The document outlines the design and development of an enterprise data warehouse for Carl Zeiss Vision North America, emphasizing the need for consolidated and user-friendly reporting. It details the project approach, including the use of various Microsoft tools for ETL, analytics, and reporting, as well as the importance of understanding business processes and requirements. Additionally, it highlights the significance of dimensional design and the creation of star schemas for data management and analytics.

1. Architecting A Data Warehouse:
A Case Study
A Case Study
Project: zBis
Carl Zeiss Vision North America
Mark Ginnebaugh, User Group Leader,
Mark Ginnebaugh User Group Leader
mark@designmind.com

2. The Journey
 Determined Need for Enterprise Data Warehouse
Determined Need for Enterprise Data Warehouse
 Worked with Business Users to Understand Business
Requirements
DDetermined Software Requirements
i dS f R i
 MS SQL Server 2005 & 2008
 MS SSIS (ETL Tool)
MS SSIS (ETL Tool)
 MS SSAS (Analytic Cube Tool)
 MS SSRS & Excel (Reporting Tools)
 SharePoint for Deploying Reports over Company
Intranet
 Designed and Developed zBis Data Warehouse
g p

3. Z BIS = What We Will Deliver
The DesignMind project team will deliver
The DesignMind project team will deliver
 Consolidated reporting for Carl Zeiss Vision North
America
 Reporting that is consistent and from one data
warehouse
R
Reporting that is easy to use and easy to access
ti th t i t d t
 Toolset will be flexible and able to grow and change
with your business
 Phase I rock solid download from ERP/Manf –
Providing ability to review lab information as a lab
network – not individual silos – with accurate
reporting across all products and services
We will deliver the best product possible based on the information we can place
in our data warehouse!

4. DesignMind
www.designmind.com

5. • Reporting from cubes – off source systems only –
No data warehouse
N d t h
• Disparate data systems with different results from
p y
each
• Most systems not balanced to GL
• Reporting for each business unit only
• No reporting across all business units

6. Transactional Cube of Approach
Sales Queries Other Reports Sales Reports
Corporate
Download
D l d
Data Mart Data Mart Data Mart
Finance Inventory Sales & Marketing
ETL Loads
ETL Load
ODS/Staging
g g
Operational Data Store
ETL Load
ERP Manufacturing Other

7. BI Tools/Analytics Active
Excel Static Reports
Reports
PerformancePoint Server
SharePoint
SQL
SQL Analytics
Reporting
Server (SSAS)
Server
Aggregated Finance Inventory
Sales
Data Mart Data Mart Data Mart
Data Mart
TBD
ETL Load (SSIS)
Data Warehouse
ETL Load (SSIS)
ODS/Staging
O S/S
Operational Data Store
ETL Load (SSIS)
ERP Manufacturing SW Other Data Sources

8. Introduction to Data Warehousing
 What is a Data Warehouse System
 Why a Data Warehouse Vs. Cubes on Source Systems
y y
 Star Schema Vs. Transactional Data Warehouses
 Star Schemas ease of system integrating
 Star Schemas provide substantial performance gains
 Star Schemas hierarchy capabilities or Drill Down
Capabilities
Capabilities
 Ralph Kimball Developed Current Industry Standards for Star
Schema – Dimensions and Facts

9. Data Warehouse Project Lifecycle
Technical Product
Architecture Selection &
Design Installation
Project
Business Data Staging Testing
Planning Dimensional Physical
Requirement Design & ETL & Deployment Maintenance
Modeling Design
Definition Development DW/DM
Report Report Report
Specifications Development Testing
Project Management

10. 4 + 1 – Steps
4 + 1 Steps
Dimensional Design Process
Ralph Kimball’s Process for Developing Star Schemas
1. Determine Business Process
 Model business Processes
Model business Processes
 Each Process will determine 1 or more Facts
 Design DW by Business Process Not Business Unit
2.
2 Identify the Grain of the Fact
Identify the Grain of the Fact
• What does 1 row in Fact table represent
• Transactional or Summary
3. Design the DW Dimensions
D i h DW Di i
4. Design the DW Facts
+1 Determine Hierarchies
Determine Hierarchies

11. Business Driven vs. Data Driven
 Design DW/BI System via Business Process
 Develop DW/BI System via Data from Source Systems
l / f
 Profile Data as early as possible
 Understand data and design DW using existing data
Understand data and design DW using existing data
 Design & Develop using both Business Process and available
Design & Develop using both Business Process and available
Data if possible

12. Understanding Your Business
 Identify key business sponsors for DW project
 Use Corporate Org Chart
 Setup initial interviews with key sponsors
 Develop Business Process diagrams
D
Develop high level Use Case Diagrams
l hi h l l U C Di
 Determine Business Hierarchies

13. The Business Executive Interview
The Business Executive Interview
• What are the objectives of your organization?
• What Business goals do you want to accomplish with the
development of zBis d t
d l t f Bi data warehouse System?
h S t ?
• How do you measure success? How do you know you are doing
How do you measure success? How do you know you are doing
well? How often do you measure your corporate performance?
• What are your key business issues that you are trying to solve
from the zBis system? If these issues are not justified what is the
impact to your department and organization?
impact to your department and organization?

