions of 308 00:19:26,320 --> 00:19:29,600 Speaker 1: the Oracle database software. Now, it took a couple of 309 00:19:29,640 --> 00:19:32,879 Speaker 1: years to get Oracle ready for commercial deployment from the 310 00:19:32,920 --> 00:19:36,560 Speaker 1: founding of the company. So again STL was founded in 311 00:19:36,640 --> 00:19:40,520 Speaker 1: nineteen seventy seven, but by nineteen seventy nine, Oracle was 312 00:19:40,560 --> 00:19:43,320 Speaker 1: ready to go, and the company formerly known as Software 313 00:19:43,320 --> 00:19:48,600 Speaker 1: Development Laboratories, had undergone a name change, but it still 314 00:19:48,840 --> 00:19:55,399 Speaker 1: wasn't called Oracle yet. Instead it became known as Relational Software, Incorporated. 315 00:19:55,720 --> 00:19:58,600 Speaker 1: And one wonders if they ever got contacted by people 316 00:19:58,960 --> 00:20:04,359 Speaker 1: who were compute dating enthusiasts, because Relational Software suggests to 317 00:20:04,400 --> 00:20:06,920 Speaker 1: me that maybe you can hook me up with miswrite. 318 00:20:07,240 --> 00:20:09,040 Speaker 1: I don't need that. By the way, I'm happily married. 319 00:20:09,400 --> 00:20:13,159 Speaker 1: The company's Oracle product soon became the go to for 320 00:20:13,359 --> 00:20:17,280 Speaker 1: lots of big companies and organizations, including other U. S. 321 00:20:17,320 --> 00:20:20,520 Speaker 1: Government and military clients. So in addition to the c 322 00:20:20,680 --> 00:20:23,800 Speaker 1: i A, there was the Air Force and the Navy. 323 00:20:23,840 --> 00:20:26,160 Speaker 1: In fact, depending upon whose account you read, the first 324 00:20:26,160 --> 00:20:30,560 Speaker 1: customer for the company wasn't the CIA, but instead was 325 00:20:30,600 --> 00:20:34,800 Speaker 1: the Air Force. Either way, the military and intelligence communities 326 00:20:34,840 --> 00:20:38,400 Speaker 1: were hot for relational databases, and it makes sense considering 327 00:20:38,400 --> 00:20:41,920 Speaker 1: how much information those organizations have to handle, So one 328 00:20:41,960 --> 00:20:46,280 Speaker 1: of their earliest non government contracts would be with Bell Labs, 329 00:20:46,359 --> 00:20:49,240 Speaker 1: another company that has a huge amount of information to 330 00:20:49,320 --> 00:20:51,439 Speaker 1: deal with, so it made sense that they wanted a 331 00:20:51,560 --> 00:20:55,320 Speaker 1: database software program where they could structure that data in 332 00:20:55,359 --> 00:20:58,159 Speaker 1: a way that was more useful. By the model for 333 00:20:58,200 --> 00:21:01,480 Speaker 1: business computing had shifted toward mini computers and the Unix 334 00:21:01,520 --> 00:21:04,520 Speaker 1: operating system for things like database management, So people were 335 00:21:04,520 --> 00:21:08,400 Speaker 1: moving away from having that enormous centralized computer that mainframe 336 00:21:08,600 --> 00:21:11,320 Speaker 1: inside their business. They were now starting to rely on 337 00:21:11,400 --> 00:21:16,959 Speaker 1: these relatively smaller mini computer workstations and the Unix operating 338 00:21:17,000 --> 00:21:20,760 Speaker 1: system so that they could actually do their work instead 339 00:21:20,760 --> 00:21:24,919 Speaker 1: of having this proprietary massive computer in their building. That 340 00:21:25,040 --> 00:21:29,120 Speaker 1: played right into this young company's strengths and admit, their 341 00:21:29,119 --> 00:21:32,000 Speaker 1: decision to focus on many computers was a big success, 342 00:21:32,080 --> 00:21:36,000 Speaker 1: and sales steadily began to climb. Now it wasn't a 343 00:21:36,200 --> 00:21:40,000 Speaker 1: