Design Principles for Scalable Data Systems Architecture

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Description

This exam evaluates fundamental design principles governing scalable data systems architecture crucial for efficient handling of increasing data volumes.

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Exam Details

Duration: 50 minutes

Prerequisites: Introduction To Software Architecture, Database Design Principles, Cloud Computing Fundamentals

Key Topics

  • Scalable Data Architecture
  • Horizontal Scaling
  • Vertical Scaling
  • Cloud Infrastructure
  • Design Methodologies

Learning Outcomes

  • Articulate Scalable Data Architecture Principles
  • Analyze Scaling Methods
  • Evaluate Cloud Infrastructure Roles
  • Identify Best Practices in Design

Full Description

This exam centers on the design principles that govern scalable data systems architecture. Candidates will discuss methodologies that enable systems to efficiently handle increasing data volumes.

Scalable architecture is critical for organizations aiming to maintain performance and reliability as data growth occurs. Understanding design principles ensures that systems remain responsive and cost-effective under varying loads.

The evaluation will focus on candidates' ability to articulate the fundamental concepts of scalability, including horizontal vs. vertical scaling and the role of cloud infrastructure.

Moreover, candidates will have the opportunity to analyze case studies of data architectures to identify common design pitfalls and best practices in system scalability.

Sample Questions

  • What are the advantages of horizontal scaling compared to vertical scaling?
  • How does cloud infrastructure support scalable data systems?

Field: Engineering and Technology

Subfield: Software Engineering

Specialization: Data Engineering

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