The document provides an overview of the data warehouse/business intelligence (DW/BI) system lifecycle, emphasizing the Kimball approach to building effective systems that meet business requirements. It covers various phases such as project planning, defining business requirements, ETL system design, and BI application development, while highlighting the importance of incremental delivery and collaboration between IT and business teams. Key concepts include the need for a conformed data architecture, dimensional modeling, and strategies for managing data quality.

1. THE DW/BI SYSTEM LIFECYCLE
OVERVIEW
The Kimball Approach
Warren Thornthwaite

2. Acknowledgments
 Course materials adapted from...
 The Microsoft Data Warehouse Toolkit
 J. Mundy, W. Thornthwaite (Wiley 2006)
 The Data Warehouse Lifecycle Toolkit, 2nd Ed.
 R. Kimball, M. Ross, W. Thornthwaite,
J. Mundy, B. Becker (Wiley 2008)
 The Data Warehouse Toolkit, 2nd Ed.
 R. Kimball, M. Ross (Wiley 2002)
 Kimball University
 Course materials
 Design Tips and Intelligent Enterprise articles at
www.KimballUniversity.com
2

3. Acknowledgments
 Course materials adapted from...
 The Data Warehouse Lifecycle Toolkit, 2nd Ed.
 R. Kimball, M. Ross, W. Thornthwaite,
J. Mundy, B. Becker (Wiley 2008)
 The Data Warehouse Toolkit, 2nd Ed.
 R. Kimball, M. Ross (Wiley 2002)
 The Microsoft Data Warehouse Toolkit, 2nd Ed.
 J. Mundy, W. Thornthwaite (Wiley 2011)
 Kimball Group / Kimball University
 Course materials
 Design Tips and Intelligent Enterprise articles at
www.KimballGroup.com

4. Session Agenda
 DW/BI Lifecycle business context
 DW/BI System Lifecycle overview
 Planning and managing the project/program
 Defining business requirements
 Creating the dimensional modeling (the data track)
 Designing the DW/BI system architecture (the technology track)
 Building the ETL system
 Building BI applications (the applications track)
 Rollout and repeat
4

5. The DW/BI Lifecycle Context

6. The Business Context to the Lifecycle
 Business people need information to make plans and assess
results, and this need continues to grow
 Data is captured by complex systems structured to support
specific transaction requirements
 Business people find it difficult to get business information from
data in transaction systems
Therefore, our job is to create a system that will:
reliably take data out of the source systems,
restructure its form and content as appropriate for business analysis,
and provide it to the business people via tools they can actually use.
6

7. Strengthen Your Awareness of the
Broader Context
 Ask yourself “What am I doing?”
 Writing a program
 Building a database
 Creating a DW/BI system
 Solving a set of high value, difficult problems
 Thebroader you think, the more effective you will be
in addressing business problems and delivering real
business value.
7

8. DW/BI System Lifecycle Overview

9. The Kimball Approach
 Understand business requirements and deliver business value
 Follow a proven methodology: the DW Lifecycle
 Build and deliver incrementally (by business process) within an
enterprise data framework (Bus Matrix and conformed dimensions)
 Design the data sets for flexibility, usability and performance
(Business Process Dimensional Model)
 Provide the complete solution, including reports, query tools, portals,
documentation, training, and support
9

10. Business Requirements Are the
Foundation of Success
 The more you focus your efforts on information-based
business opportunities that are high value and
relatively easy to implement, the more likely you will
be to succeed.
 Regardless of which ETL or BI tools you use
 Regardless of which database you use
 Regardless of your technical skills

11. The DW/BI Lifecycle
Technical Product
Architecture Selection &
Design Installation Growth
Business
Project Dimensional Physical ETL Design &
Requirements Deployment
Planning Modeling Design Development
Definition
BI BI Maintenance
Application Application
Specification Development
Project Management
11