runaway success right out of the gate, but they were 344 00:21:40,080 --> 00:21:44,880 Speaker 1: making regular sales. In one the company lured away former 345 00:21:44,920 --> 00:21:49,600 Speaker 1: IBM employee Umang Gupta to join as the seventeenth employee 346 00:21:49,640 --> 00:21:52,600 Speaker 1: of Relational Software. I'll be talking about some of the 347 00:21:52,640 --> 00:21:55,920 Speaker 1: other early employees in part two of this episode, because, 348 00:21:55,960 --> 00:21:59,240 Speaker 1: as it turns out, some people that were hired early 349 00:21:59,320 --> 00:22:03,080 Speaker 1: on stuck around with Oracle for quite some time. But 350 00:22:03,560 --> 00:22:07,000 Speaker 1: over that time they began to form some very strong 351 00:22:07,040 --> 00:22:12,840 Speaker 1: opinions about Larry Ellison and his managerial style. Anyway, back 352 00:22:12,840 --> 00:22:16,200 Speaker 1: to Gupta, his main priority was developing a business plan 353 00:22:16,320 --> 00:22:19,040 Speaker 1: for the company. Because you had these three guys who 354 00:22:19,040 --> 00:22:22,880 Speaker 1: had founded the company and they knew how to make 355 00:22:23,000 --> 00:22:26,400 Speaker 1: and market a product. Everyone said that Ellison was kind 356 00:22:26,400 --> 00:22:28,440 Speaker 1: of the marketing guy. He was the one who would 357 00:22:28,440 --> 00:22:32,240 Speaker 1: go out and sell the product, and Bob Minor was 358 00:22:32,320 --> 00:22:36,159 Speaker 1: the architect and at Oates was a developer. But they 359 00:22:36,200 --> 00:22:39,399 Speaker 1: weren't business guys in the sense that they weren't the 360 00:22:39,400 --> 00:22:43,440 Speaker 1: ones ready to run an enormous company um and so 361 00:22:43,680 --> 00:22:46,760 Speaker 1: doing things like developing a business plan was not exactly 362 00:22:46,800 --> 00:22:48,959 Speaker 1: in their strong suit. That wasn't one of their uh 363 00:22:49,440 --> 00:22:53,919 Speaker 1: there uh features. So Gupta came in and he created 364 00:22:53,960 --> 00:22:55,880 Speaker 1: a business plan for the company, and he was also 365 00:22:55,920 --> 00:22:59,960 Speaker 1: the vice president of the company's microcomputer products division. Now, 366 00:23:00,040 --> 00:23:04,240 Speaker 1: remember this was a time when personal computers, also known 367 00:23:04,280 --> 00:23:07,960 Speaker 1: as micro computers, were really starting to become a big success. 368 00:23:08,080 --> 00:23:11,680 Speaker 1: In the early nineteen eighties. The proliferation of computer systems 369 00:23:11,680 --> 00:23:15,320 Speaker 1: and businesses and homes created the opportunity for software companies 370 00:23:15,359 --> 00:23:18,280 Speaker 1: to go after new markets, and after a relatively short 371 00:23:18,320 --> 00:23:22,240 Speaker 1: stint at the company, Gupta would end up leaving along 372 00:23:22,240 --> 00:23:27,040 Speaker 1: with the first employee hire of Oracle's history, Bruce Scott, 373 00:23:27,760 --> 00:23:31,960 Speaker 1: and they would found Gupta Technologies, which later became cinur 374 00:23:32,080 --> 00:23:35,840 Speaker 1: A Software. Also in nineteen eighty one, the company began 375 00:23:35,880 --> 00:23:39,000 Speaker 1: to work on features that would expand Oracles, such as 376 00:23:39,040 --> 00:23:42,840 Speaker 1: the Interactive Application Facility. This was a tool that could 377 00:23:42,840 --> 00:23:47,479 Speaker 1: handle transaction processing forms, which doesn't sound exciting, but it 378 00:23:47,560 --> 00:23:52,640 Speaker 1: was an important development in the company changed names again, 379 00:23:53,240 --> 00:23:58,040 Speaker 1: except this time they finally became the Oracle we know today. 