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  2. Fact tables contain quantitative data that can be aggregated, while dimension tables contain descriptive data about the dimensions of your data1234. Here are the key differences:
    • Fact tables: Contain primary keys of referenced dimension tables and quantitative metrics (e.g., sales figures).
    • Dimension tables: Hold descriptive information related to the fields in the fact table's records.
    Learn more:
    The main difference between fact and dimension tables is that a fact table contains quantitative data that can be aggregated, while a dimension table contains descriptive data about the dimensions of your data. For example, a fact table may contain sales figures, while a dimension table may contain information about the products sold.
    zebrabi.com/guide/how-to-create-fact-and-dimensi…
    Fact tables store the numbers we’re interested in, and dimension tables contain the categories, or dimensions, that determine how the data is aggregated within our queries. Facts represent the events that occur in the specific business process we’re recording. Each row in a fact table holds the data measured for that event.
    www.interviewquery.com/learning-paths/data-engin…
    Fact table: A fact table contains the primary keys of the referenced dimension tables along with some quantitative metrics. Examples of a fact table include customer orders or time-series financial data. Dimension table: A dimension table holds the descriptive information for the related fields that are in the fact table’s records.
    builtin.com/articles/fact-table-vs-dimension-table
    Fact Table: It contains all the primary keys of the dimension and associated facts or measures (is a property on which calculations can be made) like quantity sold, amount sold and average sales. Dimension Tables: Dimension tables provides descriptive information for all the measurements recorded in fact table.
    stackoverflow.com/questions/20036905/difference-…
     
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