Introduction to FIS 318/618,Financial Systems & Databases:

The Relational Database Model

Oakland UniversitySchool of Business Administration

Accounting and FinanceJoe Callaghan

The Relational Database Model

• Based on the theory of relational math (set theory)• It is an “automatic transmission” database (with

embedded relationships between tables) which replaces the “standard transmission” database (which employs flat-file techniques with explicit pointers between files and records)

• Flat-files (collections of similar records) are being replaced by collections of interrelated files

• Allows data to be broken down into logical, smaller, more manageable units - simplifies the organization of complex sets of data

Why A Relational Model?• Duplicate data reduced - less input, maintenance, storage,

and improved data integrity• Data independence: Data can be thought of as being stored

in tables regardless of how physically stored.• Application independence: Databases defined

independently from the systems and programs that will use them - allows users to create ad hoc queries, rather than only receive pre-specified reports

• A change in the database does not require rewriting all the application program codes. Ability to share same data across multiple applications and systems.

• It has the ability to maintain several tables of related information that can be accessed by several different users in many different ways - a single query can retrieve data from more than one table.

Some Definitions...Data: Raw facts about the organization and its business

transactions that are of interest to the end user

Database: A computer structure that houses a collection of data

Relational database: Stores information about instances of entities (a specific sales event, salesperson), attributes of those entities (invoice no., salesperson ID) , and the relationships among these entities (each sale can only have one salesperson) - perceived by user to be a collection of two-dimensional tables

RDBMS: Software that manages a relational database, controls access, and allows users to retrieve requested data through a standard data-access language, SQL.

Entity-type: Something of significance about which you want to store data in a database, e.g., customers, employees, suppliers, inventory items (note: this is a data modeling term – an entity becomes a table in a RDBMS)

Table: An entity-type (e.g., customer) and its attributes

Attribute: A property or characteristic of an entity. A column in a relational database table, e.g., customer name, reference #, address, zip ((note: this is a data modeling term – an attribute becomes a column in a RDBMS

Row (tuple, record): A record of data in a database table - a single occurrence or entity instance

Value: Data in a “cell” – the intersection between row and column in a database table

Types of AttributesKey (identifier in data modeling): Attribute, or combination of

attributes, that determines the values of other attributes in each row

Composite Key: Multiple-attribute keys; may be further subdivided, e.g., phone may be area code and number - can be a primary key

Candidate Key (CK): Attribute (or a minimum combination of attributes) that uniquely identifies each row in a given table - there can be more than one CK (employee entity type: SSN; assigned ID#)

Primary Key (PK) ( a unique identifier in data modeling): A CK selected to uniquely identify all other attributes in a given row; cannot be Null

Foreign Key (FK): ( a relationship in data modeling): Attribute (combination of attributes) whose value(s) must match the Primary Key in another table in the same database, or whose value(s) must be Null

Non-key Attribute: Attribute that is not part of a key

Attributes With A Null Value • Null Value: An unknown attribute value (e.g.,

salesperson not yet allocated to a customer) - it is not a zero. It is an optional attribute.

• Inclusion of nulls in a table is important - they provide a consistent way to distinguish between valid data such as a 0 and missing data, e.g., an account payable with 0 is good to see; one with an unknown balance can indicate a significant problem

• In most cases, nulls appear as blanks on a query’s result table on a screen

Relationships

• Data modeling term that indicates an association between tables: How the things of significance are related (A FK must match to an existing PK, or else be NULL)

• This controlled redundancy allows linking of tables (hence “relational”)

• Entity-Relationship Diagram (ERD): A data model (at the conceptual level) that shows the relationships enforcing business rules between entities (tables) in a database environment (Fig. 5.4)

Business Rules

• Narrative descriptions of policies, procedures, or principles in an organization