380 00:23:58,440 --> 00:24:00,920 Speaker 1: At that time, the company was enjoying two and a 381 00:24:01,000 --> 00:24:04,960 Speaker 1: half million dollars in annual revenue. To grow further, the 382 00:24:05,040 --> 00:24:08,200 Speaker 1: company leaders decided to invest a quarter of their revenues 383 00:24:08,480 --> 00:24:12,720 Speaker 1: back into research and development. So how did that pan out? Well, 384 00:24:12,760 --> 00:24:16,040 Speaker 1: I'll tell you, but first let's take another quick break 385 00:24:16,400 --> 00:24:26,400 Speaker 1: to thank our sponsor. As it turns out, this two 386 00:24:26,400 --> 00:24:29,639 Speaker 1: and a half million and annual revenue and then the 387 00:24:29,760 --> 00:24:32,760 Speaker 1: reinvestment into research and development paid off in a big way. 388 00:24:32,840 --> 00:24:36,680 Speaker 1: So the next big jump Oracle took was in three 389 00:24:36,840 --> 00:24:40,760 Speaker 1: when the company offered up a version of relational database 390 00:24:40,800 --> 00:24:45,160 Speaker 1: management software that could work on any sort of computer platform, 391 00:24:45,160 --> 00:24:51,720 Speaker 1: which included mainframes, workstations, and personal computers. This expansion doubled 392 00:24:51,840 --> 00:24:56,160 Speaker 1: company revenues for that year, which is pretty good validation 393 00:24:56,320 --> 00:25:00,840 Speaker 1: for your decision. This was Oracle version three, which really 394 00:25:00,880 --> 00:25:05,359 Speaker 1: means it was version two, because again they started with two, 395 00:25:05,400 --> 00:25:07,439 Speaker 1: not one. So you know what, when I tell you 396 00:25:07,560 --> 00:25:12,080 Speaker 1: version names, just mentally subtract one from the number, because 397 00:25:12,080 --> 00:25:15,200 Speaker 1: that's what it really was. Now. Version three was such 398 00:25:15,240 --> 00:25:18,560 Speaker 1: a big success that the company decided to push version 399 00:25:18,680 --> 00:25:22,320 Speaker 1: four out the following year, in nineteen eighty four. This 400 00:25:22,480 --> 00:25:26,160 Speaker 1: version included the ability to generate a report based on queries, 401 00:25:26,440 --> 00:25:29,520 Speaker 1: which again seems like a no brainer these days, but 402 00:25:29,600 --> 00:25:34,280 Speaker 1: it was a real innovation at the time by Oracle 403 00:25:34,359 --> 00:25:37,600 Speaker 1: was selling more than twenty million dollars a year in 404 00:25:37,680 --> 00:25:41,000 Speaker 1: software deals, and the company was getting into a very 405 00:25:41,119 --> 00:25:46,199 Speaker 1: young field, which was the Internet. In the Internet was 406 00:25:46,280 --> 00:25:48,960 Speaker 1: extremely young, not a lot of people knew about it, 407 00:25:49,560 --> 00:25:52,439 Speaker 1: but in fact, of course, that was a decade before 408 00:25:52,440 --> 00:25:55,600 Speaker 1: the Web would really become a thing, So this was 409 00:25:55,840 --> 00:26:00,560 Speaker 1: a pretty bold move. Um. Version five of our software 410 00:26:00,560 --> 00:26:04,480 Speaker 1: supported the ability for a machine running Oracle to log 411 00:26:04,520 --> 00:26:07,280 Speaker 1: into a database server, so you didn't have to rely 412 00:26:07,400 --> 00:26:11,000 Speaker 1: on computer systems that were co located anymore. With a 413 00:26:11,040 --> 00:26:14,080 Speaker 1: connection to the Internet, you could have computers in offices 414 00:26:14,119 --> 00:26:18,080 Speaker 1: around the world log into the same database. The version 415 00:26:18,200 --> 00:26:21,440 Speaker 1: also included an auditing feature that tracked all the times 416 00:26:21,640 --> 00:26:25,400 