DW/BI Lifecycle in Depth (PDF version)

Why Attend

The data warehouse and business intelligence (DW/BI) system continues to be one of the most organizationally complex and technically interesting IT projects. This Kimball University course prepares you to successfully implement your DW/BI environment by distilling the essential elements of the popular Kimball approach as described in the bestselling book, The Data Warehouse Lifecycle Toolkit, Second Edition.

This course is packed with specific techniques, guidance and advice from initial project planning through deployment and maintenance. It is taught through a combination of lectures, class exercises, small group workshops, and individual problem solving.

The DW/BI Lifecycle in Depth course is appropriate for anyone who is new to DW/BI and wants to learn a holistic set of best practices from the beginning, or for anyone who has been through a couple projects and wants to refine their methods to better align with the proven, broadly-accepted Kimball approach.

Who Should Attend

This course is designed for all major roles on a DW/BI project, including project managers, business analysts, data modelers and database administrators, architects, and ETL or BI application designers/developers.

Instructors               

Margy Ross and  Joy Mundy, co-authors of The Data Warehouse Lifecycle Toolkit, Second Edition

Course Overview     

Day 1

• Introduction to the Kimball Lifecycle Approach
• Program/Project Planning and Management
• Business Requirements Analysis
• Dimensional Modeling Introduction

Day 2

• Dimensional Modeling continued
• Mature DW/BI System Checkups

Day 3

• Technical Architecture and System Setup
• Target Physical Database Design
• ETL System Planning and Design

Day 4

•  ETL System Implementation
•  BI Applications
•  DW/BI System Deployment, Support, and Growth

Course Details

DAY 1

Introduction to the Kimball Lifecycle Approach

• Roadmap of project tasks

Program/Project Planning and Management

• Readiness factors
• Risk assessment and mitigation plans
• Scoping and business justification
• Team roles and responsibilities
• Project plan development and maintenance
• Program management

Business Requirements Definition

• Program versus project requirements preparation
• Requirements gathering participants
• Techniques for gathering requirements and handling obstacles
• Program/project requirements deliverables
• Requirements prioritization

Dimensional Modeling

• Role of dimensional modeling in the Kimball, Corporate Information Factory (CIF) and hybrid architectures
• Fact and dimension table characteristics
• 4-step process for designing dimensional models
• Transaction fact tables
• Fact table granularity
• Denormalizing dimension table hierarchies
• Degenerate dimensions
• Date and time-of-day dimension considerations
• Dealing with nulls
• Surrogate key for dimensions
• Star versus snowflake schemas
• Centipede fact tables with too many dimensions
• Factless fact tables
• Additive, semi-additive, and non-additive facts
• Workshop: Converting requirements and source data realities into dimensional model
• Consolidated fact tables
• Dimension table role-playing
• Allocated facts at different levels of detail
• Complications with operational header/line data
• Multiple currencies

DAY 2           

Dimensional Modeling Continued

• Junk dimensions for miscellaneous transaction indicators
• Periodic and accumulating snapshot fact tables
• Implications of business processes on data architecture
• Enterprise Data Warehouse Bus Architecture and matrix for master data and integration
• Conformed dimensions – identical and shrunken roll-ups
• Exercise: Translate business requirements into DW Bus Matrix
• Slowly changing dimensions – type 1, 2, 3 and hybrid techniques for current and point-in-time attribute values
• Mini-dimensions for large, rapidly changing dimensions
• Exercise: Design review to identify common dimensional modeling flaws
• Design review dos and don’ts and mistakes to avoid
• Dimensional modeling process, tasks, and deliverables
• Exercise: Design enhancements to embellish existing design
• Exercise: Convert E-R model into dimensional model

Mature DW/BI System Check-ups

• Symptoms of sponsorship, data, infrastructure, and business acceptance disorders
• Prescribed treatment plans for common maturity problems

DAY 3

Technical Architecture Design

• Architecture concepts
• Topology options – independent data marts, enterprise data warehouse, and conformed data warehouse
• Common components and functionality
  • ETL system
  • Exercise: Processing slowing changing dimensions type 2
  • Presentation servers (RDBMS/OLAP)
  • Real time options – direct to source, ODS, and real time layer
  • BI application types and services
• Creating the architecture plan
• Exercise: Translating requirements into architecture implications

Product Selection and System Setup

• Architecture-based evaluation approach and matrices
• Infrastructure considerations
• Metadata management
• Securing the system

Physical Database Design

• Standards and naming conventions
• Physical model development
• Initial aggregation, indexing and storage plans
• Column-oriented database alternative
• Usage monitoring

Extract, Transformation and Load     

• Design the ETL system
  • Determine design patterns and implement key subsystems
  • Quality assurance and data validation system
  • Warehouse operations system
• ETL development workflow
  • Create high-level and detailed ETL schematics
  • Extract to create, filter and transfer source data
  • Cleaning and conforming dimensions and facts

DAY 4

Extract, Transformation and Load continued

• ETL development workflow continued
  • Preparing and delivering dimensions and facts
  • Data integration and master data management
  • Dealing with data quality issues
  • Aggregate management
  • Load cycle management
  • Exercise: “High-level ETL schematic” case study

BI Applications

• BI application types (ad hoc, standard reporting, analytic applications, dashboards) and audiences
• Specification of templates, applications and navigation framework
• Development of applications and BI portal

DW/BI System Deployment and Support

• System deployment
• Communication and documentation
• Training and support
• On-going user, data and system maintenance