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 handson training that can be conducted inperson 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 Training
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.
DAY
2

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.

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
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.

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
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.

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
Data Architecture & Integration
Training
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.

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.
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.
•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.
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
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.
•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 diagrambased design artifacts during collaborative planning.
•Performing model versioning and trace not only changes but the impact of those changes.
•Producing text or diagrambased model and interface engineering artifacts.

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.
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.
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.

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.

Incontext model browsing, finding matches in other interfaces, and finding usages of attributes.

Getting started with model health checks.
Data Architecture, Integration, Training
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.

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.

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.
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.
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.
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.

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.

Incontext model browsing, finding matches in other interfaces, and finding usages of attributes.

Getting started with model health checks.