im03 - data modeling

INTERMEDIATE TO INFORMATION

MANAGEMENT

Presented by Kelvin Chan

IM03: Data Modeling

Introduction

• Meeting “Deliver More With Less” challenge, we need to leverage all resources especially data

• Data never lie and can input as a Historical Model that treat as Foundation

• The Time-proven method is through Dimensional Data structures.• Organizations often struggle to develop Dimensional Models that

consistently meet business needs due to less of knowledge and experience

What is Dimension?

• A set of Attributes describes the same Structural Thing

• Is a Business Perspective• Eg. Date, Customer, Product, Salesman

How would we interpret the below statement?

• Sales Report by Store– A Report Stating the Measurement of Sales Figures by

each Store– Store is Dimension– Sales Figures is Measure (Fact / Metric)

Degenerate Dimension• Is a dimension key in the Fact Table that does not have its

own Dimension Table, because all the concerned attributes have been placed in existing Dimension such as Salesman, Customer, Transaction Date

• Contains no attributes and hence does not join to any existing Dimension Table

Role-playing Dimension• Dimensions are often recycled for multiple applications

within the same database. • Eg. Date Dimension can be used for Invoice Date, as well as

Order Date, or Date of Birth

What does Key mean?• Key is a unique identifier of the row. We have below Key in Database:• Primary key. The Primary Unique Identifier of the row• Foreign key. It is the other Table Primary Key. Sometime we call it a

Dimension Key in Fact Table or Mapping Key or Look-up Key to Business Users

• Composite Key. A Unique Key that composite of two or more fields (attributes).

• Natural key. A Unique Key that is formed of attributes that already exist in the real world. For example, in Hong Kong, we have Hong Kong Identity Card Number (HKID no.) for each citizen and it is unique and also has a special meaning

• Surrogate key. A Unique Key with no business meaning. It normally generated by Database as Incremented Key or in SQL, MAX() + 1

Slowly Changing Dimension (SCD)

• Dimensions that change over time• Typically, there are three type of SCD• Type 1: Replace the entry with a new attributes• Type 2: Create a new entry and mark the old record as

outdated• Type 3: Add additional column for each tracking attribute,

eg. NAME, OLD_NAME

Recommendation on Which SCD Type?

• If you need to track the changes over time, a SCD Type II is recommended

• If you don’t care about the historical change on the captioned dimension, a SCD Type I is suggested

• In general, Data Warehouse seldom implement SCD Type II

Example on SCD Type II

Assume there is a new Customer Profile created on 2009-01-22 and with TOP30 attribute

Customer Name Created Date TOP30 T300 T4Peter Chan 2009-01-22 Y

Custmer Attribute

In Excel, we keep the record as below:

Customer Name Effective Start Effective End TOP30 T300 T4Peter Chan 2009-01-22 2099-12-31 Y

As of Date: 2009-01-22 Custmer Attribute

Customer Name Created Date TOP30 T300 T4Peter Chan 2009-01-22 Y

Custmer Attribute

Initial Condition:

Attribute Change Log for Peter Chan


New Conditions:

Customer Name Effective Date Action AttributePeter Chan 2009-05-01 Remove TOP30Peter Chan 2009-05-01 Add T300

J ournal

Customer Name Effective Start Effective End TOP30 T300 T4Peter Chan 2009-01-22 2099-12-31 Y

As of Date: 2009-01-22 Custmer AttributeInitial Condition:

Customer Name Effective Start Effective End TOP30 T300 T4Peter Chan 2009-01-22 2009-04-30 YPeter Chan 2009-05-01 2099-12-31 Y



New Condition:

Initial Condition:Customer Name Effective Start Effective End TOP30 T300 T4Peter Chan 2009-01-22 2009-04-30 YPeter Chan 2009-05-01 2099-12-31 Y


Customer Name Effective Date Action AttributePeter Chan 2009-06-01 Add TOP30

J ournal

Customer Name Effective Start Effective End TOP30 T300 T4Peter Chan 2009-01-22 2009-04-30 YPeter Chan 2009-05-01 2009-05-31 YPeter Chan 2009-06-01 2099-12-31 Y Y
