Database Essentials

Oracle University Podcast

Join hosts Lois Houston and Nikita Abraham, along with Hope Fisher, Oracle’s Product Manager for Database Technologies, as they break down the basics of databases, explore different database management systems, and delve into database development. Whether you're a newcomer or just need a refresher, this quick, informative episode is sure to offer you some valuable insights.

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Special thanks to Arijit Ghosh, David Wright, Radhika Banka, and the OU Studio Team for helping us create this episode. -------------------------------------------------------- Episode Transcript:

00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we’ll bring you foundational training on the most popular Oracle technologies. Let’s get started!

00:26 Nikita: Hello and welcome to the Oracle University Podcast. I’m Nikita Abraham, Principal Technical Editor with Oracle University, and with me is Lois Houston, Director of Innovation Programs.

Lois: Hi there! For the last seven weeks, we’ve been exploring the world of OCI Container Engine for Kubernetes with our senior instructor Mahendra Mehra. We covered key aspects of OKE to help you create, manage, and optimize Kubernetes clusters in Oracle Cloud Infrastructure. So, be sure you check out those episodes if you’re interested in Kubernetes.

01:00

Nikita: Today, we’re doing something a little different. We’ve had a lot of episodes on different aspects of Oracle Database, but what if you’re just getting started in this world? We wanted you to have something that you could listen to as well. And so we have Hope Fisher with us today. Hope is a Product Manager for Database Technologies at Oracle, and we’re going to ask her to take us through the basics of database, the different database management systems, and database development.

Lois: Hi Hope! Thanks for joining us for this episode. Before we dive straight into terminologies and concepts, I want to take a step back and really get down to the basics. We sometimes use the terms data and information interchangeably, but they’re not the same, right?

01:43

Hope: Data is raw material or a set of facts and observations. Information is the meaning derived from the facts. The difference between data and information can be explained by using an example, such as test scores. In one class, if every student receives a numbered score and the scores can be calculated to determine a class average, the class average can be calculated to determine the school average. So in this scenario, each student's test score is one piece of data. And information is the class’s average score or the school's average score. There is no value in data until you actually do something with it.

02:24

Nikita: Right, so then how do we make all this data useful? Do we create a database system?

Hope: A database system provides a simple function—treat data as a collection of information, organize it, and make the data usable by providing easy access to it and giving you a place where that data can be stored. Every organization needs to collect and maintain data to meet its requirements. Most organizations today use a database to automate their information systems. An information system can be defined as a formal system for storing and processing data. A database is an organized collection of data put together as a unit. The rationale of a database is to collect, store, and retrieve related data for use by database applications. A database application is a software program that interacts with the database to access and manipulate data. A database is usually managed by a Database Administrator, also known as a DBA.

03:25

Nikita: Hope, give us some examples of database systems.

Hope: Popular examples of database systems include Oracle Database, MySQL, which is also owned by Oracle, Microsoft SQL server, Postgres, and others. There are relational database management systems. The acronym is DBMS. Some of the strengths of a DBMS include flexibility and scalability. Given the huge amounts of information that modern businesses need to handle, these are important factors to consider when surveying different types of databases.

03:59

Lois: This may seem a little bit silly, but why not just use spreadsheets, Hope? Why use databases?

Hope: The easy answer is that spreadsheets are designed for specific problems, relatively small amounts of data and individual users. Databases are designed for lots of data, shared information use, and complex data analysis. Spreadsheets are typically used for specific problems or small amounts of data. Individual users generally use spreadsheets. In a database, cells contain records that come from external tables. Databases are designed for lots of data. They are intended to be shared and used for more complex data analysis. They need to be scalable, secure, and available to many users. This differentiation means that spreadsheets are static documents, while databases can be relational.

