1. Databases

2. Terms & Concepts Field Record File / Table Database Entity Attribute
Key Field / Primary Key
Candidate Key
Composite Key
Foreign Key

3. Traditional File Processing

4. Flat File Example – (Hospital)
Radiology Department
Patno
Fname
Lname
Street
City
Service
Servchrg
1111
Jane
Smith
Main
Cape
X-ray
$125.00
Pathology Department
Patno
Fname
Lname
Street
City
Service
Servchrg
1111
Jane
Smith
Main
Cape
Blood
$15.00

5. Traditional File Environment Problems
Data redundancy
Data inconsistency
Program-data dependence
Lack of flexibility
Poor security
Lack of data sharing and availability

6. Advantages of the Database Approach
Program-data independence
Minimal data redundancy
Improved data consistency
Improved data sharing
Increased productivity of application development

7. Advantages of the Database Approach (cont’d)
Enforcement of standards
Improved data quality
Improved data accessibility
Reduced program maintenance

8. Database Exercise
Create the following five tables using the fields listed below. Underline the Key field(s) for each table.
Tables: Students Courses Zip_codes Student_addresses Instructors
Fields: StudentID (2), Instructor_ID, City, Student_firstname, Zipcode (2), State, CourseID, Course_num, Instructor_firstname, Course_section, Address_ type, Student_lastname, Street, DOB, Entry_date, Instructor_lastname, Instructor_phone, Course_description, course_hours

9. Database Exercise Students
StudentID, St_FirstName, St_LastName, DOB, Entry_Date
Courses
CourseID, CourseNum, CourseSection, CourseDescription, CourseHours
Zip_codes
ZipCode, City, State
Student_addresses
StudentID, Street, ZipCode, AddressType
Instructors
InstructorID, Instructor_FirstName, Instructor_LastName, Instructor_Phone

10. Flat File Example – Student Db
StuID
Fname
Lname
Street
City
State
ZipCd
Sem
1111
Jane
Smith
Main
Cape MO
63701
Spring
North
Anna IL
62980
Railrd
Sike
63755
Continued
Year
CID
Course
Sec
Desc
Hrs
Prof
Phone
2009
0413
MI375 01
MIS 3
Schw
7387

11. Relational File Example
DrID
Fname
Lname
DS1
Dana
Schwie
JR3
James
Ricks
Student Database
SID
Fname
Lname
1111
Jane
Smith
SID
CID
EID
1111
2345
DS1
3687
JR3
Schedule
Students
SID
Street
Zip
Phone
Addtype
1111
Main
63701
2100
home
Student_Address
CID
CrsNum
Sec
Desc
Hrs
0375
MI375 03
MIS 3
0301
MK304 01
MKTG
Course

12. Creating a Database
Designing
Data need to be organized for retrieval and analysis
Key elements of a database
Data
Normalization
Repeating groups
Structure
Data model
A map or a diagram representing entities and their relationships
Entity-Relationship (ER) Diagram
Distributing
Client / server networks
Partitioned database
Duplicate database
DISTRIBUTED DATABASE: Data Physically Stored in more than one Location
Partitioned – (only local files) Central db can be partitioned so that each remote processor has the necessary data to serve its local area. Changes in local files can be justified with central db on a batch basis often at night.
Duplicate – (All) Replicate db at all remote locations. Ex. Lufthansa’s DBMS.
Distributed systems reduce the vulnerability of a single, massive central site. However, dependent on high-quality telecommunications lines. Sometimes local dbs depart from central data standards and definitions. They may pose security problems.

13. Effective Management of Databases
Database Administrator (DBA)
Responsible for development and management of databases
Works with system analysts and programmers
Works with users and managers
Implements security features
Grants access rights
One of the key actors in creating a successful database

14. Entering Data Forms Enter data about a record
Field in a form corresponds to attribute in a record
Used to add, modify, or delete data

15. Querying Data Query: Used to retrieve information
Structured Query Language (SQL)
Example: Display students who earned an “A”
Writing SQL queries can become very complex

16. Query by Example Simpler than SQL Drag-and- drop features
Construct a sample of the data we would like to see

17. Creating Database Reports
Compilation of data from the database
Report generators
Retrieve, manipulate, and display data
Example
Quarterly sales for a restaurant
Adding
Grouping

18. Operational vs. Informational Systems

19. Data Warehouses and Data Marts
Integration of multiple large databases and other information sources into a single repository
Pull together, integrate, and share critical corporate data throughout the firm
Data Mart
Data warehouse that is limited in scope
Customized for the decision support applications of a particular end-user group

20. Associations Used to relate information between tables
Needed to retrieve information
Example: Basketball league database