• Examples: – A pilot cannot be on duty for more than 10 hours

in a 24-hour period– A professor must teach at least three classes in

a semester– A class may not have fewer than 10 enrollments

Concept to Definition

FileConcept System Modeling RDBMS ExampleCollection of Objects File Entity-Type Table CustomersObject record entity row (tuple) John Doe, a particualr customerAspect field attribute column of a

data typeHair Color

Uniqueness index? identifier primary key customer #Relationship programmed relationship

with cardinalityand optionality

primary key toforeign key matching sometimes has orders

Value value realization cell Blonde

Example from Ch. 3 (P&S)

• Partial MSC:– Sale to Customer– Ship to Customer

• Multi-product merchandiser

• Salesperson, Shipping Clerk

Figure 3.25 Entity-relationship diagram.

Customer Invoiceis sent an1 M

Invoice Invoice LinecontainsM1

draws uponM M

InventoryInvoice

Figure 3.26 Revised entity-relationship diagram.

Customer Invoiceis sent an1 M

Invoice Invoice LinecontainsM1

InvoiceInvenM M

InventoryInvoice1 1

Figure 3.1 Sales transactions stored in a database accounting system.

Figure 3.7 The Customer relation, tblCustomer.

Figure 3.8 Primary key and foreign key relationship.

foreign key

primary key

Figure 3.9 Schemas of tables in the invoicing system.

tblCountryName (CountryID, CountryName, ExportCoffeeBags, ExportTeaPounds)

tblCustomer (CustomerID, CompanyName, Contact, Address, City, State,ZipCode, PhoneNumber, FaxNumber, CreditLimit)

tblEmployee (EmployeeID, EmployeeFirstName, EmployeeLastName,EmployeeWorkPhone, EmployeeTitleID, EmployeeCommRate,EmployeeHireDate, EmployeeDOB, EmployeeGender,EmployeeNotes)

tblEmployeeTitle (TitleID, Title)

tblInventory (InventoryID, ItemID, Caffeinated, Price, OnHand)

tblInventoryDescription (ItemID, Name, BeverageType, Flavored, CountryID, Comments)

tblInvoice (InvoiceID, InvoiceDate, OrderDate, CustomerID, EmployeeID,CustomerPO)

tblInvoiceLine (InvoiceID, InventoryID, Quantity, UnitPrice, Discount)

tblSalesTaxRate (StateAbbreviation, StateName, TaxRate, Population, LandArea)

Figure 3.10 Example rows in the Invoice table, tblInvoice.

primary keyforeign key

500 records in this table

Figure 3.11 Example rows in the Invoice Line table, tblInvoiceLine.

primary keyforeign key

Figure 3.12 Example rows in the primary Inventory table, tblInventory.

primary keyforeign key

Figure 3.13 Example rows in the secondary Inventory table, tblInventoryDescription.

primary keyforeign key

Normalization• Process of taking a “raw” database and breaking it

into logical units called tables, by following theoretical rules called normal forms

• The intent is to create a degree of controlled redundancy that allows two or more tables to be joined, by matching a FK in one table to a PK in another table

• Referential integrity (constraint created upon table creation) is enforced when every non-null FK value must match an existing PK value (if there is a FK, there has to be a PK for that FK in another table)

• Normalization has six nested normal forms• Generally a well-formed business database will be

normalized through 3rd normal form (3NF)

Benefits of Normalization • Greater overall database organization• Minimize data redundancies• Data consistency within the database• A more flexible database design• Data can be used more productively• A better handle on database security

Disadvantage of Normalization• Reduced database performance because database must locate requested tables and join data - requires additional processing logic

Normal Forms

—Normalization through a series of stages called NORMAL FORMS

–Each NF depends on normalization steps taken in the previous NF

»First Normal Form - 1NF»Second Normal Form - 2NF»Third Normal Form - 3NF

1NFFirst normal form rules:

•All key attributes must be defined

•There must be no repeating groups (values), i.e., each row/column intersection can have only one value