Speaker 1: someone accessed the database, which was a security and quality 417 00:26:25,400 --> 00:26:29,040 Speaker 1: control feature. So it didn't necessarily immediately tell you who 418 00:26:29,080 --> 00:26:31,439 Speaker 1: had accessed the database, but I would tell you the 419 00:26:31,480 --> 00:26:35,600 Speaker 1: location of that person or the person's computer and the time, 420 00:26:35,880 --> 00:26:38,359 Speaker 1: like what time did they access the database. So if 421 00:26:38,400 --> 00:26:40,600 Speaker 1: you go into the database and you think, well, that's weird, 422 00:26:41,040 --> 00:26:44,320 Speaker 1: three whole columns are missing. Someone accidentally deleted them. I 423 00:26:44,359 --> 00:26:46,439 Speaker 1: wonder who did that. You could actually go through the 424 00:26:46,480 --> 00:26:50,240 Speaker 1: audit list and find out who had last accessed that 425 00:26:50,480 --> 00:26:54,240 Speaker 1: particular database, and then you could go and pay them 426 00:26:54,240 --> 00:26:57,200 Speaker 1: a little visit and maybe ask them why they don't 427 00:26:57,200 --> 00:27:01,000 Speaker 1: like their kneecaps anymore. I'm assuming you're using the database 428 00:27:01,000 --> 00:27:03,879 Speaker 1: in the mafia. But the point being that this was 429 00:27:04,000 --> 00:27:08,240 Speaker 1: a new feature that allowed for greater tighter control not 430 00:27:08,359 --> 00:27:13,240 Speaker 1: just of the information but access to it. And they 431 00:27:13,359 --> 00:27:17,280 Speaker 1: hit fifty five million dollars in revenue. That's not profit, 432 00:27:17,359 --> 00:27:19,600 Speaker 1: that's in revenue, but still fifty five million is a 433 00:27:19,640 --> 00:27:22,520 Speaker 1: huge amount of money, and it was incredible growth for 434 00:27:22,560 --> 00:27:25,520 Speaker 1: the software company. That was also the year Oracle held 435 00:27:25,560 --> 00:27:28,960 Speaker 1: its initial public offering or i p O. That's when 436 00:27:28,960 --> 00:27:32,600 Speaker 1: a private company turns into a publicly traded one. The 437 00:27:32,680 --> 00:27:36,800 Speaker 1: initial price for a share of Oracle stock was fifteen dollars. 438 00:27:37,200 --> 00:27:41,440 Speaker 1: An Oracle created two point one million shares and made 439 00:27:41,440 --> 00:27:44,560 Speaker 1: them available. So you multiply those two numbers together and 440 00:27:44,600 --> 00:27:47,119 Speaker 1: you get the market value of the company, which was 441 00:27:47,200 --> 00:27:50,840 Speaker 1: thirty one and a half million dollars. So again you 442 00:27:50,920 --> 00:27:53,000 Speaker 1: just look at how much is it per share, how 443 00:27:53,040 --> 00:27:55,800 Speaker 1: many shares are out there. Multiply those two numbers together, 444 00:27:56,359 --> 00:27:59,040 Speaker 1: and that tells you the market value for a company. 445 00:27:59,080 --> 00:28:01,480 Speaker 1: By the way, if you want to know how much 446 00:28:01,560 --> 00:28:05,239 Speaker 1: a share of Oracle stock you bought back in the 447 00:28:05,320 --> 00:28:08,040 Speaker 1: days when it went public, how much would that be 448 00:28:08,040 --> 00:28:10,199 Speaker 1: worth today? You actually have to do a little bit 449 00:28:10,200 --> 00:28:14,000 Speaker 1: of math. The day I'm doing this research, So the 450 00:28:14,080 --> 00:28:17,560 Speaker 1: day I actually researched this information, Oracle stock came in 451 00:28:17,640 --> 00:28:21,240 Speaker 1: at forty six dollars per share or so, which means 452 00:28:21,280 --> 00:28:24,200 Speaker 1: it's about three times more than the initial offering at 453 00:28:24,200 --> 00:28:27,320 Speaker 1: fifteen dollars, which means you