14. The Business Executive Interview
The Business Executive Interview
• How do you identify problems or know when you might be
headed for trouble?
• How do you spot exceptions in your business? What
opportunities exist to dramatically impact your business based
opportunities exist to dramatically impact your business based
on improved access to information? What is the financial
impact
• If you could….., What would it mean to your business?
• What is your vision to better leverage information within your
What is your vision to better leverage information within your
organization?
•H
How do you anticipate that your staff will interact directly with
d ti i t th t t ff ill i t t di tl ith
this information?

15. Th B i M I t i
The Business Manager Interview
• What are the objectives of your department?
What are the objectives of your department?
• What are you trying to accomplish? How would do you go
about achieving your objectives?
about achieving your objectives?
• What are your success metrics?
• How do you know you are doing well?
• How often do you measure your department/team?
y y p
• How do you anticipate that your staff will interact directly with
this information?

16. Business Process Diagrams
 Understand Business Requirements for building
DW/BI system.
DW/BI system.
 Defines the Measures and Dimensions for data
Defines the Measures and Dimensions for data
warehouse

17. Determine Hierarchies
 Customer Hierarchies – Sales Channels
 Distribution Channels
 Business Channels
 Customer Channels
 Product Divisions
Product Divisions
 Sales Organizations
 Sales Office
Sales Office
 Buy Groups/Directly Purchase

18. Determine Hierarchies
 Product Hierarchy
 Manufacturer
 Brand
 Product Type – Each product type had own Hierarchy
Lens
 Service
 Equipment
 etc…
t
 Design
 Make/Model
/

19. Determine Hierarchies
 Geo Hierarchy
 Sales Division
 Sales Region
 Sales Territory

20. Conformed Dimensions
 Standardized dimensions across data warehouse
St d di d di i d t h
 Dimensions are associated with multiple business
processes
 Determine by using Bus Matrix & enforced in ETL
C f
Conformed Dimensions are shared and consistent
d Di i h d d it t
across fact tables

21. Use Data Warehouse BUS Matrix
 Use Data Warehouse BUS Matrix for
 Understanding & mapping of Business Processes and
Dimensions
 Ongoing DW/BI planning efforts
 Team & Management Communications
Team & Management Communications
 Understand Business Process unions across the enterprise

22. Data Warehouse BUS Matrix
Date Company Customer Product Geo Dist Ctr Promo
Company X X X X X X
Sales
Customer X X X X X X
Discounts
Product X X X X X X X
Cost
Company X X X
Inventory
Dist Ctr X X X
Inventory

23. De elop Dimensional Schema
Develop Dimensional Schema

24. Sl Ch i Di i
Slow Changing Dimensions
 Type 1 – Overwrite existing Dimension Row
Type 1 Overwrite existing Dimension Row
 Use when don’t need to keep history data row
 Can be used to correct bad data
 Type 2 – Create a new Dimension Row
 Use date and/or active non‐active fields to identify current
and inactive data rows
 Type 3 – Keep old and add new attributes in Dimension Row
 Allow Alternate realities to exist simultaneously in one
Allow Alternate realities to exist simultaneously in one
Dimension Row
 Slow Changing Dimensions are handled in the ETL

25. T f Di i
Type of Dimensions
 Mini‐Dimension
Mini Dimension
 Junk Dimensions
 Outrigger Dimensions
Outrigger Dimensions
 Small Static Dimensions
 Lookup tables
Lookup tables

26. T fF t
Type of Facts
 Transaction Fact Tables
 Snapshot Fact Tables
 Accumulating Snapshot Fact Tables
 Consolidated or Aggregated Fact Tables

27. B id T bl
Bridge Tables

28. B id T bl
Bridge Tables

29. R d d R di li
Recommended Reading list
 The Data Warehouse Toolkit: The Complete Guide to Dimensional
Modeling (Second Edition) by Ralph Kimball and Margy Ross
M d li (S d Edi i ) b R l h Ki b ll d M R
 The MicrosoftData Warehouse Toolkit: With SQL Server2005 and the
MicrosoftBusiness Intelligence Toolset by Joy Mundy, Warren
Thornthwaite, and Ralph Kimball
 Building a Data Warehouse: With Examples in SQL Server (Expert's Voice)
Building a Data Warehouse: With Examples in SQL Server (Expert s Voice)
by Vincent Rainardi
 The Data Warehouse Lifecycle Toolkit by Ralph Kimball, Margy Ross,
Warren Thornthwaite, and Joy Mundy
 The Data Warehouse ETL Toolkit: Practical Techniques for Extracting,
Cleanin by Ralph Kimball and Joe Caserta
by Ralph Kimball and Joe Caserta

30. To learn more or inquire about speaking opportunities,
please contact:
Mark Ginnebaugh, User Group Leader
mark@designmind.com