Exam DP-900 topic 1 question 285 discussion

- Fact Table is the correct answer because it is designed to store and aggregate numeric values. The rows in the fact table represent individual transactions or events and are uniquely identified by a combination of foreign keys and sometimes a unique identifier (such as a transaction ID). - These numeric values (facts) are the ones aggregated to provide insights, such as total sales, average order value, or total profit, making the fact table central to quantitative analysis in an analytical data model.

Trick question

This feels like a trick question, but with how it's worded I think the answer is B. dimension. Fact tables typically contain quantitative data. Dimensions typically contain qualitative data. The dimensions are often used to slice or group the quantitative data from the fact tables, though. For example, you could use the Customer dimension to aggregate sales amounts from the Sales fact table by Customer. This is what makes me think Dimension is actually the right answer for this question. The "numeric values" are the misleading part.

Correct Option C: Fact tables contains all foreign keys from Dimensions. That is to make sure of data integrity in star schema.

it's B. The question is which type of table contains entities where each entity is represented by a row with a unique key value? [that are used to aggregate numeric values] --> this is on purpose noise

C - Fact Table

The answer is without a doubt => C - Fact Table Typically dimension tables don't store numeric values and are not aggregated. They are used to aggregate information in the fact tables BY DIMENSION

Coined another way: What type of table contains entities used to aggregate numeric values, where each entity is represented by a row with a unique key value, in an Analytic Data Model? ChatGPT: In an Analytic Data Model, the type of table that contains entities used to aggregate numeric values, with each entity represented by a row with a unique key value, is typically referred to as a "fact table." A fact table is a central component of a multidimensional data model such as a star schema or snowflake schema. It contains quantitative data (facts) about a business process or activity and serves as the primary source for aggregating and analyzing numerical measures. Each row in the fact table represents a specific event or transaction, and the fact table usually includes foreign keys that reference dimension tables, which provide context and additional descriptive attributes for the facts. Fact tables play a crucial role in supporting analytical queries and reporting in data warehousing and business intelligence environments by enabling the aggregation of data across different dimensions, such as time, geography, product, or customer.

A Fact table typically stores quantitative data, often referred to as measures or metrics, and contains foreign keys that reference related Dimension tables. Fact tables are central to a star schema or snowflake schema design, which are common schema designs used in data warehousing and OLAP environments for supporting analytical querying and reporting.

Dimension

B - Dimension Table

INCORRECT. It's B, Dimension. Here from ChatGPT: In an analytical data model, the type of table that contains entities used to aggregate numeric values, with each entity represented by a row having a unique key value, is typically referred to as a "dimension table."