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List of notes for this specialization + Lecture notes & Repository & Quizzes + Home page on Coursera. Read this note alongside the lecture notes—some points aren't mentioned here as they're already covered in the lecture notes.

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Refrences

• AWS Well-Architected Framework.
  • Documentation
  • AWS Well-Architected Labs
• Jay Kreps, “Questioning the Lambda Architecture,” O’Reilly Radar, July 2, 2014.
• “A Brief Introduction to Two Data Processing Architectures — Lambda and Kappa for Big Data” by Iman Samizadeh
• An article about Amazon's API Mandate

Data Architecture

Overview

• This week, we dive deeper into what it means to build a good data architecture.
• How Data Architecture fits within Enterprise Architecture (entire org)
• Specific architecture examples
• Choosing technologies: how to translate from stakeholder needs to technology choices.
• Guiding architectural principles to think like an arthictect
• Lab to learn trade-off evaluation between: cost, performance, scalability, security
• Learn about AWS Well-Architected Framework.

What is Data Architecture?

• Enterprise Architecture: the design of systems to support change in an enterprise, achieved by flexible and reversible decisions reached through a careful evaluation of trade-offs

  

• Data Architecture: the design of systems to support the evolving data needs of an enterprise, achieved by flexible and reversible decisions reached through a careful evaluation of trade-offs.

• One-way and Two-way Decisions:

  • One-way: A decision that is almost impossible to reverse

  • Two-way: An easily reversible decision. Eg: S3 Object Storage Classes

    

• Can convert one-way to multiple smaller two-way decisions.