1. ISQS 6339, Business Intelligence Database vs. Data Warehouse
Zhangxi Lin
Texas Tech University 1 1

2. Agenda Install Parallels (instructions)
Test SQL Server 2016 on Parallels
Access the shared network drive
For MacBook:
For Windows: Map to \\Techshare\coba\d\isqs3358
Create a database using WPC scripts
\\Techshare\coba\d\isqs3358\isqs3348\Exercises\D BC-e07-WPC-Scripts
Convert WPC database to data warehouse

3. Database Review
ISQS6339

4. Purpose of a Database
The purpose of a database is to keep track of things.
Unlike a list or spreadsheet, a database may store information that is more complicated than a simple list.
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

5. Components of a Database System
Figure 1-15: Components of a Database System
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

6. Relational Databases
A relational database stores information in tables. Each informational topic is stored in its own table.
In essence, a relational database will break-up a list into several parts—one part for each theme in the list.
A Project List would be divided into a CUSTOMER Table, a PROJECT Table, and a PROJECT_MANAGER Table.
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

7. Example Database Metadata: A Relationship Diagram
Figure 1:16 Example Metadata: A Relationship Diagram
for the Art Course Tables in Figure 1-10
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

8. Normalization Process
Identify all the candidate keys of the relation
Identify all the functional dependencies in the relation
Examine the determinants of the functional dependencies. If any determinant is not a candidate key, the relation is not well formed.
Place the columns of the functional dependency in a new relation of their own
Make the determinant of the functional dependency the primary key of the new relation.
Leave a copy of the determinant as a foreign key in the original relation.
Create a referential integrity constraint between the original relation and the new relation.
Repeat Step 3 as many times as necessary until every determinant of every relation is a candidate key
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Educations, Inc. Publishing as Prentice Hall

9. Normal Forms There are many defined normal forms:
First Normal Form (1NF)
Second Normal Form (2NF)
Third Normal Form (3NF)
Boyce-Codd Normal Form (BCNF)
Fourth Normal Form (4NF)
Fifth Normal Form (5NF)
Domain/Key Normal Form (DK/NF)
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

10. This is Boyce-Codd Normal Form (BCNF)
Normalization to BCNF
For our purposes, a relation is considered normalized when:
Every determinant is a candidate key.
This is Boyce-Codd Normal Form (BCNF)
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

11. Normalization Example
(StudentID)
(StudentName, DormName, DormCost)
However, if…
(DormName)
(DormCost)
Then DormCost should be placed into its own relation,
resulting in the relations:
(StudentName,
DormName)
(StudentID)
(DormName)
(DormCost)
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Educations, Inc. Publishing as Prentice Hall

12. Normalization Example (Cont’d)
(AttorneyID,ClientID)
(ClientName, MeetingDate, Duration)
However, if…
(ClientID)
(ClientName)
Then ClientName should be placed into its own relation,
resulting in the relations:
(AttorneyID,ClientID)
(MeetingDate, Duration)
(ClientName)
(ClientID)
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Educations, Inc. Publishing as Prentice Hall

13. Levels of Entity Attribute Display
Figure 4-3: Levels of Entity Attribute Display
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

14. Relationships
Entities can be associated with one another in relationships.
Relationship degree defines the number of entity classes participating in the relationship:
Degree 2 is a binary relationship.
Degree 3 is a ternary relationship.
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

15. Crow’s Foot Symbols Figure 4-8: Crow’s Foot Notation
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

16. Crow’s Foot Example: One-to-Many Relationship
Figure 4-7: Two Versions of a 1:N Relationship
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

17. Heather Sweeney Designs: Final Data Model
(c) The Finished Data Model
Figure 4-21: The Final Data Model for Heather Sweeney Designs
KROENKE and AUER - DATABASE CONCEPTS (7th Edition) Copyright © 2015 Pearson Education, Inc. Publishing as Prentice Hall

18. Database case
Find the SQL scripts in \\Techshare\coba\d\isqs3358\isqs3348\Exercises\
Use the scripts in \DBC-e07-WPC Script\
Download file for the exercises

19. Wedgewood Pacific Corporation

20. Wedgewood Pacific Corporation

21. Incapability of database
How could I analyze the performance between departments regarding workload and employee numbers?
How could I do online prediction of future projects trend according to current projects?
If the database contains 100 million records how could the response time become acceptable?

22. Data warehousing

23. Data Mart Planning Fact table – collections of measures
Measures: MaxHours, HoursWorked
Dimension tables
Time: StartDate, EndDate
Project
Employee
Department

24. Dimensional Model DIM_PROJECT ---------------------- DIM_DEPSRTMENT
ProjectID
ProjectName
Department
MaxHours
StartDate
EndDate ……
DIM_DEPSRTMENT
DepartmentName
BudgetCode
OfficeNumber
Phone
PROJ_ASSIGN
EmployeeNumber
ProjectID
HoursWorked
StartDate
EndDate
DIM_EMPLOYEE
EmployeeNumber
FirstName
LastName
Department
Phone
DIM_TIME
Year
Quarter
Month
Week
Date

25. Data Mart Design Fact Table Dimension Tables
PROJ_ASSIGN (ProjectID, EmployeeNumber, HoursWorked, StartDate, EndDate)
Dimension Tables
TIME(Year-Quarter-Month-Date)
PROJECT(ProjectID, ProjectName, Department, MaxHours)
DEPARTMENT(DepartmentName, BudgetCode, OfficeNumber, Phone)
EMPLOYEE(EmployeeNumber, FirstName, LastName, Department, Phone, )

26. Data Mart Design – Scheme 2
Fact Table
PROJect (ProjectID, ProjectName, Department, MaxHours, StartDate, EndDate)
Dimension Tables
TIME(Year-Quarter-Month-Date)
DEPARTMENT(DepartmentName, BudgetCode, OfficeNumber, Phone)
This is a simplified model from the previous