would triple your money. Right, 454 00:28:28,119 --> 00:28:30,760 Speaker 1: not so fast, because it gets way better than that. 455 00:28:31,320 --> 00:28:34,320 Speaker 1: If you just thought, oh, the stock prices three times 456 00:28:34,359 --> 00:28:36,479 Speaker 1: what it used to be, I make three times as 457 00:28:36,560 --> 00:28:41,240 Speaker 1: much money. Here's the thing. Oracle has split its stock 458 00:28:41,400 --> 00:28:45,320 Speaker 1: a few times. So splitting stock increases the number of 459 00:28:45,360 --> 00:28:48,040 Speaker 1: shares a company has out on the market, and it 460 00:28:48,160 --> 00:28:51,320 Speaker 1: also has the effect of lowering the price per share. 461 00:28:51,800 --> 00:28:54,360 Speaker 1: But you end up with twice as many shares if 462 00:28:54,400 --> 00:28:57,120 Speaker 1: you're doing a two for one split, and the overall 463 00:28:57,120 --> 00:29:00,040 Speaker 1: market valuation of the company will remain the same of 464 00:29:00,120 --> 00:29:03,520 Speaker 1: the moment. So, in other words, the market valuation has 465 00:29:03,560 --> 00:29:08,400 Speaker 1: to remain constant. You don't magically make the company more valuable. Right, 466 00:29:09,000 --> 00:29:12,200 Speaker 1: So if you already have your company valued at thirty 467 00:29:12,200 --> 00:29:16,600 Speaker 1: million dollars and you've got two million UH shares out there, 468 00:29:16,600 --> 00:29:18,880 Speaker 1: and you go to four million shares, your company is 469 00:29:18,880 --> 00:29:21,280 Speaker 1: still going to be worth thirty million dollars. It's just 470 00:29:21,360 --> 00:29:23,920 Speaker 1: that each share is going to be worth half as 471 00:29:24,000 --> 00:29:28,080 Speaker 1: much as it was before. So I have I do 472 00:29:28,120 --> 00:29:30,320 Speaker 1: it too. For one split, I double the number of 473 00:29:30,320 --> 00:29:32,680 Speaker 1: shares in my company. I also have the value of 474 00:29:32,720 --> 00:29:35,560 Speaker 1: the individual shares, because again, the value of my company 475 00:29:35,600 --> 00:29:38,040 Speaker 1: does not magically change. So I'm gonna give you a 476 00:29:38,080 --> 00:29:40,600 Speaker 1: full example here, Let's say that my company is worth 477 00:29:40,640 --> 00:29:44,240 Speaker 1: fifty million dollars and I've got two million shares out there, 478 00:29:44,240 --> 00:29:47,160 Speaker 1: which means each shares worth twenty five bucks before I split. 479 00:29:47,720 --> 00:29:50,120 Speaker 1: Then I split the stock two for one. Now there 480 00:29:50,120 --> 00:29:53,600 Speaker 1: are four million shares of my company out on the market, 481 00:29:53,800 --> 00:29:56,320 Speaker 1: which makes the price of each share go down to 482 00:29:56,400 --> 00:30:01,320 Speaker 1: twelve dollars and fifty cents. So when you split a stock, 483 00:30:01,560 --> 00:30:04,840 Speaker 1: if someone already owns stock, they get the benefit of 484 00:30:04,880 --> 00:30:07,240 Speaker 1: that split. Right. So if it's a two for one 485 00:30:07,280 --> 00:30:10,880 Speaker 1: split and I own ten shares of the company, now 486 00:30:10,880 --> 00:30:14,280 Speaker 1: I own twenty shares of the company. Each share is 487 00:30:14,320 --> 00:30:16,680 Speaker 1: half as expensive as it used to be, but I've 488 00:30:16,680 --> 00:30:20,040 Speaker 1: got twice as many. So why would I Why would 489 00:30:20,080 --> 00:30:22,800 Speaker 1: I bother splitting if the value of the company remains 490 00:30:22,800 --> 00:30:26,960 Speaker 1: the same. What's the point? Well, there's some psychological effects 491 00:30:27,080 --> 00:30:30,200 Speaker 1: when you split stock. If you were to take humans 492 