Structured Data

Structured and Unstructured Data

Definition

Structured data refers to information organized in predefined formats such as tables, databases, or spreadsheets. It contrasts with unstructured data like free text or images.

Purpose

The purpose is to enable efficient storage, retrieval, and analysis of information. Structured data underpins data science and AI systems.

Importance

  • Easily searchable and machine-readable.
  • Provides reliable input for supervised learning.
  • Limited in capturing complex real-world variability.
  • Often combined with unstructured data for richer models.

How It Works

  1. Collect data from sensors, transactions, or logs.
  2. Organize into rows and columns with defined schema.
  3. Store in relational or NoSQL databases.
  4. Query using SQL or APIs.
  5. Use as input for analytics or ML models.

Examples (Real World)

  • Banking transactions stored in structured databases.
  • Hospital records in structured EHR formats.
  • E-commerce product catalogs.

References / Further Reading

  • ISO/IEC 11179: Metadata Registries.
  • NIST Big Data Interoperability Framework.
  • Kimball & Ross. The Data Warehouse Toolkit.