Dimensional Modeling

Correct Answer: Creating a bridge table with factless facts to link multiple dimensions

Creating a bridge table with factless facts is the optimal solution for handling many-to-many relationships in dimensional modeling. Key reasons why this is the best approach: 1. Bridge tables provide a clean way to represent complex relationships 2. Factless facts maintain referential integrity 3. This approach preserves the analytical capabilities of the model 4. It follows dimensional modeling best practices Why other options are less suitable: - Using multiple join paths through intermediate tables adds unnecessary complexity and can impact query performance - Merging all related dimensions into a single denormalized table creates data redundancy and maintenance issues - Adding surrogate keys alone doesn't solve the many-to-many relationship challenge and could lead to data integrity problems The bridge table approach maintains data integrity while providing efficient query performance and clear relationship mapping.

Correct Answer: Use consistent surrogate key assignments and maintain a central key management system

In dimensional modeling, using consistent surrogate key assignments with a central key management system is the optimal approach because: Strengths of the correct answer: - Ensures data consistency across the entire data warehouse - Simplifies maintenance and updates - Reduces the risk of data mismatches - Enables efficient querying across multiple fact tables - Supports proper dimensional conformity Why other approaches fall short: Generating unique surrogate keys for each fact table creates unnecessary complexity and requires additional storage and processing for mapping tables. Implementing separate key sequences requires complex ETL reconciliation processes and can lead to data inconsistencies. Allowing each fact table to maintain its own key generation breaks dimensional conformity and makes it difficult to maintain data integrity across the warehouse. The central key management approach is considered a best practice in dimensional modeling as it supports scalability, maintainability, and data consistency while reducing complexity in the overall data warehouse architecture.

Correct Answer: Contains quantitative metrics and foreign keys to dimension tables

A fact table in dimensional modeling is primarily characterized by having quantitative metrics (measurable values) and foreign keys that connect to dimension tables. This is a fundamental concept in star schema design. The correct answer accurately describes the two main components of a fact table: 1. Quantitative metrics (like sales amount, quantity, etc.) 2. Foreign keys that link to dimension tables The other options are incorrect because: - The description of containing descriptive attributes and business hierarchies actually describes dimension tables, not fact tables - Storing slowly changing dimensions is a characteristic of dimension tables, not fact tables - Maintaining historical changes to dimension attributes is also a dimension table concept, not a fact table function Fact tables are typically the largest tables in a data warehouse and contain the numerical measurements of the business process being analyzed.