12. Planning and Managing the
Project/Program
Technical Product
Architecture Selection &
Design Installation Growth
Business
Dimensional Physical ETL Design &
Requirements Deployment
Modeling Design Development
Definition
BI BI Maintenance
Application Application
Specification Development

13. Project Planning & Management
Highlights
 Assess readiness and determine starting point
 Define the program / project – (2 phased startup)
 Phase 1 program level: Enterprise business requirements
 Prioritization / Business justification
 Phase 2 project scope: Initial business process lifecycle iteration
 Plan the project
 Team roles and responsibilities
 Detailed project plan
 Manage the project
 Control scope creep
 Communication to manage expectations
13

14. Data Warehouse
Readiness Factors
1. Strong business management sponsor(s) (60%)
 Vision of value, Politically capable, Realistic
2. Compelling business motivation (15%)
 Generates urgency and supplies justification
3. Feasibility (15%)
 Data feasibility
4. Other organizational Issues (10%)
 IT/Business partnership
 Current analytic culture
 Requirements definition and prioritization are best tools to
address shortfalls
 Proof of concept demo is generally a bad idea
14

15. Defining the Project:
the Two Phased Startup
 Phase 1: Enterprise Requirements definition
 Phase 2: Project requirements focused on top priority
business process
1 2
Enterprise Project
(Horizontal) (Vertical)
Initial Requirements
Project
Project Prioritization
Business Planning Business
Scope Process
Requirement Requirement
Definition Definition
Project Management
15

16. Planning the Project:
the Phase 2 Detailed Project Plan
 Assign roles and responsibilities
 Leverage existing project planning tools
 List end-to-end tasks for entire Lifecycle
 Integrated and detailed
 Key team members should develop estimates for their
tasks
 User acceptance after major tasks & deliverables
 Keep unique characteristics in mind
 Cross-functional, high visibility, iterative
 Data problems will happen – identify them early!
16

17. Estimating Guidelines for
Project Planning / Management
 Phase 1 requirements and prioritization
 Key determinates: Readiness / sponsor scenario
 Rule of thumb: Three weeks to months +
 Developing the project plan
 Rule of thumb: Less than two weeks
 On-going project management
 Key determinates: Organizational complexities, #
players, # issues, political realities, ...
 Rule of thumb: Often dedicated to DW/BI team
17

18. Defining Business Requirements
Technical Product
Architecture Selection &
Design Installation Growth
Project Dimensional Physical ETL Design &
Deployment
Planning Modeling Design Development
BI BI Maintenance
Application Application
Specification Development
Project Management

19. Defining Business Requirements:
Overall Process
 Interviews are preferable
 Three phases
 Preparation (do your homework)
 Interviews (including data source experts)
 Documentation
 Two passes
 Enterprise
 Project
19

20. Defining Business Requirements: the
Interviews
 Assign roles and be ready
 Must ask the right question
 NOT “What do you want?”
 Ask “What do you do?”
(“What are your roles and responsibilities? What could you do better
with improved access to information?”)
 Cover key areas and listen
 Take notes
 Debrief with team immediately after
 Common themes / opportunities
 Required data (business processes)
 Do-ability
 Areas requiring clarification
 User analytical / technical sophistication
20

21. Defining Business Requirements:
Interview Results
 You must do the formal documentation
 Validation
 Reference material
 Individual interview write-ups
 Summary, not transcript
 Business Objectives
 Analytic opportunities and info requirements
 Project Success Criteria
 Consolidated findings document
 Main content is list and descriptions of analytic opportunities
 Includes the initial data warehouse bus matrix
21

22. The Data Warehouse Bus Matrix is the
Enterprise Data Architecture Framework
 Matrix of business processes and
conformed dimensions
Business <--- Dimensions --->
Processes Date Product Dist Ctr Vendor Shipper Store Customer Promo
Purchase Orders X X X X
Dist Ctr Delivery X X X X X
Dist Ctr Inventory X X X
Store Deliveries X X X X X
Store Inventory X X X
Store Sales X X X X X
Returns X X X X X
22

