Entities and Attributes
Revision as of 00:42, 12 September 2017 by Bacchas (talk | contribs) (→ERD Entity relationship diagram)
Entity Defined
Something of significance to the business about which data must be known
A name for a set of similar things that you can list
Usually a noun
Examples: object, events, people
Entities have instances
An instance is a single occurrence of an entity
- A Dalmatian, a Siamiese cat, a Cow are instances of ANIMAL
- A convertible, a sedan, a Station wagon are instances of CAR
- Some entities have many instances and some have only a few
- Entities can be:
- Tangible, like PERSON, or PRODUCT
- Intangible, like SKILL LEVEL
- An Event, like CONCERT
WHAT IS AND ATTRIBUTE
- An attribute represents something of significance to the business
- An attribute is a specific piece of information that helps:
- Describe an Entity
- Quantify an Entity
- Qualify an Entity
- Classify an Entity
- Specify an Entity
- An attribute has a single value
Relationship
- Association between 2 or more entities
- Conceptual model
- A data model, usually represented by an entity relationship diagram (ERD)
- The client dream would be the conceptual model
- Physical model
- A design for an object (a car, a house, a database, etc) which includes implementation details such as size, volume, weight, etc)
- The physical reality will become the physical model
- All many-to-many relationships must be reduced to a set of on-t--many relationships
ERD Entity relationship diagram
- An entity relationship diagram (ERD) is a consistent tool that can be used to represent the data requirements of a business regardless of type of database that is used, and even in the absence of one
Implementation-Free Models
A good conceptual data model stays the same regardless of the type of database the system is eventually built or implanted on, This is what is meant by saying the model is implementation-free
- The data model should stay the same even if a database is not used at all
What is an Entity Relationship Model
A list of entities and attributes as well as all relationships between the entities that are of importance
Provided background information such as entity descriptions, data types, and constraints
NOTE: The model does not require a diagram, but the diagram is typically a very useful tool
Goals of ER Modeling
- Capture all required information
- Ensure that information appears only once
- Model no information that is derivable from other information already modeled
- Locate information in a predictable, logical place
Database Normalization
Storing data in a normalized format means only one update is required to reflect the new address, and it should always be the one that appears whenever your mailing address is needed.
Many people unfamiliar with database design principles often ask, “Why not just put all the data in one big table?” This single-table approach leads to problems of data redundancy (duplication) and data anomalies (data inconsistencies).
To avoid these data issues, database normalization is used to create a design that reduces or eliminates data redundancy and, therefore, avoids data anomalies. In general, normalization helps database designers determine which attributes, or fields, belong to each entity. In turn, this information helps determine which fields belong in each table. Normalization is a multistage process that enables designers to take the raw data to be collected about an entity and develop the data into a structured, normalized form that reduces the risks associated with data redundancy. Data redundancy poses a special problem in databases because storing the same data in different places can cause problems when updates or changes to data are required.
When a record contains repeating groups (that is, multiple entries for a single column), it’s considered unnormalized. First-normal form (1NF) indicates that all values of the columns are atomic—meaning they contain no repeating values. To convert records to 1NF, remove the repeating values by making each author entry a separate record,
When more than one field is used as the primary key for a table, the combination of fields is usually referred to as a composite primary key
Now that the repeating values have been eliminated and the records can be identified uniquely, the data is in 1NF
A problem known as partial dependency can occur when the primary key consists of more than one field. Partial dependency means the fields contained in a record (row) depend on only one portion of the primary key
By removing Partial dependency your table is now second-normal-form (2NF)
A transitive dependency means at least one value in the record isn’t dependent on the primary key but on another field in the record. In this case, the contact person from the publisher’s office is actually dependent on the publisher, not on the book.
Levels of Normalization
1NF: Eliminate all repeating values and identify a primary key or primary composite key.
2NF: Make certain the table is in 1NF and eliminate any partial dependencies.
3NF: Make certain the table is in 2NF and remove any transitive dependencies.
A many-to-many relationship can’t exist in a relational database. The most common approach to eliminating a many-to-many relationship is to create two one-to-many relationships by adding a bridging entity. A bridging entity is placed between the original entities and serves as a “filter” for the data.
SQL Command Types
- Query
- SELECT(Retrieve the data values)
- Data manipulation language (DML)
- INSERT, UPDATE, DELETE (Create or modify data values)
- Data definition language (DDL)
- CREATE, ALTER, DROP (define data structures)
- Transaction control (TC)
- COMMIT, ROLLBACK (Save or undo data value modifications)
- Data control language(DCL)
- GRANT, REVOKE (Set permissions to access database structures)