Data Architecture Boot Camp - 4 day(s)

This class is a hands-on, intense course that includes lecture, hands on labs, and nightly homework. The Data Architecture Boot Camp is designed to address the critical need within the data warehousing industry for seasoned Data Architects. This class is designed to expand on the skills of people that already have some business analysis, systems analysis and database design skills, and couple them with group facilitation skills, process modeling and data warehouse design skills. Upon completion of this course, the student will be able to facilitate the gathering of business information needs requirements and turn them into reliable and forward-thinking data warehouse designs complete with data models and specifications for ETL and Business Intelligence development.

Prerequisites: Seven Years IT Experience, and one or more of the following: Database Design Experience, Requirements Gathering Experience, Data Warehouse Experience, Public Speaking Experience.

Day One
Data Warehouse Basics:

• Design Characteristics
• Architectural Considerations
• Critical Success Factors

Requirements Definition:

• Scope
• Process Modeling
• Data Modeling
• Information Needs Modeling

Facilitation Management:

• Purpose
• Techniques
• Understanding Groups
• Facilitator's Tool Kit
• LAB 1

Day Two
Business Process Modeling:

• Context Diagramming
• Process and Flow Characteristics
• Process Relationships
• Methodology
• Validation Steps
• LAB 2

Enterprise Data Modeling:

• Definition and Use
• Architecture
• Mechanics
• LAB 3

Business Information Needs:

• Purpose and Use
• Focus on Business Objectives
• LAB 4

Day Three
Data Modeling Overview:

• Logical vs Physical Models
• Logical Model Purpose and Components
• Physical Model Purpose and Components
• LAB 5

Data Modeling Entity-Attribute-Relationship Characterization:

• Understanding Entities and Attributes
• Representing Relationships and Hierarchies
• Unique Identifiers - Best Practices
• Naming Standards
• LAB 6

The Data Modeling Process:

• Techniques
• Understanding the Normal Forms
• Data Profiling
• LAB 7

Day Four
Data Architecture Data Acquisition:

• Data Warehouse Architectural Layers
• Source Layer Considerations
• Audit Layer Considerations
• LAB 8

Data Architecture ETL Considerations:

• Stage Layer Design
• Audit/Stage ETL Design
• LAB 9

Data Architecture Base-History-Dimensional Design:

• Base Layer Design Standards
• History Layer Design Standards
• Dimensional Design Standards
• LAB 10

Modeling for BI Tool Capabilities:

• Business Tool Considerations
• Leveraging RDBMS Capabilities
• Leveraging BI Tool Capabilities
• LAB 11

Conclusions:

• Data Warehouse Layers
• Presentation Components
• Audit Components
• Business Objective Focus
• FINAL EXAM

For more information or to schedule this class, contact: corecollege@vipconsulting.com