23. Requirements Prioritization Session
 Facilitated session with Business and IT management
 Agenda:
 Confirm requirements
 Prioritize analytic info groups High
A
 Evaluate business B
impact / benefit
 Evaluate feasibility E
Potential G
Business F
 Outcomes: Impact
H
 Mgmt education on feasibility D
 “Right” opportunities C
 Consensus Low
 Ownership / Sponsorship Low Feasibility High
 Roadmap for growth
23

24. Defining Business Requirements
Summary
 Understanding business requirements is CRITICAL to
successful DW/BI system
 Don’t overlook the up-front preparation
 Focus on listening
 Document what you’ve heard
 Analytic requirements
 Enterprise bus matrix
 Prioritize with senior management
24

25. Designing the Dimensional Model
The Data Track
Technical Product
Architecture Selection &
Design Installation Growth
Business
Project Requirements Deployment
Planning
Definition
BI BI Maintenance
Application Application
Specification Development
Project Management

26. Designing the Business
Process Dimensional Model
 Basic dimensional modeling concepts
 Slowly changing dimensions
 The dimensional modeling process
 Data profiling and data stewardship
26

27. Terminology: Business Process
Dimensional Model (or Star Schema)
 Normalized fact table (business event) for a single business
process at atomic detail level (the grain)
 Denormalized dimensions (entities/objects) with all attributes
and one active row per
occurrence of the object Product KEY Product KEY Store KEY
Date KEY
Product Store KEY Store
 Benefits: Attributes Promo KEY Attributes
 Easier to understand
 Better performance
 Pre-joined dimensions Date KEY Promo KEY
Facts
 Star join optimization Promo
Date
 Dimensional engine Attributes
Attributes
 Extensible to handle change
27

28. Terminology:
Slowly Changing Dimension
 Techniques for handling changes to dimension attributes
 Type 1: overwrite attribute values
 Common default, appropriate for corrections
 Type 2 : create a new dimension row when attribute value
changes
 Flexible technique, critical for accurately tracking behavior over time
 Hybrid combinations of 1 and 2 are most common
 Integration Services has basic Slowly Changing Dimension
management built in
28

29. Dimensional Modeling Process
 Develop the Data Warehouse Bus matrix
 Start with the 4-step method to identify facts and dimensions
 Step 1: Identify the business process (what row on the matrix should we
start with?)
 Step 2: Declare the grain
 Step 3: Choose the dimensions
 Step 4: Choose the facts
 Diagram the dimensional model
 Fill in the dimension and fact attributes (Step 5)
 Use business requirements + source docs + data profiling
 Follow naming standards (understandable to business)
 Try the dimensional modeling spreadsheet from the book’s web site:
http://www.kimballgroup.com/html/booksMDWTtools.html
29

30. Creating Conformed Dimensions
(Step 5)
 All fact tables that share dimensions must use the same
dimension with the same key
 Agree on column names and definitions
 Identify best source
 Assign surrogate key to every dimension row
Product
 Combine all attributes into Surrogate Key Product KEY
Master dimension table Business Key Product Code
 Use the Master dimension Description
to map the business Marketing Brand
Category
key in the fact rows Height
to the surrogate key for Logistics
Width
each business process Weight
that uses the dimension Cost Acctg. Standard Cost
30

31. Dealing with Data Quality
Data Profiling Data Stewardship
 Data exploration to determine  Identify people on the
data feasibility business side who care
 Understand data structures,  Enroll them in data
relationships and business rules exploration
 Identify (and document) data
problems  Include source systems
 Tools
managers
 Simple: SQL, BI tool, RS project  Agree on names, definitions,
(see kimballgroup.com) business rules, etc.
 Advanced: Data Profiling tool

