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Relational Database Design Glossary

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Codd's Relational Model

The relational database model was conceived by E. F. Codd in 1969, then a researcher at IBM. The model is based on branches of mathematics called

set theory and
predicate logic.

The basic idea behind the relational model is that a database consists of a series of unordered tables (or relations) that can be manipulated using non-procedural operations that return tables. This model was in vast contrast to the more traditional database theories of the time that were much more complicated, less flexible and dependent on the physical storage methods of the data.
Note: It is commonly thought that the word relational in the relational model comes from the fact that you relate together tables in a relational database. Although this is a convenient way to think of the term, it is not accurate. Instead, the word relational has its roots in the terminology that Codd used to define the relational model. The table in Codd's writings was actually referred to as a relation (a related set of information). In fact, Codd uses the terms relations, attributes and tuples where most of us use the more common terms tables, columns and rows, respectively (or the more physical and thus less preferable for discussions of database design theory files, fields and records). The relational model can be applied to both databases and database management systems (DBMS) themselves.
The relational trustworthiness of database programs can be analyzed using Codd's 12 rules. Since Codd's paper on the relational model, the number of rules has been expanded to 300 for determining how DBMS products conform to the relational model. When compared with other database management programs, Microsoft Access fares quite well in terms of relational trustworthiness. Still, it has a long way to go before it meets all twelve rules completely

