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TRAINING COURSES

Empower your team with the knowledge and skills they need to perform. 

 

Our experts work with you to make sure that your needs and organizational goals are met.  Our engaging and informative courses empower your team and drive performance, delivering results. Our courses offer hands-on training that can be conducted in-person or virtually and cover best practices in data architecture, data modeling, data model development, integration, and tooling. 

Choose a course that's right for you.

see what you'll learn

 

DATA ARCHITECTURE

 

TWO DAY COURSE

 

FACE TRAINING
 

TWO DAY COURSE

 

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DATA ARCHITECTURE &  INTEGRATION
 

THREE DAY COURSE

 

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INTEGRATION,
PHENOM & CINC



 

THREE DAY COURSE

 

DATA ARCHITECTURE
INTEGRATION
PHENOM & CINC

FOUR/FIVE DAY COURSE

 

 

Data Architecture Training

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DAY

1

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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DAY

2

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  • An introduction to data  architecture model structure.

  • The difference between conceptual, logical, and platform data models.

  • Data modeling best practices.

  • Patterns in data modeling.

  • Terminology related to different model components.

  • How to use data models for documenting interfaces.

  • Data model validity.

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  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

FACE Training

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DAY

1

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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  • Overview of the FACE Architecture, Portability and Interoperability as Key Drivers

  • FACE Software Architecture & Data Architecture Concepts and design patterns

  • Introduction of FACE Software Segments

  • Implementing a FACE Unit of Conformance (UoC)

  • API Overview and Relationship to FACE Data Modeling

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DAY

2

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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  • Portable Software Segment Design

  • Platform Specific Software Segment and IO Design

  • Transport Service Segment Design Considerations

  • Integrating FACE UoCs with the Transport Service

  • Conformance.  Requirements and Tools  

  • Hands On UoC generation and Integration

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Data Architecture & Integration
Training

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DAY

2

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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  • An introduction to data  architecture model structure.

  • The difference between conceptual, logical, and platform data models.

  • Data modeling best practices.

  • Patterns in data modeling.

  • Terminology related to different model components.

  • How to use data models for documenting interfaces.

  • Data model validity.

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DAY

3

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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•Fundamental concepts, principles, and terminology of data integration.

•Common methods of data integration.

•Data integration techniques and technologies.

•Roles, purpose, and variations of data integration.

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DAY

1

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

       Integration,                 
                              Training 

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DAY

3

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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•An overview of CinC.

•Learning to test and validate automatically as integration software is generated.

•Developing and exporting conformant data  models with guided modeling.

•Assessing key model health indicators during  model design with analytical reporting.

•Producing diagram-based design artifacts  during collaborative planning.

•Performing model versioning and trace not only changes but the impact of those changes.

•Producing text or diagram-based model and  interface engineering artifacts.

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  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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DAY

1

•Fundamental concepts, principles, and terminology of data integration.

•Common methods of data integration.

•Data integration techniques and technologies.

•Roles, purpose, and variations of data integration.

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DAY

2

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

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  • An overview of PHENOM.

  • How to import a data model.

  • How to add to new and existing data models and how to merge models.

  • How to browse data models.

  • Using data model validation tools and what the results mean.

  • In-context model browsing, finding matches in other interfaces, and finding usages of attributes.

  • Getting started with model health checks.

       Data Architecture, Integration,                                                                      Training 

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DAY

2

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

Northern Lights_edited_edited_edited_edi
  • An introduction to data  architecture model structure.

  • The difference between conceptual, logical, and platform data models.

  • Data modeling best practices.

  • Patterns in data modeling.

  • Terminology related to different model components.

  • How to use data models for documenting interfaces.

  • Data model validity.

Northern Lights_edited_edited_edited_edited_edited.jpg
  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

Northern Lights_edited_edited_edited_edi

DAY

1

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

Northern Lights_edited_edited_edited_edited_edited.jpg
  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

Northern Lights_edited_edited_edited_edi

DAY

3

•Fundamental concepts, principles, and terminology of data integration.

•Common methods of data integration.

•Data integration techniques and technologies.

•Roles, purpose, and variations of data integration.

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DAY

4

  • Fundamental concepts, principles, and terminology of Data Architecture.

  • The difference between Syntax & Semantics and why it matters.

  • Fundamental concepts, principles, and terminology of Data Modeling.

  • The role that data models play in data architecture.

  • How to use a data model to capture syntax & semantics.

  • Why and how to construct a Data Model.

Northern Lights_edited_edited_edited_edi
  • An overview of PHENOM & CinC.

  • How to import a data model.

  • How to add to new and existing data models and how to merge models.

  • How to browse data models.

  • Using data model validation tools and what the results mean.

  • In-context model browsing, finding matches in other interfaces, and finding usages of attributes.

  • Getting started with model health checks.