04:51

Nikita: Hope, what are some common database applications? Hope: Database applications are used in far and wide use cases that most commonly can be grouped into three areas. Applications that run companies called enterprise applications. Enterprise applications are designed to integrate computer systems that run all phases of an enterprise's operations to facilitate cooperation and coordination of work across the enterprise. The intent is to integrate core business processes, like sales, accounting, finance, human resources, inventory, and manufacturing.

Applications that do something very specific, like healthcare applications-- specialized software is software that's written for a specific task rather than for a broad application area. And then there are also applications that are used to examine data and turn it into information, like a data warehouse, analytics, and data lake.

05:54

Lois: We’ve spoken about data lakes before. But since this is an episode about the basics of database, can you briefly tell us what a data lake is?

Hope: A data lake is a place to store your structured and unstructured data as well as a method for organizing large volumes of highly diverse data from diverse sources. Data lakes are becoming increasingly important as people, especially in businesses and technology, want to perform broad data exploration and discovery. Bringing data together into a single place or most of it into a single place makes that simpler.

06:29

Nikita: Thanks for that, Hope. So, what kind of organizations use databases? And, who within these organizations uses databases the most?

Hope: Almost every enterprise uses databases. Enterprises use databases for a variety of reasons and in a variety of ways. Data and databases are part of almost any process of the enterprise. Data is being collected to help solve business needs and drive value.

Many people in an organization work with databases. These include the application developers who create applications that support and drive the business. The database administrator or DBA maintains and updates the database. And the end user uses the data as needed.

07:19

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07:57

Nikita: Welcome back. Now that we’ve discussed foundational database concepts, I want to move on to database management systems. Take us through what a database management system is, Hope.

Hope: A Database Management System, DBMS, has the following elements. The kernel code manages memory and storage for the DBMS. The repository of metadata is called a data dictionary. The query language enables applications to access the data.

Oracle database functions include data definitions, storage, structure, and security. Additional functionality also provides for user access control, backup and recovery, integrity, and communications. There are many different database types and management systems. The most common is the relational database management system.

08:51

Nikita: And how do relational databases store data?

Hope: Essentially and very simplistically, there are key elements of the relational database. Database table containing rows and columns; the data in the table, which is stored a row at a time; and the columns which contain attributes or related information. And then the different tables in a database relate to one another and share a column.

09:17

Lois: Customers usually have a mix of applications and data structures, and ideally, they should be able to implement a data management strategy that effectively uses all of their data in applications, right? How does Oracle approach this?

Hope: Oracle's approach to this enterprise data management strategy and architecture is converged database to all different data types and workloads.

The converged database is a database that has native support for all modern data types and, of course, traditional relational data.

By providing support for all of these data types, a converged database can run all sorts of workloads, from transaction processing to analytics and machine learning to blockchain to support the applications and systems.

Oracle provides a single database engine that supports all data models, process types, and development environments. It also addresses many kinds of workloads against the same data sets. And there's no need to use dozens of specialized databases. Deploying several single-purpose databases would increase costs, complexity, and risk.

10:25

Nikita: In the final part of our conversation today, I want to bring up database development. Hope, how are databases developed?

Hope: Data modeling is the first part of the database development process. Conceptual data modeling is the examination of a business and business data to determine the structure of business information and the rules that govern it. This structure forms the basis for database design. A conceptual model is relatively stable over long periods of time. Physical data modeling, or database building, is concerned with implementation in each technical software and hardware environment. The physical implementation is highly dependent on the current state of technology and is subject to change as available technologies rapidly change.

Conceptual model captures the functional and informational needs of a business and is used to identify important entities and their relationships.

A logical model includes the entities and relationships. This is also called an entity relationship model and provides the details of the relationships.

11:34

Lois: I think that’s a good place to wrap up our episode. To know more about the Oracle Database architecture, offerings, and so on, visit mylearn.oracle.com. Thanks for joining us today, Hope.

Nikita: Join us next week for another episode of the Oracle University Podcast. Until then, this is Nikita Abraham…

Lois: And Lois Houston, signing off!

11:55

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