Fact tables in a star schema contain transactional data that can be analyzed, often including measures and foreign keys to dimension tables.

Fact tables in a star schema represent transactional data, containing measurable, quantitative data for analysis.

ETL stands for Extract, Transform, Load, which is the process of moving data from source systems into a data warehouse.

Data latency refers to the time delay between when data is generated and when it becomes available for analysis in a data warehouse.

Dimension tables contain descriptive attributes that provide context to the facts stored in the fact tables.

A star schema is a type of database design that consists of a central fact table surrounded by dimension tables, facilitating easier data retrieval.

Indexing improves query performance by allowing the database to find data more quickly, which is crucial in a data warehouse environment.

Data normalization aims to reduce data redundancy and improve data integrity, although it is less common in data warehousing compared to operational databases.

OLAP (Online Analytical Processing) is used in data warehousing to support complex queries and data analysis.

A data warehouse is designed to support business intelligence activities by consolidating data from various sources for analysis.

Normalization aims to reduce data redundancy and improve data integrity, although data warehouses often use denormalization for performance.

ETL stands for Extract, Transform, Load, which is the process of moving data from source systems into a data warehouse.

Dimension tables provide context to the fact data, allowing users to analyze the facts in relation to various attributes.

Indexing in a data warehouse is used to speed up query performance by allowing faster data retrieval.

Optimistic locking is often used in data warehousing environments where read operations are more frequent than write operations.

A data mart is a smaller, more focused version of a data warehouse, designed to serve the needs of a specific business area.

A data mart is a subset of a data warehouse, often focused on a specific business line or team.

ETL stands for Extract, Transform, Load, which is the process of moving data from source systems into a data warehouse.

Data warehouses are characterized by their ability to store historical data for analysis, unlike operational databases which focus on current transactions.

Data replication is a common method used to ensure data consistency across different systems in a data warehouse.

Data warehousing focuses on analytical processing rather than transaction speed, which is a characteristic of operational databases.

Multi-dimensional architecture is not a recognized type of data warehouse architecture; the common types are single-tier, two-tier, and three-tier.

Data warehouses are not typically used for real-time transaction processing, which is better suited for operational databases.