00:30:30,240 --> 00:30:34,440 Speaker 1: out of the equation entirely, if you took human emotion out, 493 00:30:34,960 --> 00:30:37,640 Speaker 1: then it wouldn't really matter if you split the stock 494 00:30:37,720 --> 00:30:39,880 Speaker 1: or not. It wouldn't really have a big effect on 495 00:30:39,960 --> 00:30:44,600 Speaker 1: the company's performance. But we are human, we're the ones investing, 496 00:30:44,640 --> 00:30:47,840 Speaker 1: so it does matter. By splitting the stocks and reducing 497 00:30:47,840 --> 00:30:50,920 Speaker 1: the cost on a per share basis, you can improve 498 00:30:50,960 --> 00:30:54,120 Speaker 1: the liquidity of shares. People are more likely to trade 499 00:30:54,280 --> 00:30:59,200 Speaker 1: because they don't feel they don't feel frozen either by 500 00:30:59,200 --> 00:31:02,960 Speaker 1: holding onto stocks that are incredibly expensive, and therefore they 501 00:31:03,120 --> 00:31:10,040 Speaker 1: have the the the reputation of being valuable. And you 502 00:31:10,160 --> 00:31:15,480 Speaker 1: don't avoid investing because the entry price is too high. Right, 503 00:31:16,000 --> 00:31:19,360 Speaker 1: You've lowered the entry fee to buy stock by making 504 00:31:19,360 --> 00:31:22,240 Speaker 1: the stocks half as expensive. So you might have small 505 00:31:22,320 --> 00:31:25,920 Speaker 1: investors out there who would jump on shares of Oracle, 506 00:31:26,280 --> 00:31:28,720 Speaker 1: but if it's too expensive, they're like, I just I 507 00:31:28,760 --> 00:31:32,160 Speaker 1: can't buy a forty dollar stock that drops down to 508 00:31:32,200 --> 00:31:35,880 Speaker 1: twenty Oh, I can buy that. Then you get more investors, 509 00:31:35,920 --> 00:31:38,280 Speaker 1: So that's one of the reasons you might do it. 510 00:31:38,320 --> 00:31:40,840 Speaker 1: You might do it to try and encourage more trading, 511 00:31:41,360 --> 00:31:45,200 Speaker 1: to encourage more small investors, and you're also doing it 512 00:31:45,280 --> 00:31:49,080 Speaker 1: in an attempt to continue growing. So while you initially 513 00:31:49,640 --> 00:31:52,560 Speaker 1: reduce the price of those shares by half, they can 514 00:31:52,560 --> 00:31:57,240 Speaker 1: still climb up as the company does well. So uh, 515 00:31:57,320 --> 00:31:59,800 Speaker 1: that means the stock price can increase over time. So 516 00:32:00,040 --> 00:32:03,000 Speaker 1: over the course of Oracle's history, it is actually split 517 00:32:03,080 --> 00:32:07,600 Speaker 1: its stock ten times. Six of those were two for 518 00:32:07,720 --> 00:32:10,280 Speaker 1: one stocks, which meant if you held stocks an Oracle, 519 00:32:10,440 --> 00:32:12,840 Speaker 1: the number of shares would double each time it has 520 00:32:12,840 --> 00:32:15,640 Speaker 1: a two for one split, but four of the splits 521 00:32:16,240 --> 00:32:19,440 Speaker 1: we're three for two stock splits, meaning that for every 522 00:32:19,480 --> 00:32:22,280 Speaker 1: two shares you held, you would get a third one, 523 00:32:22,400 --> 00:32:25,600 Speaker 1: or if you prefer, for each share you got one 524 00:32:25,640 --> 00:32:29,920 Speaker 1: and a half shares. Right, So if you bought one 525 00:32:30,040 --> 00:32:34,840 Speaker 1: share of Oracle in nine six for fifteen dollars, after 526 00:32:35,040 --> 00:32:38,520 Speaker 1: all the stock splits, you would actually end up with 527 00:32:38,600 --> 00:32:43,200 Speaker 1: three hundred twenty four shares of Oracle, right, because of 528 00:32:43,200 --> 00:32:45,760 Speaker 1: each of the times they split, your number of shares 529 00:32:45,800 --> 00:32:48,760 Speaker 1: would increase. So if you add up all the different 530 00:32:48,800 --> 00:32:53,080 Speaker 1: ten splits, that one share turns into three four shares. 