1. MIS 301 Information Systems in Organizations Dave Salisbury salisbury@udayton.edusalisbury@udayton.edu (email) http://www.davesalisbury.com/http://www.davesalisbury.com/ (web site)

2. Databases & Data Modeling Data as a resource Samples of how databases are set up in organizations Basic logical modeling of data Basic physical modeling of data Data Integrity Normalization

3. Logical Data Elements Employee Record 2 Employee Record 1 Employee Record 3 Employee Record 4 NameSSSalaryNameSSSalaryNameSSSalaryNameSSSalary Data Personnel Database Payroll File Benefits File

4. Physical Data Access (Primary) key fields Unique identifier for a record Sequential Access (Tape) Stored in order by key field Can only be retrieved/stored in that order Direct Access (Disk) Hashed File Organization Key transformed into physical address using algorithm Indexed Sequential Access Method (ISAM) Direct access using indexes Sequential when doing batch runs

5. Disadvantages of File Processing Program-Data Dependence All programs maintain metadata for each file they use Data Redundancy (Duplication of data) Different systems/programs have separate copies of the same data Limited Data Sharing No centralized control of data Excessive Program Maintenance 80% of of information systems budget

6. Duplicate (Redundant) Data

7. Problems with Data Redundancy Waste of space to have duplicate data Causes more maintenance headaches The biggest Problem: When data changes in one file, could cause inconsistencies Compromises data integrity Lack of coordination and central control Non-standard file formats

8. Database Central repository of shared data Data is managed by a controlling agent Stored in a standardized, convenient form Requires a database management system (DBMS)

9. Advantages of Database Approach Program-Data Independence Metadata stored in DBMS, so applications don’t need to worry about data formats Minimal Data Redundancy Leads to increased data integrity/consistency Improved Data Sharing Different users get different views of the data Enforcement of Standards All data access is done in the same way Improved Data Quality Constraints, data validation rules

10. Modeling Reality A database must mirror the real world if it is to answer questions about the real world Data Modeling is a design technique for capturing reality STUDENT Social_Security_No Name Major

11. Entity-Relationship Modeling One type of data modeling Represents data in terms of: Entities Relationships

12. Entity-Relationship Modeling Entity-something (real or abstract) that can be identified in a user’s work environment that can be distinguished from other things. Entity Class-(i.e. CUSTOMER) Entity Instance-(e.g. FRED FLINSTONE)

13. Entity-Relationship Modeling Attributes (a.k.a. properties). Describe the characteristics of entities. EMPLOYEE_NAME EMPLOYMENT_DATE

14. Entity-Relationship Modeling Primary keys - identify instances of entities, a.k.a. key attributes SOCIAL_SECURITY_NUMBER

15. Entity-Relationship Modeling Relationships imply constraints on how many entities may occur on one side (or the other) of a given relationship. Types of Relationships one-to-one 1:1 one-to-many 1:N many-to-many N:M

16. Notation in an ER diagram ENTITY RELATIONSHIP Attribute – Something you want to store about an entity. Primary Key – Uniquely identifies an entity (e.g. SID). Something about which you want to keep data. How things you want to keep data about are tied together.

17. Entity-Relationship Modeling Customer Order Product Places/ Placed by Contains/ is Contained in

18. Relational Databases Relations (a.k.a. tables) Each row is unique (entity instance) Order is unimportant Each column represents one thing (attribute) Entries are from the same domain (e.g. student)

19. Relational Databases Keys Primary key (uniquely identifies a record) Composite key, a.k.a. Concatenated key (two elements combined are unique) Foreign key (links tables/relations)

20. Data Integrity Rules to make sure your data is valid Entity integrity constraint Primary key cannot be null Referential integrity Ensures valid relationships between data Cannot add a row with no parent Cannot delete a parent without deleting child (cascading) Domain Integrity

21. Data Interrelationships Dependencies and determinants Anomalies Insertion Deletion Update

22. Normalization First normal form No repeating groups Second normal form No partial dependencies Third normal form No transitive dependencies

23. M:N Relationships in Relational Model Customer Order Order Line Places/ Placed by Contains/ is Contained in Product Contains/ is Contained in

24. How this looks in Access CustomerID FirstName LastName Address City State Zip Telephone OrderID OrderDate CustomerID OrderID ProductID Quantity ProductID Description Price Weight Supplier CUSTOMER ORDER ORDER LINE PRODUCT 1 8 1 8 1 8