Overview

Meta data models are a critical component of a Managed Meta Data Environment (MME). Their quality impacts the entire MME project since a flawed model compounds all other technical problems. However, creating high quality models is one of the most difficult tasks to undertake; the stakes are high and the task is intellectually very deep and demanding. Design of the meta data models is the foundation on which the rest of the meta data infrastructure rides, you must do them right and understand them.

All designs are compromises. A good design finds the balancing point for all the forces that constrain it. The forces at play in meta data modeling require extensibility and extreme flexibility. Without these traits in a high quality meta data model, long term meta data repository success is jeopardized. This class will show you how to initially construct and achieve extensibility and flexibility in your meta data model.

Meta data becomes very powerful when it integrates information across a wide domain compared to stove-piped meta data. The domains can cover business processes, databases, application systems, XML, data warehouses, EAI systems, and more. Without a cohesive model for that integration, the integration will have great difficulty and the resulting meta data repository will be much less useful. This class help you understand how to make integrated models. It will also provide a foundational set of integrated meta data models and lessons from relevant meta data standards including, ISO11179, CWM, DMTF, MDA, and other related standards.

The class is workshop-focused since design concepts are best learned from doing. The final workshops are oriented to solving problems that you have in your current projects. The workshops allow you to learn how the design forces interact, how a design evolves and how to design in flexibility and extensibility.

Benefits To Your Company

• Your MME projects will grow in scope and only by having good quality meta data models can the project gracefully and affordably expand to meet the new scope. You will have higher quality designs and prevent creating stovepipe meta data applications.
• By understanding your meta data requirements, you will more easily and completely meet the needs of your environment.
• Flawed design of meta data models greatly impacts the complexity and cost of the associated software of the meta data project. You will lower software development costs.
• Understanding the models also conveys a deeper understanding of the domains. More powerful and flexible systems are the result.

Who Should Attend

• Data architects
• Enterprise architects
• Database designers
• Systems analysts
• Technical managers
• Software systems designers

Learning Objectives

You will understand:

• Importance of good quality meta data models
• How to successfully define your meta model requirements
• The process of meta data model design
• Principles of meta data model design
• A set of meta data models covering a very broad domain
• Meta data standards and how to apply them
• Technical hurdles in a MME

You will:

• Develop solutions to your own meta data model problem area
• Know how to evaluate commercial meta data tools based on their meta data models
• Learn how to work collaboratively to gain better design

What Makes This Certified Course Unique

This EWSolutions-certified course provides participants with practical, in-depth understanding of why meta data modeling is important to the success of the MME and how to deliver the best meta data models for your organization. Through case studies and team interaction attendees will attain the real-world implementation skills necessary to build a successful meta data model and how to integrate industry standards into your meta models.

Course Outline

1. Foundations of modeling
   • Modeling abstractions
   • Level of abstraction in a model
   • Identifying meta data requirements
   • Design forces
   • Meta data models differences
2. Implementation issues
   • Foundational technologies
   • Supporting application system
   • Reporting
3. A systems view of meta data
   • Meta data system
   • Driving meta data system design requirements
   • MME development challenges
4. Designing models of meta data
   • How to evaluate design
   • Evaluate the design process
   • What makes for good design in meta data models
   • Understanding meta data models use
   • Need for flexible designs
   • Architecture impacts
5. Standards
   • Concepts
     • Basic technology
     • Design forces impacting the standard
     • Essence of the standard and its goals
     • Application and use of the standard
6. Standards examined:
   • DMTF - Distributed Management Task Force - Common Information Model - used to model IT systems and management
   • OMG's Common Warehouse Metadata model (CWM) - covers the meta data models for data warehousing
   • OMG's Model Driven Architecture (MDA) - the meta data driven vision of the future of systems development
   • The Open Information Metadata model - a predecessor to the CWM but covers some other areas too
   • ISO 11179 – meta data specification and standardization of data elements
   • Others
7. Integrated meta data models
   • Foundation for universal meta data models
   • Essential parts of the IT infrastructure
   • Starting points for further designs and use
8. Evaluating meta data tools based on their meta data models
9. Final workshop on student's own meta data model problem.
10. Students are encouraged to bring meta data models they are currently using or developing for refinement.
11. Workshop conclusion
    • Summary, additional exercises, sources for further reading, etc.

Standard Duration

• 3 days (may be customized as needed)

To learn more about how EWSolutions can provide our World-Class Training for your company or to request a quote, please feel free to contact Dr. Anne Marie Smith, our Director of Education at AMSmith@EWSolutions.com or call her at 856.468.6194

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