Why an understanding of Database Design is important

Database Design Glossary Terms

attribute: A characteristic of an entity; data that identifies or describes an entity. Usually represented as a column in a table, attributes store data values.
base table: A table stored in a database.
BLOB domain type: Short for “binary large object”; a domain type used to store binary objects such as graphics in a relational database.
Boolean expression: An expression that results in a value of either TRUE or FALSE. Boolean expressions are also called comparison expressions, conditional expressions, and relational expressions.
business objects: Items in a business environment that are related, and about which data need to be stored (e.g., customers, products, orders, etc.).
Business rules: A set of rules or conditions describing the business polices that apply to the data stored on a company databases.
CASE tools: Short for computer-aided software-engineering tools, CASE tools are software packages used to design and implement information systems.
Chen model: One of several types of entity-relationship (ER) diagrams. The Chen model is named after the inventor of ER diagramming.
Collation: A database's collation refers to the types of language characters the database will support. If you do not specify a collation, the MySQL default collation will bge used.
composite entity: In relational database design, a composite entity is used to provide an indirect link between two entities in a M:N (many-to-many) relationship. Also called a linking table.
composite key attribute: A key attribute belonging to a composite entity, comprising the key attributes from each of the two entities linked by the composite entity. Also called a composite primary key.
composite primary key: Another name for a composite key attribute.
conceptual model: A description of the structure of a database.
constraints: Rules a database designer imposes upon certain elements in a database to preserve data integrity.
Crowsfoot model: One of several types of entity-relationship (ER) diagrams, the Crowsfoot model neatly packages entities with their attributes by placing them in boxes. Also referred to as the Information Engineering model.
CRUD: CRUD: CRUD stands for the four fundamental database operations that any database should provide: Create, Read, Update, and Delete. If you read database articles and discussions on the Web, you will often see people usingthe term CRUD.
data: The "raw facts" stored in a database.
data definition language (DDL): A collection of programming statements that describe and define data and data relationships in a database.
data flow diagram: A diagram illustrating the flow of data in an organization, including data sources, data storage, and data transformation processes.
data integrity: A term used to describe the quality (in terms of accuracy, consistency, and validity) of data in a database, in the sense that values required to enforce data relationships actually exist. Problems with data integrity occur when a valuein one table that’s supposed to relate to a value in another can’t, because the second value either has been deleted or was never entered.
data manipulation language (DML): A collection of programming statements used to manipulate a database.
data modeling: The process of creating a data model, which is a conceptual representation of the data structures that are required by a database.
data redundancy: Duplication of data in a database.
data value: Data entered at the intersection of a row (record) and column (field); the data describes or identifies the subject of the record.
database model: A formal structure for organizing and linking data in a database.
domain: Determines the type of data values that are permitted for that attribute.
domain constraints: Rules that require values of attributes to come from specific domains (e.g., text, numbers, date, etc.).
entity: A single stand-alone unit or a business object about which data are stored in a database; usually synonymous with a database table.
entity identifier: A key attribute that uniquely identifies each entity.
entity relationship: Entities that participate in a relationship are associated; the three types of entity relationships (associations) are 1) one-to-one, 2) one-to-many, and 3) many-to-many.
entity-relationship Model: An entity-relationship diagram is another form of object model that in many ways is similar to a semantic object model. It also allows you to represent objects and their relationships, although it uses different symbols.
(ER) entity-relationship diagram: A diagram used during the design phase of database development to illustrate the organization of and relationships between data during database design.
field: The smallest structure in a table; contains data describing the subject of a table.
foreign key: A field (or combination of fields) used to link tables; a corresponding primary key field occurs in the same database.
hierarchical model: A database model that organizes data in a top-down (inverted tree) structure.
IDEF1X model: One of several types of entity-relationship (ER) diagrams. .Information Engineering (Crowsfoot) model - One of several types of entity-relationship (ER) diagrams; usually referred to as the "Crowsfoot" model.
index: In the context of a relational database, an index is a structure that allows you to quickly find records in a table based on the contents of the specific table columns that have been indexed. An index on employee last name and first name fields, for example, would allow you to retrieve an employee record by name. Indexes are an essential part of getting reasonable performance out of any relational database.
information: A collection of "raw facts" (data) organized in such a way that they have value beyond the value of the facts themselves.
information system: Interrelated components (e.g., people, hardware, software, databases, telecommunications, policies, and procedures) that input, process, output, and store data to provide an organization with useful information.
instance of entity: The equivalent of a row (record) in a database with values entered for the entity's attributes.
instance entity: A group of attributes that identify and describe one occurrence of an entity; the equivalent of a record in a table.
key attribute: An attribute that identifies an entity or an entity identifier.
legacy database: Any type of database that has been in use by an organization for several years.
linking table: Another name for a composite entity. Used to provide an indirect link between two entities in a M:N (many-to-many) relationship.
logical design: The second stage in the DBLC: creating a logical schema, followed by data normalization.
logical schema: The overall logical plan of a database; typically a completed ER diagram.
mandatory entity: In the language of relational database design, mandatory entity is another name for the entity that has mandatory participation in an entity relationship.
mandatory participation: In the language of database design, participation describes the nature of the relationship between two tables. Mandatory participation describes a relationship in which least one record in a table must exist before any records can be added to its associated table.
many-to-many relationship: In relational database design, a many-to-many (M:N) relationship exists when, for one instance of entity A, there exists zero, one, or many instances of entity B; and for one instance of entity B, there exists zero, one, or many instances of entity A.
multi-valued attribute: An attribute with more than one data value; must be resolved into a single-valued attribute.
network model: An extension of the hierarchical model. (See hierarchical model.)
non-duplication: The degree to which there is a one-to-one correlation between records and the real-world object or events being represented.
non-key attribute: An attribute that describes an entity.
normalization: The process of applying increasingly stringent rules to a relational database to correct any problems associated with poor design.
Object-oriented design: A design that allows you to not only define what data you can store in your database, you also define a set of actions (methods) associated with the data..
object-oriented model: Object/relational database management systems (ORDBMSs) add new object storage capabilities to the relational systems at the core of modern information systems. By encapsulating methods with data structures, an ORDBMS server can execute complete analytical and data manipulation operations to search and transform multimedia and other complex objects.
one-to-many relationship: In relational database design, a one-to-many (1:N) relationship exists when, for one instance of entity A, there exists zero, one, or many instances of entity B; but for one instance of entity B, there exists zero or one instance of entity A.
one-to-one relationship: In relational database design, a one-to-one (1:1) relationship exists when zero or one instance of entity A can be associated with zero or one instance of entity B, and zero or one instance of entity B can be associated with zero or one instance of entity A.
optional participation: In the language of database design, participation refers to the nature of the relationship between tables. Optional participation describes a relationship in which no records need to exist in a table before records are added to its associated table.
paper-based database: Typically a filing system where data is stored on a variety of paper forms.
physical design: The third stage in the DBLC: tweaking data design elements to optimize database performance.
physical schema: The underlying physical storage of data in a database, managed by the RDBMS.
primary key: A field (or combination of fields) that uniquely identifies a record in a table.
query: (v.) To extract data from a database; (n.) a set of SQL statements for extracting particular data from a database.
record: A particular instance of the subject of a table.
redundant data: Duplicate data in a database; although redundant data can never be totally removed, a major goal of database design is to eliminate as much redundant data as possible.
relational database: A relational database management system (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by Edgar F. Codd.
Relational database: A database built on the relational model, which organizes data into tables comprising columns and rows.
Relational Database Management System (RDBMS): A software package that manages and provides access to a database. These packages follow Codd’s 12 rules of relational databases and normally use SQL to access data.
relational model: A formal structure that organizes data into relations (i.e., tables).
requirements analysis: The stage in the database design cycle when designers find out everything they can about the data the client needs to store in the database and the conditions under which that data needs to be accessed.
schema: The description of a database is called the database schema, which is specified during database design and is not expected to change frequently. Most data models use certain conventions for displaying their schema as diagrams.
single-valued attribute: An attribute with more than one data value; must be resolved into a single-valued attribute.
SQL: SQL is an acronym for Structured Query Language. It provides a set of commands that can be used to add data to a database, retrieve that data, and update it. SQL, often pronounced “sequel”, is universally supported by relational database vendors.
Surrogate Key: For mapping a category whose defining superclasses have different keys, it is customary to specify a new key attribute, called a surrogate key, when creating a relation to correspond to the category. The keys of the defining classes are different, so we cannot use any one of them exclusively to identify all entities in the category.
system administrator: The person responsible for administering a multi-user computer system; duties range from setting up and configuring system components (e.g., an RDBMS) to performing maintenance procedures (e.g., database backups) on the system.
table: A collection of data arranged in rows and columns. A table is the largest structure in a relational database.
user view: Specifies which users are permitted access to what data in a database.
user views: Saved queries created with SQL. User views specify which users are permitted access to what data in a database.
vertical integration: The practice of an existing firm replacing one or more of its supplier markets with its own hierarchial structure for creating the supplied product.
virtual table: A table stored in the computer’s memory. Virtual tables themselves are not stored in the database; rather, the definition of the view is stored and given a name. Users call up that name, and the view is created (from base tables) on the fly. When a user closes the view, it "disappears" from memory, only to be recreated the next time itsname is invoked.
weak entity: In the language of relational database design, weak entity is another name for the entity that has optional participation in an entity relationship.
Yourdon/DeMarco: A popular style of data-flow diagram. It includes symbols that illustrate who handles the data in a database, where the data moves, where the data are stored, and what is done to the data.