D EVELOPING D ATA M ODELS Joe Meehean 1. B USINESS R EQUIREMENTS Business Narrative How the company works, what do they do Consistency and Simplicity.

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Presentation transcript:

D EVELOPING D ATA M ODELS Joe Meehean 1

B USINESS R EQUIREMENTS Business Narrative How the company works, what do they do Consistency and Simplicity make ERD consistent with narrative make ERD simple Lots of experience required to do right art not science 2

I DENTIFYING E NTITY T YPES Nouns Entity types contain additional describing sentences (usually) properties of a noun are likely attributes Attributes are also nouns without additional descriptive sentences e.g., “Students are assigned IDs and a graduation date; they must declare a major.” 3

P RIMARY K EYS Good primary keys are: Stable never change after assignment addresses are not stable a book’s ISBN are Single purpose attributed used only for identification automatically generated by DBMS SSN is a bad primary key SSN also encodes place where SSN was issued Privacy concern of primary key private key may be printed on documents 4

R ELATIONSHIPS Verbs that connect nouns Cardinality plural nouns indicate a “many” relationship’ words like “collection” or “set” also indicate “many” “optional” or “required” indicate min cardinality “optional” = 0 “required” = 1 min cardinality should default to mandatory e.g., “Students are required to enroll in one course per semester” 5

R ELATIONSHIPS Direct or indirect relationships direct: 2 entities connected by a relationship indirect: 2 entities connected by other entities with relationships in-between Can be difficult to tell how entities are related Entities involved in many relationships can become a hub connects many entities indirectly often important documents e.g., “order”, “registration” 6

R EFINING ERD S Process is iterative involves common behaviors Attribute expansion expand attribute into an entity more detail provided for an attribute replace attribute with an entity and 1-M relationship e.g., JobTitle Split Compound Attributes compound attributes contain multiple kinds of data split into smaller attributes e.g., address => street, city, state, zip 7

R EFINING ERD S Expanding Entity Types divide an entity into two entities and a relationship record finer detail about an entity e.g., JobTitle => JobTitle & HasJobTitle can now record years at job title Transform a weak entity into a strong entity add a primary key Add history history stored by adding another entity primary key constructed by combining primary key from original entity with version # often includes beginning and ending dates e.g., SupplierHistory 8

F INAL S TEPS Documentation not really a final step, should be doing all along problems inconsistency or incompleteness potential future problems design decisions e.g., “a supplier is still a supplier even if they don’t supply anything anymore” Check for common design errors fan trap chasm trap 9

Q UESTIONS ? 10