•All attributes must be functionally dependent on the PK, or part of the PK - e.g., SSN determines DOB, but DOB cannot determine SSN

Hint: Put all attributes in a two-dimensional flat table, with no repeating values

General Journal Entry:Traditional View - Unnormalized

Table 1

Traditional General Journal Entries

Tran_# Date Title Acct_# Debit Credit Explain

1 1/3/96 Cash 11001 100.00

Receivable 11003 200.00

Sales 41001 300.00

credit sale with down payment

2 1/3/96 COGS 51001 150.00

Inventory 11004 150.00

sale of inventory

Assume that the transaction # will reset to 1 at the beginning of the next fiscal year

GJ: First Normal Form

Table 2

General Journal Entries: 1NF

Tran_# Date Title Acct_# Debit Credit Explain

1 1/3/96 Cash 11001 100.00 0.00 credit sale

1 1/3/96 Receivable 11003 200.00 0.00 credit sale

1 1/3/96 Sales 41001 0.00 300.00 credit sale

2 1/3/96 COGS 51001 150.00 0.00 sale ofinventory

2 1/3/96 Inventory 11004 0.00 150.00 sale ofinventory

2NF–Second Normal Form Rules:

»Table is in 1NF; and»Table includes no partial dependencies;

that is, no attribute is dependent on only portion of the primary key – must be dependent on entire PK

Hint: Examine non-key attributes to determine whether any are dependent on only portion of a composite PK - this would violate 2NF

If a table only has one attribute as a PK, then it is in 2NF.

Chart of Accounts Table

Table C

General Journal Entries: 2NF, 3NF Acct_#

Title

11001

Cash

11003

Receivable

41001

Sales

51001

COGS

11004

Inventory

Transaction Listing Table

Table A

General Journal Entries: 2NF, 3NF

Tran_#

Date

Explain

1

1/3/96

credit sale with down payment

2

1/3/96

sale of inventory

Transaction Detail Table(Base Table)

Table B

General Journal Entries: 2NF

Tran_# Date Acct_# Debit Credit

1 1/3/96 11001 100.00 0.00

1 1/3/96 11003 200.00 0.00

1 1/3/96 41001 0.00 300.00

2 1/3/96 51001 150.00 0.00

2 1/3/96 11004 0.00 150.00

3NF–Third Normal Form Rules:

»Table is in 2NF and

»There are no transitive dependencies

Hint: You will violate 3NF if you can deduce the value of a non-key attribute by knowing the value of another non-key attribute

NormalizedTransaction Detail (Base) Table

Table D

General Journal Entries: 3NF

Tran_#

Date

Acct_#

Amount

1

1/3/96

11001

$100.00

1

1/3/96

11003

$200.00

1

1/3/96

41001

($300.00)

2

1/3/96

51001

$150.00

2

1/3/96

11004

($150.00)

Example from Ch. 3 (P&S)Continued

Figure 3.14 Example table containing repeating groups.

repeating group

repeating group

repeating group

repeating group

Figure 3.15 Example rows of the Customer table in first normal form (1NF).

Figure 3.16 Functional dependencies in the Customer table.

CustomerID CompanyName PhoneNumber Contact InvoiceID Total

Figure 3.17 Invoice table in second normal form (2NF).

Figure 3.18 Transitive dependencies in the Invoice table shown in Figure 3.17.

InvoiceID InvoiceDate OrderDate CustomerID EmployeeID Contact

Operations

• Restrict aka Select• Project• Join• SQL the standard language

– DDL: data definition language– DML: data manipulation language

• Destructive: CUD• Non-Destructive: R• CRUD again

Figure 3.19 Select operation.

