The importance of data and continuous learning

Oracle Academy Tech Chat

In this episode host Orlaith Lawton speaks with Oracle Ace Director Finland Heli Helskyaho about the importance of data and continuous learning. --------------------------------------------------------- Episode Transcript: 00;00;09;03 - 00;00;37;15 Welcome to the Oracle Academy Tech Chat. This podcast provides educators and students in-depth discussions with thought leaders around computer science, cloud technologies and software design to help students on their journey to becoming industry ready technology leaders. Of the future. Let's get started. Hello, everybody. Today, in February 2024, my name is Orlaith Lawton that I'm the Oracle Academy and Media Marketing Manager. 00;00;37;17 - 00;01;08;27 And I'm delighted to say I'm here with my colleague Rania Herberg, who represents Oracle Academy in Helsinki. And Heli Helskyaho. She is the CEO for Miracle Finland OY. She also holds a master's degree in computer science from the University of Helsinki, and she's specialized in databases. 00;01;08;29 - 00;01;44;15 At the moment, she's working on her doctoral studies at the University of Helsinki. And Henry has actually been working on it since 1990. She's also an Oracle ace director and a frequent speaker at my company since she's also an author of Oracle as well. Developer Data Monitor for Database Design Mastery and a coauthor of Real World School and Feel and School Advice from the Experts, Machine Learning for Oracle Database Professionals and several other books. 00;01;44;18 - 00;02;13;01 So we are absolutely delighted to have you here, Heli. Thank you so much for joining us. And let me start off by maybe talking a little bit about to as I mentioned, you're an author and you're very interested in data and it's fantastic to have a female voice in technology. Perhaps you can give us a little bit of background about your role and how you got into technology and became an oracle ACE 00;02;13;02 - 00;02;35;01 So I always love to answer this that I always wanted to be in tech and I always loved computers and that kind of stuff, but I didn't. I actually hated computers, so I was studying mathematics and I didn't know what I want to do when I grow up. And I my father told me to take some computer science classes and I was thinking, okay, why not? 00;02;35;04 - 00;02;55;20 Because actually learning was always very easy for me. So I was thinking, it's going to be a piece of cake, you know, just some computers and that's it. But it was not. So when I took the first course, I barely passed and I didn't understand anything. So that was so frustrating because I was the A-plus student. And I just, you know, didn't understand anything. 00;02;55;28 - 00;03;16;07 So I was blaming the teacher. The teacher must be bad. And I will take another course that is taught by another teacher. But the same happened again. And then I was thinking, it cannot be the teacher, it must be me. So there's something I don't understand about computers and the computer science. And because I always loved challenges, I decided I will take more courses. 00;03;16;07 - 00;03;36;19 I never give up. So I always like to fight. So I was saying, I need to know what. What's the problem? Why don't I understand anything? And I took more and more courses. Finally, I took all their courses you can take as a minus student. And I was thinking, I still don't know anything. So I had to change my major and start with computer science. 00;03;36;20 - 00;03;58;03 So I went to see the faculty principal and I said, I want to change the computer science. And he was like, Are you kidding you? You're very good in math, but you are no good in computer science. So why do you want to change? I said, Well, you just described it. That's why. Because I really don't understand computer science, and I want to understand. 00;03;58;10 - 00;04;18;01 That's why I want to change. And he was okay, I'll sign the paper. But if you if you just decide you made a mistake, come back. But then suddenly I started to understand when I came to data and databases and all this kind of thing, I realized this is my field, so this is what I wanted to do. 00;04;18;03 - 00;04;48;18 Then I was also hired by a computer factory. So I was. I was able to see how the computer is built and it's not rocket science. So I realized this is very understandable for even somebody who is not very technical. If you could say that I'm a super tester, so I break everything I touch. So they didn't let me build any computers, but it was very, very intuitive to see the pieces that you used to build a computer and it somehow made it understandable to me. 00;04;48;19 - 00;05;13;28 So it's it's, it's not that difficult. So kind of after all that struggle, I realized that computer science is definitely for me. And I have never regret my decision. So finding data, finding databases, and now lately machine learning as well. I am so happy where I am at the moment. So this is definitely my career. So what I could tell everybody else is never give up. 00;05;13;28 - 00;05;36;26 So if you feel like you don't know something, it's just a little bit something that should be explained in another way or something that you should try yourself to understand what it actually means. So it doesn't mean that you are stupid or you are not technical or you are not whatever. It's just that you are missing a piece of information and that's why you don't understand. 