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.
Data Architecture Training
DAY 1
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Fundamental concepts, principles, and terminology of Data Architecture.
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The difference between Syntax & Semantics and why it matters.
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Fundamental concepts, principles, and terminology of Data Modeling.
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The role that data models play in data architecture.
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How to use a data model to capture syntax & semantics.
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Why and how to construct a Data Model.
Data Architecture & Integration Training
DAY 1
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Fundamental concepts, principles, and terminology of Data Architecture.
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The difference between Syntax & Semantics and why it matters.
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Fundamental concepts, principles, and terminology of Data Modeling.
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The role that data models play in data architecture.
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How to use a data model to capture syntax & semantics.
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Why and how to construct a Data Model.
Data Architecture, Integration, PHENOM & CinC Training
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Fundamental concepts, principles, and terminology of Data Architecture.
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The difference between Syntax & Semantics and why it matters.
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Fundamental concepts, principles, and terminology of Data Modeling.
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The role that data models play in data architecture.
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How to use a data model to capture syntax & semantics.
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Why and how to construct a Data Model.
DAY 1
Training
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Overview of the FACE Architecture, Portability and Interoperability as Key Drivers
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FACE Software Architecture & Data Architecture Concepts and design patterns
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Introduction of FACE Software Segments
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Implementing a FACE Unit of Conformance (UoC)
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API Overview and Relationship to FACE Data Modeling
DAY 1
DAY 1
Integration, PHENOM & CinC Training
•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.
