SIT772 - Textbook - Database Systems - Summaries

DATABASE SYSTEMS

• Part 1 - Database Concepts
• Chapter 1 - Database Systems
• Data consists of raw facts. Information is the result of processing data to reveal its meaning. Accurate, relevant and timely information is the key to good decision making, and good decision making is the key to organizational survival in a global environment.
• Data is usually stored in a database. To implement a database and to manage its contents, you need a database management system (DBMS). The DBMS serves as the intermediary between the user and the database. The database contains the data you have collected and "data about data", known as Metadata.
• Database design defines the database structure. A well-designed database facilitates data management and generates accurate and valuable information. A poorly designed database can lead to poor decision making, and poor decision making can lead to the failure of an organization
• Databases can be classified according to the number of users supported, where the data is located, the type of data stored, the intended data usage, and the degree to which the data is structured.
• Databases evolved from manual and then computerized file systems. Ina file system, data is stored in independent files, each requiring its own data management programs. Although this method of data management is largely outmoded, understanding its characteristics makes database design easier to comprehend.
• Some limitations of file system data management are that it requires extensive programming, system administration can be complex and difficult, making changes to existing structures is difficult, and security features are likely to be inadequate. Also, independent files tend to contain redundant data, leading to problems of structural and data dependence.
• Database Management Systems were developed to address file system's inherent weaknesses. Rather than depositing data in independent files, a DBMS presents the database to the end-user as a single data repository. This arrangement promotes data sharing, thus eliminating the potential problems of islands of information. In addition, the DBMS enforces data integrity, eliminates redundancy and promotes data security.

Diapositiva 2

• Chapter 1 - Database Systems (continued)
• Knowledge of database technologies leads to many career opportunities in the ever-expanding IT industry. There is a variety of specialization within the database arena for a wide range of skills and expertise.

Diapositiva 3

• Part 1 - Chapter 2
• Summaries
• A data model is an abstraction of a complex real-world data environment. Database designers use data models to communicate with programmers and end-users. The basic data-modelling components are entities, attributes, relationships, and constraints. Business Rules are used to identify and define the basic modeling components within a specific real-world environment.
• The Hierarchical and Network Data Models were early models that are no longer used, but some of the concepts are found in current data models.
• The Relational Model is the current database implementation standard. In the Relational Model, the end-user perceives the data as being stored in Tables. Tables are related to each other by means of common values in common attributes. The Entity Relationship (ER) Model (ERM) is a popular graphical tool for Data Modeling that compliments the Relational Model. The ER Model allows database designers to visually present different views of the data - as seen by database designers, programmers, and end-users - and to integrate the data into a common framework.
• The Object-Oriented data Model (OODM) uses objects as the basic modelling structure. Like the relational model's entity, an object is described by its factual content. Unlike an entity, however, the object also includes information about relationships between the facts, as well as relationships with other objects, thus giving its data more meaning.
• The Relational Model has adopte many object-oriented (OO) extensions to become the extended Relational Data Model (ERDM). Object/relational database management systems (O/R DMBS) were devloped to implement the ERDM. At this point, the OODM is largely used in specialized engineering and scientific applications, while the ERDM is primarily geared to business applications.
• Emerging Big Data technologies such as Hadoop, MapReduce, and NoSQL provide distributed, fault-tolerant, and cost-effective support for Big Data organizations. NoSQL databases offer distributed data stores that provide high scalability, availability, and fault tolerance by sacrificing data consistency and shifting the burden of maintaining relationships and data integrity to the program code.

Diapositiva 4

• Data-modeling requirements are a function of different data views (global versus local) and the level of data abstraction. The American National Standards Institute / Standards Planning and Requirements Committee (ANSI/SPARC) describes three levels of data abstraction: External, Conceptual, and Internal. The fourth and lowest level of data abstraction, called the physical level, is concerned exclusively with physical storage methods.

Part 2 - Design Concepts

• Chapter 3 - The Relational Database Model
• Tables are the basic building blocks of a relational database. A grouping of related entities, known as an entity set, is stored in a table. Conceptually speaking, the relational table is composed of intersecting rows (tuples) and columns. Each row represents a single entity, and each column represents the characteristics (attributes) of the entities.
• Keys are central to the use of relational tables. Keys define functional dependencies; that is, other attributes are dependent on the key and can therefore be found if the key value is known. A key can be classified as a superkey, a candidate key, a primary key, a secondary key, or a foreign key.
• Each table row must have a Primary Key. The Primary Key is an attribute or combination of attributes that uniquely identifies all remaining attributes found in any given row. Because a primary key must be unique, no null values are allowed if entity integrity is to be maintained.
• Although tables are independent, they can be linked by common attributes. Thus, the Primary Key of one table can appear as the foreign key in another table to which it is
• linked. Referential Integrity dictates that the foreign Key must contain values that match the primary Key in the Related Table, or must contain NULLS.
• The Relational Models support several Relational Algebra Functions, including SELECT, PROJECT, JOIN, INTERSECT, UNION, DIFFERENCE, PRODUCT and DIVIDE. Understanding these functions give a broader understanding of the data manipulation options.
• A Relational Database performs much of the Data Manipulation work behind the scenes. For example, when you create a database, the RDBMS automatically produces a structure to house a data dictionary for your database. Each time you create a new table within the database, the RDBMS updates the data dictionary, thereby providing the database documentation
• Once you know the basic of Relational Databases, you can concentrate on design. Good design begins by identifying appropriate entities and their attributes and then the relationships among the entities. Those relationships (1:1, 1:M, and M:N) can be represented using ERDs. The use of ERDs allows you to create and evaluate simple logical design. The 1:M relationship is most easily incorporated in good design; just make sure that the primary key of the "1" is include in the table of the "many"