531 00:32:53,160 --> 00:32:56,320 Speaker 1: And it's not three four shares at fifteen dollars, which 532 00:32:56,360 --> 00:32:59,080 Speaker 1: is what you bought it at. It's three four shares 533 00:32:59,120 --> 00:33:02,360 Speaker 1: of Oracle at forty six dollars, which means your fifteen 534 00:33:02,360 --> 00:33:08,040 Speaker 1: dollar investment would turn into fourteen thousand, nine hundred four dollars. 535 00:33:09,160 --> 00:33:13,840 Speaker 1: Not bad, not bad to go from fifteen to fourteen 536 00:33:13,840 --> 00:33:18,680 Speaker 1: thousand bucks now almost fifteen thousand bucks now. Oracle clients 537 00:33:18,760 --> 00:33:23,040 Speaker 1: were pretty huge, which makes sense. Not a lot of 538 00:33:23,120 --> 00:33:27,400 Speaker 1: smaller organizations had real need for the robust databases Oracle 539 00:33:27,480 --> 00:33:31,760 Speaker 1: had to offer. Instead, Oracles products were appealing to bigger 540 00:33:31,880 --> 00:33:38,479 Speaker 1: organizations and companies industries like pharmaceutical companies, aerospace companies, tech firms, 541 00:33:38,520 --> 00:33:44,800 Speaker 1: automotive corporations. Those were among oracles top clients. In Oracle 542 00:33:44,920 --> 00:33:47,240 Speaker 1: launched a new division in the company. It was called 543 00:33:47,240 --> 00:33:51,480 Speaker 1: the Applications Division, and it initially had just seven employees 544 00:33:51,560 --> 00:33:54,560 Speaker 1: working in it. Their job was to put together application 545 00:33:54,600 --> 00:33:58,680 Speaker 1: software to integrate various functions with the database software to 546 00:33:58,760 --> 00:34:04,040 Speaker 1: make it easier to run routine tasks for large organizations. Essentially, 547 00:34:04,200 --> 00:34:07,440 Speaker 1: the thought was that the database software gave organizations a 548 00:34:07,440 --> 00:34:10,399 Speaker 1: lot of power to analyze their data, but they still 549 00:34:10,480 --> 00:34:13,080 Speaker 1: had to develop their own tools to put that data 550 00:34:13,080 --> 00:34:15,680 Speaker 1: to use. So Oracle was getting into the business of 551 00:34:15,760 --> 00:34:20,280 Speaker 1: developing applications that would do that for these companies. Oracle 552 00:34:20,320 --> 00:34:22,520 Speaker 1: didn't just rely on in house teams to do this. 553 00:34:22,680 --> 00:34:25,480 Speaker 1: The company also acquired a company called t c I 554 00:34:26,000 --> 00:34:29,399 Speaker 1: that built project management applications. The in house team got 555 00:34:29,400 --> 00:34:33,320 Speaker 1: to work building on an accounting module that could integrate 556 00:34:33,320 --> 00:34:36,360 Speaker 1: with Oracle databases, and this was the beginning of Oracle 557 00:34:36,400 --> 00:34:40,680 Speaker 1: creating a suite of software applications that could work closely together. 558 00:34:41,000 --> 00:34:45,720 Speaker 1: Branching out from being a purely database focused company, Oracle 559 00:34:45,840 --> 00:34:49,680 Speaker 1: also launched a consulting service to offer support to clients, 560 00:34:49,760 --> 00:34:53,239 Speaker 1: helping them best understand how to leverage Oracle software. So 561 00:34:53,280 --> 00:34:57,000 Speaker 1: now not only could the company sell its products to customers, 562 00:34:57,440 --> 00:35:00,680 Speaker 1: it could keep earning money from those same kind customers 563 00:35:00,719 --> 00:35:03,400 Speaker 1: by explaining to them how to use their own products, 564 00:35:03,680 --> 00:35:06,480 Speaker 1: which is pretty much genius. In fact, this was a 565 00:35:06,640 --> 00:35:10,120 Speaker 1: top revenue generator for Oracle, was not just selling the product, 566 00:35:10,320 --> 00:35:15,040 Speaker 1: but selling ongoing support for the product. In the company 567 00:35:15,080 --> 00:35:18,200 Speaker 1: was outgrowing its home base, and so it relocated to 568 00:35:18,280 --> 00:35:23,040 Speaker 1: Redwood Shores, California. It launched a subsidiary company called Oracle 569 00:35:23,160 --> 00:35:25,960 Speaker 1: Data Publishing that was all about getting hold of data 570 00:35:25,960 --> 00:35:29,719 Speaker 1: and then distributing it electronically, and the company sought out 571 00:35:29,760 --> 00:35:34,400 Speaker 1: new industries and branches of computing to expand into, including supercomputers. 572 00:35:34,880 --> 00:35:37,000 Speaker 1: The following year would end up being a tumultuous one 573 00:35:37,040 --> 00:35:41,040 Speaker 1: for Oracle, which had to make for a pretty ugly 574 00:35:41,080 --> 00:35:44,719 Speaker 1: admission for a company all about crunching numbers, because the 575 00:35:44,760 --> 00:35:48,680 Speaker 1: company turns out it had misrepresented revenues, whether on purpose 576 00:35:48,760 --> 00:35:52,239 Speaker 1: or by accident. It was not a pretty picture. And 577 00:35:52,280 --> 00:35:55,120 Speaker 1: that's how we're gonna start our next episode of the 578 00:35:55,160 --> 00:35:59,760 Speaker 1: Oracle Story talking about this massive controversy that the company 579 00:35:59,800 --> 00:36:02,719 Speaker 1: and countered early in its history and what it had 580 00:36:02,760 --> 00:36:05,480 Speaker 1: to do in order to climb back out again. In fact, 581 00:36:05,560 --> 00:36:09,160 Speaker 1: it was so bad that there was a real danger 582 00:36:09,640 --> 00:36:14,360 Speaker 1: of Oracle going away and not surviving. Now, as it 583 00:36:14,400 --> 00:36:16,680 Speaker 1: turns out, Oracle still around today, so you kind of 584 00:36:16,719 --> 00:36:21,560 Speaker 1: know things work out, but back then people weren't so sure. Now, 585 00:36:21,600 --> 00:36:24,760 Speaker 1: if you have suggestions for future episodes of tech Stuff, 586 00:36:24,800 --> 00:36:26,759 Speaker 1: I welcome you to write me and let me know 587 00:36:26,800 --> 00:36:29,560 Speaker 1: what they are. The email address for this show is 588 00:36:29,640 --> 00:36:32,440 Speaker 1: tech Stuff at how stuff works dot com, or you 589 00:36:32,440 --> 00:36:34,960 Speaker 1: can drop me a line on Twitter or Facebook. The 590 00:36:34,960 --> 00:36:37,239 Speaker 1: handle for both of those is tech Stuff hs W. 591 00:36:37,760 --> 00:36:39,960 Speaker 1: Remember we have an Instagram account. You can go and 592 00:36:40,000 --> 00:36:41,800 Speaker 1: follow us there and see all the behind the scenes 593 00:36:41,800 --> 00:36:45,880 Speaker 1: stuff and some other interesting things. Also, remember I broadcast 594 00:36:46,040 --> 00:36:50,120 Speaker 1: my recording sessions live on twitch dot tv slash tech Stuff. 595 00:36:50,520 --> 00:36:53,760 Speaker 1: Just go there. You'll see when I tend to stream. 596 00:36:53,800 --> 00:36:57,959 Speaker 1: It's on Wednesdays and Fridays, but there's a schedule up there, 597 00:36:58,000 --> 00:37:00,359 Speaker 1: so go there. You can jump into the chat room 598 00:37:00,400 --> 00:37:03,600 Speaker 1: and be part of the shenanigans. What goes on when 599 00:37:03,640 --> 00:37:06,200 Speaker 1: I record? I hope to see you there and I'll 600 00:37:06,200 --> 00:37:14,160 Speaker 1: talk to you again. Really sick for more on this 601 00:37:14,360 --> 00:37:16,880 Speaker 1: and thousands of other topics. Is it how stuff works 602 00:37:16,880 --> 00:37:27,040 Speaker 1: dot com