Employee table:

ID Name Comm HireDate BirthDate Gender1301 Stonesifer 5% 07/06/96 03/10/66 F1364 Pruski 4% 12/01/00 01/26/79 M1528 Pacioli 6% 08/26/95 05/06/50 M1695 Nagasaki 4% 01/28/00 04/10/77 M2240 Stonely 15% 11/05/88 05/03/61 F2318 Hunter 8% 11/16/93 01/26/54 F2754 Kahn 5% 05/14/97 05/29/61 M3370 Kole 9% 02/08/92 03/23/63 M3432 English 8% 10/01/93 02/14/56 F3436 Gates 6% 04/11/95 03/09/54 M3458 Morrison 15% 12/13/89 07/04/56 F3609 Chang 5% 09/16/97 03/30/77 F

… … … … … …4112 Goldman 11% 12/24/90 03/05/62 M

Result of selection operation: HireDate > 1/1/97

ID Name Comm HireDate BirthDate Gender1364 Pruski 4% 12/01/00 01/26/79 M1695 Nagasaki 4% 01/28/00 04/10/77 M2754 Kahn 5% 05/14/97 05/29/61 M3609 Chang 5% 09/16/97 03/30/77 F

Figure 3.20 Project operation.

Employee table:

ID Name Comm HireDate BirthDate Gender Name Gender1301 Stonesifer 5% 07/06/96 03/10/66 F Stonesifer F1364 Pruski 4% 12/01/00 01/26/79 M Pruski M1528 Pacioli 6% 08/26/95 05/06/50 M Pacioli M

… … … … … … … …4057 Bateman 9% 02/16/92 05/01/58 M Bateman M4058 Halstead 5% 06/16/96 12/22/73 F Halstead F4082 Flintsteel 11% 03/21/90 08/22/58 F Flintsteel F4112 Goldman 11% 12/24/90 03/05/62 M Goldman M

Projection:

Figure 3.21 Join operation.

tblEmployee tblEmployeeTitle

ID Name TitleID HireDate Gender TitleID Title1301 Stonesifer 2 07/06/96 F 1 Sales Trainee1364 Pruski 1 12/01/00 M 2 Sales Associate1528 Pacioli 2 08/26/95 M 3 Senior Sales Associate1695 Nagasaki 1 01/28/00 M 4 Sales Manager2240 Stonely 3 11/05/88 F 5 Senior Sales Manager2318 Hunter 2 11/16/93 F 6 Division Sales Manager2754 Kahn 2 05/14/97 M 7 Regional Manager3370 Kole 2 02/08/92 M 8 Division Manager3432 English 2 10/01/93 F 9 National Sales Manager3436 Gates 2 04/11/95 M

… … … … …4082 Flintsteel 3 03/21/90 F4112 Goldman 3 12/24/90 M

Result of join operation:ID Name TitleID HireDate Gender Title1301 Stonesifer 2 07/06/96 F Sales Associate1364 Pruski 1 12/01/00 M Sales Trainee1528 Pacioli 2 08/26/95 M Sales Associate1695 Nagasaki 1 01/28/00 M Sales Trainee2240 Stonely 3 11/05/88 F Senior Sales Associate2318 Hunter 2 11/16/93 F Sales Associate2754 Kahn 2 05/14/97 M Sales Associate3370 Kole 2 02/08/92 M Sales Associate3432 English 2 10/01/93 F Sales Associate3436 Gates 2 04/11/95 M Sales Associate

… … … … … …4082 Flintsteel 3 03/21/90 F Senior Sales Associate4112 Goldman 3 12/24/90 M Senior Sales Associate

Figure 3.22 Joining tables with primary key/foreign key relationships.

tblCustomer CustomerID CompanyName Contact Address PhoneNumber FaxNumber CreditLimit

(city, state,zip)

tblInvoice InvoiceID InvoiceDate OrderDate CustomerID EmployeeID CustomerPO

tblInvoiceLine InvoiceID InventoryID Quantity UnitPrice Discount

tblInventory InventoryID ItemID Caffeinated Price OnHand

tblInventoryDescription ItemID Name BeverageType Flavored CountryID Comments