Database model
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1) A data model abstracts the essential qualities of a dataset and describes the data in an organization. It involves determining user and application data requirements and integrating them into an overall conceptual view. 2) Conceptual and physical data models are created. The conceptual model specifies data for human understanding while the physical model aids database design. 3) Data modeling defines entities, attributes, relationships and identifies primary keys. It also establishes constraints and referential integrity rules for the data.
Database model
- 3. A data model is a model describing the data in an organization Abstraction tool Abstracts essential qualities of a dataset Data modeling is the process of abstraction and documentation using a data model
- 4. Determination of the data requirements (views) of individual users & applications For e.g. Project building process /customer requirements specs
- 5. Integration of the individual user (customer) & application (s/w) views into an overall conceptual views. Customer reviews – Conflict resolution. 2 types: Unconstrained/Natural Conceptual Design Constrained/Conceptual Design
- 6. The internal structure of the database Translating the Conceptual Design(previous steps) into physical structures; basically stacks, queues etc…
- 7. Data abstraction creates hierarchies of abstractions along 2 dimensions Aggregation Generalization Aggregation Identifies a data items as a part of a higher level, more aggregate descriptor e.g. Project -> Project -> Assignment
- 8. Generalization It creates categories into which a data item may be classified e.g. Employee can be categorized into age Type of job Type of pay plan, etc…
- 9. Conceptual Model: designed to promote user understandable Specifications of data. Physical Model designed to aid in physical database design. Info logical for human understanding and requirements level. Data logical deals with physical and database implementation. Some models can contain elements of both models.
- 10. Terms used in Data definition Entity: Any type of "thing" about which info. Is being maintained. Attribute: A characteristic of an entity. Instance: instance of an entity or relationship. Relationship: Association between entities. Identifiers: Set of attributes which uniquely identify an instance of an entity or relationship.
- 11. EMPLOYEE is an entity A person who works for the company is an instance of EMPLOYEE. His/her age is an attribute of the entity type. Employee OF company, here "of" is a relationship. Employee Id is an identifier.
- 12. Three types amongst activities recorded during conceptual data modeling. has adverse effects on the physical database design Basically 1:1 1:M M:N
- 13. Instance of an entity has a given relationship with only one instance of a 2nd entity. PROCESSOR ENDOWED CHAIR H HELD BY
- 14. An entity has relationships with many instances of another entity. University -> many students Students -> one university. UNIVERSITYS1 S2 S3 S4 S5S1 S3S2 S4 S5
- 15. An entity has relationships with many instances of another entity and vice-versa. STUDENT CLASS REGISTERED
- 16. Defines conditions that must be met for the data to be complete and correct. Three types: On values On dependencies On referential integrity • Values: allowable, valid values for attribute • Dependencies: allowable values for attributes may depend on some other value. • E.g. allowable values for an employee skill classification are a part of allowable skills of the department he/she works in.
- 17. Entities and relationships often have reference conditions that must be met. A sales order; for an order to exist there must be a customer.
- 19. Defines categories of data and their property. A schema is an outline or representation of a plan, a theory, or an assignment. Classification External (User's view) Conceptual (Overall logic) Internal schema or Data storage Defn.
- 20. Also known as user's schema(appl prg/ person formulating a query) is concerned with only a small portion of the database It’s the user view of data being used in the system. Only a very few of the total entities or its attributes are taken into consideration.
- 21. The logical view of the Database The closest view of the real entities and their relationships. Contains integrity rules & authorization rules. But no data about how data is stored in the Database.
- 22. Describes how the database is organized for physical storage and access. Includes information on ordering of records, block sizes, storage indexes, use of pointers and access strategies being used.
- 23. Translations from one schema to another. For user access of data the user view of the data as shown in the external schema must be translated into the overall conceptual schema. This is done by externalconceptual mapping. In the same way conceptualinternal mapping translates logical descriptions of data in the conceptual schema to physical location and access paths in the internal schema.