Data Structures

Structured

Organized in a predefined model; often uses tables, rows, columns, and supports SQL querying. (E.G. Relational databases, spreadsheets.)

Table

A structured data arrangement in a relational database that organizes information into rows and columns, where column equals attribute and row equals single record.

Fact Table

Metrics; central table in a data warehouse storing quantitative, measurable data. Linked to dimension tables via foreign keys, contains facts or metrics. Used for sales totals, units sold, revenue, profit.

Dimensional Table

Descriptive context; table that provides context for facts. Fact tables linked via primary keys. Customer info, product category, region, date.

Bridge Table

Resolves many-to-many relationships between fact and dimension tables; foreign keys and sometimes attributes to describe the relationship. Connects multiple dimension tables to a fact table, often includes surrogate keys. Used for linking students to multiple courses and employees to multiple projects.

Schema

A predefined structure and rules that determine how data is organized, stored, and validated within a database or dataset.

Semi-structured

Has tags/markers but not fixed schema; flexible formats (E.G. JSON, XML, NoSQL documents).

Nested structures

Hierarchical data formats in which fields contain additional sub-fields or objects, allowing multilevel organization of semi-structured data.

Unstructured

No formal model; harder to query and analyze directly. Images, audio, video, text documents.