TDWI Advanced Data Modeling Techniques, Ireland

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Whether you are a business data modeler who represents data requirements as entities and relationships, or a physical data modeler more concerned with tables, columns, and indexes, you know that the hard stuff lies beneath the surface. Every data design, whether logical or technical, is challenged by one or more complex considerations—scalability, adaptability, performance, legacy and package databases, etc. Every data model raises questions. Advanced modeling techniques provide many of the answers. This course explores different situations facing data modeling practitioners and provides information and techniques to help them develop the appropriate data models.

There are no prerequisites for this course.

Data modelers with some practical experience; data architects; database developers

Enterprise architecture approaches and how to apply them
How big data and analytics impact traditional approaches
Different data models and how they relate to each other
The role of modeling in analytics
Higher normalization forms
How to effectively apply generalization and specialization
The role of metadata management in data governance
State and time dependencies and how to handle them
How to validate the data model
How to transform the business data model into physical models based on the application
The implications of alternative storage approaches
The roles and structures of complementary models
How to deal with multiple time zones and currencies

Module 1: Data Modeling Concepts

Enterprise Architecture
- Definition
- Zachman Framework Overview
- Data Modeling Framework for BI
- Levels of Data Models – Enterprise Perspective
- Levels of Data Models – Project Perspective
- The Open Group Architecture Framework
- Control Objectives for Information Technology
- Frameworks – Discussion
Higher Normal Forms
- Boyce-Codd Normal Form
- Fourth Normal Form
- Fifth Normal Form
- Anchor Modeling
- Data Vault Modeling
Specialization and Generalization
- Roles and Classifications
- Considerations
- Party
Presentation
- Standards

Module 2: Business Data Model Development

Business Data Model Development Approaches
- Top-Down
- Bottom-Up
- Generic Models
- Limited Depth Models
Data Modeling Roles
- Functions, Traits, and Challenges
Business Data Model Application
- Basis for System Data Model
- Transformation and Integration Foundation
- Package Selection
- Business Communications
- Data Profiling
- Data Governance
Data Governance
- Definition
- Quality Improvement
- Real-Time Implications
- Metadata Management
- Information Subject Area
- Big Data
- Big Data Challenges

Module 3: System and Physical Data Model Development

Data Modeling Roles
- Functions, Traits, and Challenges
Globalization / Localization
- Information Needs
- Currencies
- Time Zones
- Languages
Non-Relational Data Structures
- Columnar Databases
- In-Memory Databases
- XML Structures
- Key Value Pairs
Business Analytics
- Definition
- Schema on Read
- Modeling Process

Module 4: Additional Concepts

Recursive Relationships
- Normalized Approach
- Dimensional Approach
Cloud
- Modeling Implications
Complementary Models
- State Transition Model
- Function Models
- Process Models
- Model Management
Model Management
- Model Validation and Testing
- Model Synchronization
- Tool Exploitation
- Data Modeling Tools
- Repositories

Module 5: Summary and Conclusions

Summary of Key Points
- A Quick Review
Appendix A: Bibliography and References
Appendix B: Exercises
- Exercise 1: Normalization to Higher Normal Forms
- Exercise 2: Party Modeling
- Exercise 3: Financial Institution Model
- Exercise 4: Model Application for Data Profiling
- Exercise 5: Application System Model Development
- Exercise 6: Model Evaluation

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TDWI Advanced Data Modeling Techniques Training Course in Ireland

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TDWI Advanced Data Modeling Techniques Training in Ireland

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TDWI Advanced Data Modeling Techniques Training in Ireland

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