"Compromise occurs when each of the participants is equally dissatisfied with the results."
Richard Branton




INTEGRATED DATA ARCHITECTURE
 
 
While it is often desirable to produce the “illusion” of a single enterprise-wide database, it is typically more practical to split the data into multiple datastores, each utilizing the most appropriate technology.
Integrated Data Architecture involves determining (1) What portions of the Data Structure should be implemented together vs. separately and (2) What technologies should be used to implement each portion of the data structure.

Today’s data professional is charged with developing a practical data architecture which meets multiple (and at times conflicting) demands including the need for effective data sharing, distribution and security as well as meeting the ever changing technology environment.

Course Outcomes:
Students of Advanced Strategies’ Integrated Data Architecture Course will return to work and be able to:

  1. Explain the common motivations and costs/benefits for preserving a single database image, utilizing separate datastores, and using multiple technologies.
  2. Follow a strategy for the architectural design of datastores.
  3. Make key decisions in determining and developing an optimal data architecture.

Course Outline:
What is Architecture and Data Architecture?
  • Architectual Design Process
  • Data Architectual Design Process
  • What is an Architecture?
  • Types of Data Architecture (i.e. the Cube)
  • How Application Get Built/The Framework
Architectural Design Inputs
  • Business Intentions
  • Focus Statement
  • Sub-Disciplines of Analysis
  • Search for Conditions and Opportunities
  • Sub-Disciplines of Design (Emphasis on Architectural Design)
  • Overview of the Architectural Design Process
Architectural Design Considerations
  • Architectural Design Steps
  • Conceptual Architecture Exercises
  • Appendix

Who Should Attend:
This course is targeted for Data Modelers, Database Administrators, Systems and Business Analysts, and other Data Professionals.

Non-Course Prerequisites:
Prior to the course, students should be able to read and be familiar with logical data models, physical data models and process models.

Course Duration:
Three Days

Class Availability: Request It Now!

Materials Provided:
Student Workbook

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