Databases are incredibly prevalent -- they underlie technology used by most people every day if not every hour. Databases reside behind a huge fraction of websites; they're a crucial component of telecommunications systems, banking systems, video games, and just about any other software system or electronic device that maintains some amount of persistent information. In addition to persistence, database systems provide a number of other properties that make them exceptionally useful and convenient: reliability, efficiency, scalability, concurrency control, data abstractions, and high-level query languages.
Databases are so ubiquitous and important that computer science graduates frequently cite their database class as the one most useful to them in their industry or graduate-school careers. The course does not assume prior knowledge of any specific topics, however a solid computer science foundation -- a reasonable amount of programming, as well as knowledge of basic computer science theory -- will make the material more accessible. Also bear in mind that picking and choosing which topics to learn is a great approach, and not all topics require the same level of background.
Read more. This course covers database design and the use of database management systems for applications. It includes extensive coverage of the relational model, relational algebra, and SQL. The course includes database design in UML, and relational design principles based on dependencies and normal forms.
Many additional key database topics from the design and application-building perspective are also covered: indexes, views, transactions, authorization, integrity constraints, triggers, on-line analytical processing OLAP , JSON, and emerging NoSQL systems. Working through the entire course provides comprehensive coverage of the field, but most of the topics are also well-suited for "a la carte" learning. Get personalized course recommendations, track subjects and courses with reminders, and more.
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Found in Databases. Never miss a course! How can the database management system ensure control over data integrity, avoid data redundancy, and secure data, while at the same allowing interactions with different user types? In answering these questions, we will identify and determine the characteristics of databases, their many deployment environments, and the different categories of users that interact with them.
In order to properly create and then manage a database, we need to have a thorough understanding of the data it holds. Because data can be seen from different levels, we will introduce different data models and learn how to apply them in order to describe the structure of the database, thereby providing a "view" of the database for the different types of users introduced in the previous section.
Introduction to Database Systems - Wikibooks, open books for an open world
Databases have existed for centuries: the maintenance of records and data has evolved from engravings to cards to digital storage. The history of databases gives us a view of the evolution of database models and the problems of each model. Each subsequent model was motivated by the limitations of previous models, the availability of new technology, the need to store and retrieve new types of data, or by the need to handle new volumes of data that exceeded the capabilities of current models.
In this unit, we will present the four different models of representing data, discussing the different limits of each. Databases often hold a great amount of data. In order to build a database, we need to understand which entities should hold data and identify the connections that may exist between entities. In this unit, we will learn about the Entity-Relationship model, which will allow us to create a graphical view of the different elements of a database as well as the relationships between them.
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We will also learn the drawing conventions of the E-R model using a part-to-whole approach, beginning with those conventions used to represent a single entity, and concluding with conventions used to represent all relations in a database. An E-R model is a model of a database's requirements. If we view database development from the perspective of a software life-cycle model, E-R modeling corresponds to requirements analysis.
Why to Learn DBMS?
In database terms, this is called conceptual modeling. The relational database model provides us with a way to understand how data can be perceived. While the E-R model represents the relations between elements of a database, it does not provide a logical view of its data.
We will use the relational model to solve that problem. The relational model looks at entities as tables and allows operations to be performed on them.
Introduction to Database Systems
In this unit, we will learn how to map ER models into relations. From a life-cycle perspective, the relational model corresponds to high-level design, and adds detail to the conceptual design. The database development evolves from requirements specified in a conceptual model , to high-level database design specified in a logical model , to an implementation model specified in a detailed design and physical model.
An E-R model is a particular modeling method for requirements, while a relational model is a method for database design. We have seen that database entities can be viewed as logical tables. While this is useful in its own way, we can learn more from the data if we can perform operations on the tables within a database, as data from one table may not be meaningful without the data from another table. In this unit, we will introduce relational algebra, the mathematical notation used to represent how data retrievals and updates are performed on tables in a database.
One of the overall themes of computer science is commonality: common components are useful for building many kinds of applications. A database is one of these components, and its usefulness is due to its effectiveness and efficiency in creating, storing, and operating on all types of data. Relational algebra covers basic operations and composing them to form complex queries. Relational algebra is a mathematical system, or model, that formally specifies queries of a relational database, and is implemented as a formal language, SQL.
A query against a database can be expressed as a SQL statement in more than one way, each having the same semantics. Relational algebra enables optimization of SQL queries, and allows you to structure queries in such a way that they execute more efficiently. In this course, we have learned that entities in a database can be thought of as logical tables.
Data in a table must be stored in a normalized way. First, we will identify the properties of a normalized table, learning about the process of normalization and its importance to the structure of a database. We will then study the four major steps of normalization and discuss the database anomalies that can result in the absence of normalization. Data normalization is the process of writing the data so that data redundancy is reduced and data integrity is increased.
Learning Outcomes Upon successful completion of this subject, students should: be able to apply database theory to the design and implementation of relational databases; be able to analyse and model business database requirements using Entity Relationship Diagrams ERD ; be able to analyse a database design and apply normalisation theory and techniques; be able to implement a database design using Structured Query Language SQL ; be able to query a database using SQL.
Syllabus This subject will cover the following topics: Definition of a database, database management systems and their importance to business organizations. The importance and use of data models to design databases to meet business requirements.
Identifying and documenting business rules.