00;05;36;28 - 00;06;05;09 So yeah, that's my story. In short, and I'm working on my Ph.D. So yeah, computer science is definitely for somebody who doesn't like computers in the beginning. That's really good to hear. That's really interesting to hear how you almost accidentally got into it, because I think it sounds like it was a challenge to more than anything else. But perhaps then you could give or this is more information as to the main subject areas of expertise such as data and how that has helped you in your career. 00;06;05;12 - 00;06;33;08 Well, yeah. So data, I think is everything. So there is nothing in any business if you don't have data. So that's kind of whatever the customer is working on. It's always related to data. So I think that's the reason why I find data very interesting because it has the answer to all the questions that you might have, and that leads to data quality, which is one of my favorite topics. 00;06;33;13 - 00;06;54;29 So saving any kind of data makes no sense. It has to be a good quality data, and that's why database designing is important. That's why machine learning comes important when you have good quality data. So if you have bad data, you can't do any machine learning, You can't build data warehouses, you can't do anything with bad quality data. 00;06;55;01 - 00;07;20;11 So that kind of is my favorite thing. And highlighting that good quality data is the key to everything I may need to touch back on what you were saying earlier on about computer programing, computer science and subject for those who are maybe not naturally inclined to think about it or go into it. And as you know, we have a lot of men in the technology world. 00;07;20;11 - 00;07;45;22 We don't have as many women, unfortunately. And how would you encourage girls who may be interested in trying something new and going into technology or haven't thought about even how? What would you say to girls thinking about technology? So first of all, I've been doing quite a lot of mentoring, and I usually start with the fact that people are saying that I'm not a good developer, so I cannot be on it. 00;07;45;25 - 00;08;09;07 You couldn't be more wrong because it is not about developers. It's about all kind of skill sets that you need. Developer is just one of these personas, but there's so many other skill sets that are needed in the area. So it doesn't mean if you don't like to be a developer and if you don't like programing, it doesn't mean that it's not for you because there's so many other things. 00;08;09;09 - 00;08;33;23 And I think the biggest challenge is that if if you are able to see a big picture, it's not just, you know, small, tiny details, but big pictures, you would be very welcome to it because we need people with that skill, you know, understanding. What is the big picture here? What are we trying to do? And then we have a lot of people who know the details and they are very much needed. 00;08;33;25 - 00;08;56;28 But we don't have enough people who can see big pictures. And I have so far experience that women are actually quite good in that, you know, they are raising families with a lot of children and husband and everything. And so many things are happening. And you still have to hold that project going on. So the family still has to be doing well and everything should be fine. 00;08;57;04 - 00;09;22;01 So a lot of these women are very good with big pictures and coordinating things. And I think that is the skill set that is definitely needed on it. So if you think you are not a developer, it does not mean that you are not welcome to it. There are other positions as well. A lot of that. I suppose that leads me on to the female voice in a I. 00;09;22;03 - 00;09;50;04 Obviously we think it's important to encourage girls to move into technology and learn more about us. And how important do you think it is to have a female voice, so to speak, in AI in the future? So, you know, everybody is the same and everybody thinks the same. We will have no improvements in anywhere, so we should have different kind of people who are thinking differently and seeing different things so that we can improve whatever the area is. 00;09;50;04 - 00;10;18;00 And the same goes with AI and data and all this kind of things. So we should have different people who see things differently and that's why we should have a lot of different voices to to make the field better. But also, if I think about ladies in general, I think the problem is that we are we have to be 120% sure we know something before we are ready to do it. 00;10;18;03 - 00;10;38;14 While as men, if they know about 50% of the stuff, they said, yeah, I'm very good in that. I can do that and they can, but we could also do the same. But we are just too demanding to ourselves, so we we expect too much from ourselves and that is a problem. We should get rid of that and be brave and trust ourselves. 00;10;38;17 - 00;11;02;16 That would help a lot. So we do have skills, but we are just too shy to show them. And this other question then, in relation to data, why is it important for faculty to teach their students about data? And how does having data these skills prepare students for future jobs? First of all, data, as I said, is the key to everything. 