FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -Aggregations are also built from the fact table by changing the granularity on specific dimensions and aggregating data up along these dimensions during the ETL process.

Detailed explanation-2: -In dimensional modeling, granularity refers to the level of detail stored in a table. For example, a dimension such as Date (with Year and Quarter hierarchies) has a granularity at the quarter level but does not have information for individual days or months.

Detailed explanation-3: -A fact table stores quantitative information for analysis and is often denormalized. A fact table works with dimension tables. A fact table holds the data to be analyzed, and a dimension table stores data about the ways in which the data in the fact table can be analyzed.

Detailed explanation-4: -A fact table or a fact entity is a table or entity in a star or snowflake schema that stores measures that measure the business, such as sales, cost of goods, or profit. Fact tables and entities aggregate measures, or the numerical data of a business.

Detailed explanation-5: -A fact in data warehousing describes quantitative transactional data like measurements, metrics, or the values ready for analysis. These include header numbers, order numbers, ticket numbers, transaction numbers, transaction currency, etc. The amount sold is a fact measure or a key performance indicator (KPI).