DATA MODELING
Data Modelling
1, data modelling is a technique for organizing and documenting a systems data in a model.
2. ERD depicts data in term of the entities and relationships described by the data.
3, Relational Data Model is a blueprint for implementation of a conceptual data model ( ERD) in relational database enviroment( software indepenndent)
4, MS Acess Relationship Window: a graph showing how a data model is implemented with Microsoft Acces
ERD
- is used to model data and their relationship
- is a graphical representation of a conceptual data model
- is resource independent: it does not comit to any particular database environment.
ENTITY
- is a group of attributes corresponding to the same conceptual object about which we need to capture and store data.
- is a set of occurrences(instances) of the object that it represents
- must have a unique name ( a singular noun) unique identifier, and at least one attribute ( the identifier itself)
ATTRIBUTES
- is a descritptive property or characteristic of interest of an entiy. Also called element, property and field
- DATA TYPE for an attribute defines what type of data can be sorted in that attribute
- DOMAIN of an attribute defines what values an attribute can legitimately take on.
- DEFAULT VALUE for an attributes is the value that will be recorded if not specified by the user.
IDENTIFICATION
- a KEY is an attribute, or a group of attributes that assume a UNIQUE VALUE for each entity instance
- a group of attributes that uniquely identifies an instance of a entity is called a COMPOSITE KEY
- a PRIMARY KEY ( identifier) is that candidate key that will most commonly be used to uniquely identify a single entity instance( StudentID)
- Any candidate key that's not selected to become the primary key is called an alternative key. ( SSN, DriverLicenseNo)
- a SECONDARY KEY is an attribute whose values divide all entity instances into usefull subgroup/ sub-criteria ( Major, Gender..)
RELATIONSHIPS
- a relationship documents an asscociation between one, two, or more entites
- must have a name( and many carry data)
- Degree of relationshiip ( number of entities)
- Cardinalities of relationship ( number of instances / members)
DEGREE OF RELATIONSHIp defines how many entiies are involved in a relationship.
exmalple: Recursive ( unary), Binary, ternary
CARDINALITIES
- document how many occurrences/member of one entity can relate to a single occurrence/ member of another entity in a relationship
- Max / MIx number of occurrences
- Reflect business policies or general business practices ( how many classes a student can take, how many students a class can hold)
LOGICAL DATA MODELLING STAGES
1. Context Data Model
- To establish project scope
2. Key-base data model
- Eliminate nonspecific relationships
- Add associative entities
- Include primary and alternate keys
- Precise cardinalities
3. Fully attributed data model
- All remaining attributes
- Subsetting criteria
4. Normalized data model
GOOD DATA MODEL
- Simple
Data attributes that describe any entity should describe only that entity.
Each attribute of an entity instances can have only one value.
- Non redundant:
Each data attribute, other than foreign keys, describes at most one entity
Look for the same attributes recorded more than once under different names.
- Flexible and adaptable
Rules In ERD BUIDING
- Each entitly must have a name
- Each entity must have an identifier
- An occurrence itself cannot be an entity
- Each relationship must have a name
- Reasonable cardinalities ( context specific)
ASSOCIATIVE ENTITY
- is an entity that inherits its primary key from more than one other entity ( called parents)
- each part of composite key points to one and only one instance of each of the connecting entities
FOREIGN KEYS IN RELATIONAL DATABASE
- a foreign key in entity is a primary key of another entity, which is used to identify a one-to-many relationship between two other entities. \
- In M:N relationship, the associative /junction table with a composite key will be used to capture the relationship.
- Each part of the composite key serves like a foreign key
- sometimes, a surrogate key ( RecordNo) is used as primary key to simplify the identification of record.
DATA ANYALYSIS NORMALIZATION
- data analysis is a process that prepares a data model for implementation as a simple, non-redundant, flexible, and adaptable database.
- is technique to organize data attributes such that they are grouped to form non redundant, stable, flexible, and adaptive entities.
1NF:
- No repeating group of same attribute ( multi valued attributed)
2NF
- Attributes should depen on the whole ( composite) key, not part of it( partial functional dependency)
3NF:
- Attributes should depend on the primary key only, not on each other.( transitive dependency)
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