00;11;02;19 - 00;11;33;20 But secondly, if you think about database designing, that kind of teaches you how to think logically. So you have defined entities, how the entities are related to each other, all this kind of thing. So kind of teaches theological thinking and the same skill you need in many other areas as well. So if you learn logical thinking with data, whatever the business is that you will be working on later, this skill is definitely a good bonus for whatever. 00;11;33;22 - 00;12;03;20 So yeah, knowing databases, knowing how to design databases, understand ending what data is about is the key to many, many positions. Well, absolutely. Of course, for that good quality data as well. So if you understand data, you will have good quality data. But yes, the logical thinking is number one. Perhaps. One final question then. If you could give one piece of advice to faculty or students, what would that be? 00;12;03;22 - 00;12;27;25 What I learned when I was at the university as a very young student, I was often told that you probably don't understand this. How would they know what I understand it, what I don't understand? So my advice is that you know yourself and trust yourself and don't let the others tell you what you can or what you cannot do because it's your life. 00;12;27;28 - 00;12;54;07 So you should be the one who is in charge of your life. And don't let anybody else to diminish your your you as a person or you as a student or a teacher as well. So definitely, you know what you can you also know what you can't. But that's something that you could be improving so that you would you would know more and you would be able to do more. 00;12;54;09 - 00;13;15;19 So instead of just seeing the bad things like I am not very good in math or I'm not very good in English or I'm not very good, you'll say that, say what you are good at, and then those that you are not so good at improve those skills and you will be much more good in everything eventually. Excellent. 00;13;15;19 - 00;13;40;21 That's fantastic advice for students and faculty. I may just ask Rania if she would like to ask a final question to or against Halley. My final question that's actually coming from my personal background and from my personal point of view, as well as from a leading I.T, as well as all of us here. But my background is in business, international management and psychology. 00;13;40;23 - 00;14;06;13 I mean this topic that you actually touched upon previously as well, but do you have any advice for the ladies that are studying this kind of non STEM related topics and still have the aspiration to maybe peeking into the field or of technology? What would be the first step? Well, I think now is a lot easier than it was before because we have lot of all kind of certification courses and MOOC and all this kind of thing. 00;14;06;13 - 00;14;35;28 So you are able to study, even though you are not joining university or taking any particular courses. So you can you can either spend your own time or your company's time learning about new things like at the moment, narrative. AI is quite an interesting topic for many of us. A AI in general is quite interesting, so you can just take some courses and get the understanding of what what are people talking about may be fundamental. 00;14;35;28 - 00;14;54;19 Also something like that. It doesn't have to be deep technical, but it can be something that gives you the understanding what are they talking about? So that kind of gives you the feeling that you understand what people are saying and you don't feel like you're left out because you are just like, this is a strange word. I have never heard about it. 00;14;54;19 - 00;15;20;02 So I will not listen. I'm just whatever. So it kind of includes you in the community. If you if you take those courses and and you understand what what or what are these people talking about? And as I said, this is not very difficult. So this is quite easy. It's just that I think we tend to make it look difficult because we use difficult words. 00;15;20;05 - 00;15;40;09 And my favorite we use several words for the same thing just to confuse you. So especially in AI, that is the thing. So the same thing is called with different names and then you feel like, I'm too confused. I don't understand anything, and you stop listening, so don't let that happen and don't let us do that either. 00;15;40;09 - 00;16;04;06 So if we are talking nonsense and if we are trying to make it look complicated, just say that. Can you say that in simple words and don't make it too complicated? Well, thank you so much, Shelly. That's very encouraging. I think you've made us all think it's within our reach to enjoy and understand technology, the importance of diversity and the importance of being yourself. 00;16;04;13 - 00;16;29;06 Well, thank you so much, Heli, and thank you on you as well for joining us. And your contribution is a very broad question. And thank you for sharing your knowledge about data. It what's coming in relation to AI and the slack that we should all be open to it and experiment and explore. Thank you. Also listening and I hope you join us for an exit search that wraps up this episode. 00;16;29;13 - 00;16;34;11 Thanks for listening and stay tuned for the next Oracle Academy Tech chat podcast.