Structured Data - Data that is highly organized in tables with rows and columns; easy to search and analyze (e.g., spreadsheets, SQL databases)., Semi-Structured Data - Data that has some structure but doesn't fit into strict tables; uses tags or markers (e.g., JSON, XML files)., Unstructured Data - Data without a predefined format; hard to organize and analyze (e.g., videos, images, emails)., Relational Databases - A type of database that uses structured tables with defined relationships and schemas (SQL-based)., Schema - The blueprint or structure of a database that defines how data is organized (e.g., table names, types of fields)., Tables - A collection of related data organized into rows and columns in a relational database., Rows/Records - Horizontal entries in a table, each representing one record or data item., Fields/Columns - Vertical columns in a table that define data attributes or fields (e.g., name, date, ID)., Primary Key - A field that uniquely identifies each record in a table., Foreign Key - A field in one table that links to the primary key in another table, creating a relationship., Constraints - Rules that enforce data integrity (e.g., unique, not null, foreign key restrictions)., Non-Relational Databases - A database that doesn't use tables and structured schemas; often more flexible and scalable., Key/Value Databases - A type of non-relational database that stores data in simple key-value pairs (e.g., Redis)., Document Databases - A non-relational database that stores data as documents (usually in JSON/BSON format) (e.g., MongoDB).,

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