Data Architecture

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Data architecture is an essential framework that shapes how an organization manages its data.

  • Definition:
    • Data architecture describes how data is collected, stored, processed, and accessed within an organization.

It serves as a blueprint for data flow through storage systems. Think of it as the design and structure that underpins data management.

  • Key Components:
    • Conceptual Data Models:
      • These models provide a big-picture view of the system, including organization, business rules, and relationships.

They help gather initial project requirements.

    • Logical Data Models:
      • These models offer greater detail about concepts and relationships.
      • They specify data attributes (types, lengths) and show entity relationships.
    • Physical Data Models:
      • The most detailed type, defining actual database implementation (tables, indexes, storage).
      • It ensures data integrity and performance considerations.
  • Business-Driven Design:
    • Data architecture aligns with business requirements.
    • Data architects and engineers create models based on these needs.
    • Whether for reporting or data science, it supports business initiatives.
  • Modern Trends:
    • Cloud Platforms: Many modern architectures leverage cloud platforms for data management and processing.
    • Scalability: Cloud scalability enables rapid data processing and storage expansion.
    • Integration: It breaks down data silos, allowing seamless data sharing across domains.

In summary, data architecture is the backbone of effective data strategy, ensuring organized, secure, and accessible information for better decision-making and business operations

Big data landscape1.png