32. Dimensional Modeling Summary
 Enterprise perspective / roadmap
 Enterprise Data Warehouse Bus Matrix
 Presentation area must be dimensional
 Ease of use
 Query performance
 Start with atomic detail, not just summary
 Conform dimensions for consistency
 Apply SCD techniques for handling attribute changes
 Engage business to define names, content, business rules, and deal with data
quality
 Process
 4-step approach
 1) Business process, 2) grain, 3) dimensions, 4) facts
 Fill in the attributes and measures (Step 5)
32

33. Designing the DW/BI System
Architecture
The Technology Track
Growth
Business
Project Dimensional Physical ETL Design &
Requirements Deployment
Planning Modeling Design Development
Definition
BI BI Maintenance
Application Application
Specification Development
Project Management

34. Architecture Principles
 The DW/BI System architecture is the set of
components and functionality needed to meet the
business requirements
 Business requirements determine architecture
 Most of the tools include only core functionality. You
will have to write code for your specific issues.
 Thismeans your DW/BI system architecture will not
be the same as your neighbor’s
 Draw it out and write it down!
34

35. The Goal: A Conformed DW/BI System
Source
Systems
ETL Business Process
System Dimensional Models
Relational Analysis Logistics
Inventory Dimension DMBS Services
Processing
Inventory
Fact Sales
Orders
Processing
Orders
Billing
Aggregates
- Analysis Svcs. Returns Marketing
- Relational DB
Billing / • Models contain atomic-level detail
Returns • with aggregates for performance
• and transparent aggregate navigation
• Includes both relational dimensional model
and OLAP dimensional model
35

36. What Goes Into a Typical
Warehouse Architecture?
High Level Warehouse Technical Architecture Model
Back Room Front Room
Metadata
BI Applications
Presentation Server Layer Data Access Services Direct access
Dimension query and
Source Data Quality Real Time Layer
Maintenance Operational reporting tools
BI Portal
Systems Workbench
- Operational Front End BI and Enterprise
- ODS Standard
Performanc Reporting
- Desktop tools Reports
- XML / Flat files ETL Metadata Dim 4 Dim 1 e Mgmt Services
Aggregate Navigator
Fact
- MDM system Services
Dim 3 Dim 2
Enterprise Bus Matrix
- External Storage Repository Dim 4 Dim 1
Analytic
Applications
Fact
-… Dim 3 Dim 2
Dim 4 Dim 1
Dashboards &
Fact
Dim 3 Dim 2
Delivery Admin. Web Scorecards
Cleaning &
Applications
Dim 4 Dim 1
Extract Services Services
Fact
Preparing for
Conforming
Dim 3 Dim 2
Presentation Dim 4
Fact
Dim 1 Operational
Dim 3 Dim 2 Aggregates for Metadata BI
Management Atomic level
Performance Security Mgmt.
Operational
ETL Services business process Services and Systems and
dimensional models Browsing Reports
Infrastructure

37. Sample Architecture Plan Document
Outline
 Executive Overview
 Architecture Implications of Business Requirements
 Architecture Overview
 Back Room and Front Room Services
 Data Stores (Source, Staging, Presentation Servers)
 Metadata Strategy
 ETL System Strategy and Details
 BI Applications System Strategy and Details
 Infrastructure
 Architecture Implementation Phases and Timing
 Technology Evaluation Process
37
 Architecture Models

38. The ETL System
Populating the data warehouse
Technical Product
Architecture Selection &
Design Installation Growth
Business
Project Dimensional Physical
Requirements Deployment
Planning Modeling Design
Definition
BI BI Maintenance
Application Application
Specification Development
Project Management

39. ETL Startup
 Create an ETL Plan
 Based on dimensional model docs, data quality, and
additional research
 Map source tables to each target and identify required
transformations
 Each target flow corresponds to an ETL package
 Setup development environment
39

40. The ETL Functions
 Understand the core functions common to most ETL
systems (there are 34 of them)
 They fall into four categories:
 Extract: get the data out of the source and into the DW
system
 Transformation: clean the data and conform it to
standard definitions and contents
 Prepare the data for presentation: “dimensionalization”
 Manage all the above functions in a coherent system
40

