Unpacking the Database-AI Connection: Why It Matters

In this episode host Lorna Juma speaks with Dr. Lawrence Nderu on Unpacking the Database-AI Connection and Why It Matters. If you’re an educator, student, or tech enthusiast curious about the backbone of artificial intelligence systems, this episode is your gateway to understanding the vital role of databases in artificial intelligence and machine learning. ----------------------------------------------------------- Episode Transcript:

00;00;09;02 - 00;00;35;04 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. Welcome to the Oracle Academy Tech Chat, where we discuss how Oracle Academy prepares the next generation's Laplace.

00;00;35;06 - 00;01;08;10 I'm your host, Lorna Juma. In this episode, I am joined by Doctor Laurence Darrow, a lecturer and research fellow in the Department of Computing at Jomo Kenyatta University of Agriculture and Technology. Today, we're uncovering how databases, power artificial intelligence and machine learning, two of the most transformative forces in the tech world. If you're an educator, student, and tech enthusiast curious about the backbone of AI systems, this episode is your gateway to understanding the vital role of databases in AI and machine learning.

00;01;08;12 - 00;01;35;11 To start off, Doctor Lawrence, thank you so much for joining us. Can you give me a bit about your background and the classes you teach? Yeah. Thank you so much for having me. I really think that this is a very important conversation and happy and, to work with you guys to promote the use of these solutions and these technologies for the purpose of making sure that, we have a generation that is well informed and ready for work.

00;01;35;13 - 00;02;06;07 So to start with, I am a lecturer and also the chairman, Department of Computing at the Jomo Kenyatta University of Agriculture and Technology. I'm also the founder of Jacob Moffett, which is a digital innovation hub that is based at the University of Jomo Kenyatta in Gloucester. Work and culture. In technology. I currently I do teach units that relates to AI and machine learning and also applied machine learning.

00;02;06;10 - 00;02;34;01 I also do supervise the students at the level of BHB and Masters. While working on areas of AI and machine learning. And those are the areas that that that the working on. I also read research teams that are working on innovations and I Jacob, in terms of building solutions that are using AI as the basis for, solving some problems and also others that are using AI to improve the operations.

00;02;34;03 - 00;03;00;17 Thank you, doctor Larry Entwistle. Glad to have you join us as an expert to discuss this important topic. Now, could you break down the fundamental relationship between databases and AI? Why are robust databases critical for building effective AI models? Thank you. So the first thing is that the data is the food for AI. And we have had the same being said every now and then.

00;03;00;17 - 00;03;29;18 That data is the new oil. And I think that also means that we need these data to be data that is accessible in a way that is use that work. I mean, and efficient manner. So, it means that AI is being powered by data and whether this data is structured data or unstructured data. We need data to be know about is accessible and also accessible in an efficient manner.

00;03;29;20 - 00;04;01;18 So the connection really is the fact that traditionally when we dealt with the data, we were looking at it like say more or less data that was relational based databases. Now we know that data is found in many other formats. We have data, of course, in structured. We have data in semi-structured. We have data in unstructured formats. All these data needs to be stored in ways that it can be consumed, be consumed by AI, systems.

00;04;01;21 - 00;04;28;27 And that's where now the connection comes. Because the better the data, the better you are able to create models in the AI that are effective. And they are also able to answer very many questions that that one would want. So to answer that question is that the connection is clear, that we need, data to power AI systems, and we need systems that can be able to store these data in a way that that, that I can consume it in a better way.

00;04;28;27 - 00;04;54;06 And we have the pipeline. We need that pipeline that provides data and then feeds into the, AI models or AI systems so that they can be able to make decisions and improve our ability. And now, as an educator and researcher, how do you recommend teachers and institutions incorporate database hands on teaching into their AI and machine learning curricula?

00;04;54;09 - 00;05;25;13 What approaches or tools have you found most effective for engaging student in this critical area? Number one is that if I may just mention something about as a Jomo Kenyatta, we reviewed our curriculum and one of the things that we did, in the reading of the curriculum that is currently being used is that we are very keen to make sure that we retain and then and force the aspect of covering database systems.

00;05;25;16 - 00;05;57;22 So there is and you cover sections in database systems in detail, looking at how to design them to the extent of looking at the advanced concept in databases, which of course goes to the extent of talking about considering security and such aspect in databases. So, it is a very important component to when you are teaching databases, one has to consider, number one, the fact that these are the people who then go ahead and now come on.

00;05;57;24 - 00;06;26;28 I introduction to AI and also machine learning. And they will be consuming these, these databases. So what we have done is that we, able to provide this background and then when it comes to no coverage tools like Oracle databases, the country AI, which of course, I found very important because it uses AI in vector search, for data retrieval, analysis of AI driven applications.

00;06;26;28 - 00;06;52;14 It's a very well thought up idea in terms of trying to integrate advanced AI, capabilities directly to the database engine. The idea behind this is because we, we would want smart data handling capability to be ingrained in the data. We would want to have advanced analytics to be also, ingrained within these, these kind of databases.

00;06;52;17 - 00;07;20;04 And also if you think about known going to the industry, we would be the industries would work to get, insights from their data on what they can be able to do with that. So what I would say is that when you are now teaching and you look at, you have taught concept in databases, and now when you go to teaching things like machine learning or AI, you are able to show that compute the students or even the runners.

00;07;20;06 - 00;07;42;05 The connection between having a good foundation in databases and using various tools and understanding how to make use of, various, tools that are coming up. Like I mentioned, data restrict the I was at points that I needed, making the process of, being able to, to get insights from your data are very important.

00;07;42;10 - 00;08;11;12 So it means that these people, when they go in the industry, they have skills and practical skills that they can be able now to demonstrate in the industry that whatever they are, brand has value and they can and value to the businesses. So it is very relevant that as we teach, first of all, the thinking through about the curriculum, the way it is designed in such a way that it allows for students to do practical concept that leads them to be applicable to the industry.

00;08;11;15 - 00;08;52;00 It's very important and includes that exist within for or instructor for instructors that that are already online that that they can be able to use some of the courses that that are being designed for them, that they can be able to use the event for, programing, databases, that exist today at PL SQL. Like I mentioned one, we have a database programing with SQL itself to be able to give a foundation and then going to things like, artificial intelligence so that the concept in artificial intelligence, we don't just think that they can only be implemented in Python, we can implement them in Java, we can implement them in other things.

00;08;52;02 - 00;09;14;11 We just need to understand the concept. And then we are able to do that practically. That's that. That it empowers that person, empowers the students, that eventually we are able to get our, you know, our system, having done those practical’s. And now for students interested in pursuing a career in, I do think they should start by building a strong foundation in database skills.

00;09;14;14 - 00;09;39;08 How does database knowledge empower their journey in AI and machine learning? Well, I think that what I would say is, number one is that if you look at the Oracle Academy, which, is a tool that is really very valuable, to teach and also, demonstrate some of the tools that also exist and also provision of software tools, cloud and also software tools.

00;09;39;10 - 00;10;00;18 And we also have BigQuery. But you can download content that you can download. And it also provides assessment that you can use in class. The idea is that you don't have to use it the way it is. You can take it and then you add or even subtract the items that you want to do it. So it's content that is ready and you can use it as it is.

00;10;00;18 - 00;10;34;23 Or you can be to, custom it the way you would want. It allows for, researchers to be able to focus on being able to improve and having something that we can start with. So, the