41. Populating Dimension Tables
 Recreating Type 2 change history can be a challenge
 Cleaning and conforming can be complex
 Integrating multiple sources and de-duplicating is a
process unique to your business
 Integration Services’ tools including Fuzzy Lookup can
help for simple problems
 Complex problems require a third party tool or service
 Universaldimension function is handling changes in
dimension attributes (SCDs)
41

42. Slowly Changing Dimensions
 Dimension attributes will change over time
 Business users determine what must be tracked
1
Source New Source Rows Assign Simple Insert
Surrogate Master
File
Keys Dimension
2
Type 2
Assign Update
Changed Insert New
Compare Surrogate Current_Flags
Rows Current Rows
Keys and Dates
3 Type 1
Update
Changed
Master Value in
Rows Replace
Dimension Current Row Most-Recent-
Key Map w/Current
No Change
Rows
(Optional)
Ignore
42

43. Populating Fact Tables
 Populate the initial historical load
 Different source systems, data structures, formats over time
 History missing
 Must build historical Slowly Changing Dimensions first
 Can take a long time
 Develop incremental load logic
 Usually different packages from the historical load
 Push vs. Pull (extract ownership)
 Identify new / changed rows
 Key substitution is big task
 Catch up history and start incremental loads
 Validate data at each step
43

44. Fact Table ETL:
Surrogate Key Lookup (Pipeline)
 Replace production keys in the fact table extract with surrogate
keys from the dimensions
 Maintain and ensure referential integrity!
 Watch for fact table key collisions
Most Recent Most Recent Most Recent Most Recent
Time Key Product Key Store Key Promotion
Map Map Map Key Map
time_ID product_ID store_ID promo_ID
time_key product_key store_key promo_key
Fact Table Fact Table
replace replace replace replace
Records With Records With
time_ID with product_ID store_ID with promo_ID w/
Production IDS Surrogate Keys
surrogate w/ surrogate surrogate surrogate
time_ID time_key product_key store_key promo_key time_key
product_ID product_key
store_ID store_key
promotion_ID promotion_key
dollar_sales dollar_sales
unit_sales
dollar_cost
Referential Integrity Failures unit_sales
dollar_cost
Key Collisions
load fact
table records
into DBMS
44

45. ETL System Summary
 Develop a plan and setup development environment
 Build out historical dimensions, including Type 2
attribute changes
 Build out historical facts based on historical dimension
key substitution
 Design and build Analysis Services cube(s)
 Create incremental load packages
45

46. BI Applications
Delivering Value --not just data
Technical Product
Architecture Selection &
Design Installation Growth
Business
Project Dimensional Physical ETL Design &
Requirements Deployment
Planning Modeling Design Development
Definition
Maintenance
Project Management

47. BI Application
Concepts
 Role and definition
 Application design
 Templates
 Navigation
 Applications development
 Additional Value
 Data validation
 Performance tuning
 Character development
47

48. Role and Definition of BI
Applications
Nature Consumer Information
of Use Type Interface Value of BI Appl’n
Ad hoc - Reporting / Analysis
Strategic power
Desktop tools for
Do-it-yourself examples
users - Assured reference points
queries Migration
Path
Push-button - Low effort
knowledge BI - Current business view
workers - Flexible
Applications
Migration
Path
Standard Operational
report Reporting
Operational consumers Environment

49. The BI Application Continuum
Standard Analytic
Reports Applications
Simple, fixed Standard, flexible Complex analytic
format, pre-run format, parameter applications with
reports driven reports domain expertise,
embedded algorithms
and operational system
feedback loops

50. Design and Spec BI Applications
 Create and prioritize a candidate report list
 Develop a standard report template
 Mandatory content (descriptions, titles, etc.)
 Output look and feel
 Develop mock-ups for top N candidate BI
applications
 Report/dashboard layouts with parameters
 Document data sets, business rules, calculations, etc.
 End user navigation
 Structured path through templates and reports
 This becomes the core of the BI Portal
50

51. Sample BI Application Mock-up
From the Geography
Dimension Variable Time
Period
Variable Time Period
Global BI System
<Geography Name> We’re here to help
Topline Performance Report
<Period> Compared to <Previous Period>
Sales YA Sales Sales Market % Var
<<Product Line>> Units Units Index Share Prev Share
xxxxxxxxxx xxx,xxx xxx,xxx xx.x xx.xx x.x
xxxxxxxxxx xxx,xxx xxx,xxx xx.x xx.xx x.x
xxxxxxxxxx xxx,xxx xxx,xxx xx.x xx.xx x.x
xxxxxxxxxx xxx,xxx xxx,xxx xx.x xx.xx x.x
xxxxxxxxxx xxx,xxx xxx,xxx xx.x xx.xx x.x
Report Information
Report Category: {Sales Analysis}
Report Name: {Topline Performance Report – current vs. prior period by Geography}
Source: {DW - Sales Performance} Run on: {Run_Date} Page { 1}
Product Lines that meet the constraint criteria
(may have drill down capability).

52. Sample Navigation Design
BI Portal
Marketing Sales Purchasing Manufact-
uring
Sales Activity Pipeline and Sales Force Web Channel
Forecasting Management Sales
Product Topline
Product Product Trend
Product Market Topline
Market Market Trend
Market
Template
Topline Template
Trend Template
Topline Template
Trend

53. Adventure Works Cycles DW/BI Portal
Starting Point

54. Developing BI Applications
 Begin development when...
 Data is ready
 Front end tool installed and environment set-up
 Pull out report specifications
 Build reports
 Validate tool calculations and drill-paths
 Validation data
 Performance Tuning
 Ongoing maintenance and enhancement resources
 Character Development
54

55. BI Applications Summary
 BI Applications play a critical role
 High value reporting
 Broad audience
 Data Warehouse team learning opportunity
 Design Application standards, specs and navigation up
front
 Develop Applications when data is ready
 Validate tool capabilities
 Check data quality
 Identify query performance problems
 Make sure you have dedicated resources to maintain and
enhance your BI offerings
55

56. Rollout and Repeat
Security, Deployment, Operations, and Growth
Technical Product
Architecture Selection &
Design Installation
Business
Project Dimensional Physical ETL Design &
Requirements
Planning Modeling Design Development
Definition
BI BI
Application Application
Specification Development
Project Management

57. The Thankless Tasks that Must Be
Done
 Security
 Deployment process
 User support
 Training, desktop, support, documentation
 System deployment
 dev  Test  Production
 Maintenance
 System
 User support
57

58. Growth
 The Lifecycle is an iterative process
 Revisitopportunities with business and select the next
top priority
 Build additional dimensions
 Load facts for this business process
(fill out the bus matrix row by row)
 Build and deliver the BI applications
 Rollout and repeat!
58

59. Start the Business Dimensional Lifecycle All
Over Again!
Technical Product
Architecture Selection &
Design Installation Growth
Business
Project Dimensional Physical ETL Design &
Requirements Deployment
Planning Modeling Design Development
Definition
BI BI Maintenance
Application Application
Specification Development
Project Management

60. Conclusion
 The Lifecycle is a proven DW/BI methodology
 Keys to success:
 Business value focused
 Short, iterative delivery cycles
 In an Enterprise framework
 Full, end-to-end solution
60

61. Contact Info
 warren@kimballgroup.com
 Visit www.kimballgroup.com for
 Articles
 Design tips (149 and counting)
 Whitepapers
 Forum
 Allof the concepts discussed are expanded on in the
Kimball Toolkit series of books

62. THANK YOU
for attending this session and the
2009 PASS Summit in Seattle