COG220 Access Data Model Overview, COG220 ACCESS DATA MODEL EXAM 2026 NEWEST
ACTUAL EXAM COMPLETE ACCURATE EXAM QUESTIONS WITH DETAILED VERIFIED ANSWERS
(100% CORRECT ANSWERS) /ALREADY GRADED A+ 2026
1. What does a fact table primarily contain?
Answer: Numeric measures and foreign keys
Rationale: Fact tables store metrics like charges, payments, or units, linked to dimensions.
2. Dimension tables are used to:
Answer: Provide descriptive context for measures
Rationale: Dimensions contain attributes such as patient demographics, service type, or payer
info.
3. Surrogate keys are used because:
Answer: They uniquely identify rows without relying on business logic
Rationale: Allows history tracking and avoids duplication issues.
4. In a star schema, fact tables connect to dimensions via:
Answer: Foreign keys
Rationale: Establishes relational mapping for querying.
5. Grain of a fact table defines:
Answer: The level of detail of each record
Rationale: Determines whether one row = one service line, one claim, or one patient encounter.
6. Slowly Changing Dimension (SCD) Type 2:
Answer: Preserves historical changes by creating new rows
Rationale: Tracks evolution of attributes over time.
7. Factless fact tables are used to:
Answer: Track events without numeric metrics
Rationale: Useful for documenting occurrences like service attendance.
8. Conformed dimensions:
Answer: Can be shared across multiple fact tables
Rationale: Ensures consistent reporting across the model.
9. Degenerate dimensions are:
Answer: Attributes stored in the fact table rather than a separate table
Rationale: Often used for transactional codes with no descriptive attributes.
10. Referential integrity ensures:
Answer: Every foreign key in a fact table has a matching primary key in a dimension
Rationale: Maintains valid relationships for accurate queries.
practice exam 2026
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11–20: Revenue Facts & Measures
11. Charge amount in a fact table is classified as:
Answer: Measure
Rationale: Numeric value representing revenue.
12. Payment adjustments are captured in:
Answer: Adjustment fact table
Rationale: Separates original charges from corrections for analytics.
13. Refunds should be represented as:
Answer: Negative values in the fact table
Rationale: Corrects revenue totals without losing historical data.
14. Claim line fact table links to which dimension?
Answer: Service line dimension
Rationale: Provides descriptive details of the service billed.
15. Claim header table contains:
Answer: One record per insurance claim
Rationale: Aggregates claim-level information separate from line items.
16. A patient dimension typically includes:
Answer: Name, MRN, demographics
Rationale: Supports patient-centric reporting.
17. A payer dimension stores:
Answer: Insurance plan type and identifier
Rationale: Enables payer-level revenue analysis.
18. Billing period metrics should join to:
Answer: Date dimension
Rationale: Allows time-based aggregation and trend analysis.
19. Net revenue is calculated using:
Answer: Charge minus adjustments and refunds
Rationale: Represents actual collected revenue.
20. Quantity of services performed is stored in:
Answer: Fact table as a measure
Rationale: Tracks volume for analysis.
practice exam 2026
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21–30: ETL & Data Quality
21. ETL stands for:
Answer: Extract, Transform, Load
Rationale: Process for populating the data warehouse.
22. Staging tables are used to:
Answer: Temporarily hold raw data before transformation
Rationale: Ensures data quality before loading.
23. Data validation in ETL ensures:
Answer: Data meets business rules
Rationale: Prevents incorrect or incomplete data from entering warehouse.
24. Data lineage documents:
Answer: Origin and transformations of each data element
Rationale: Supports auditing and troubleshooting.
25. Incremental load must handle:
Answer: Inserts, updates, deletes
Rationale: Keeps warehouse in sync with source systems.
26. Key ETL data quality metric:
Answer: Completeness
Rationale: Missing values affect reporting accuracy.
27. Surrogate keys assist in handling:
Answer: Slowly changing dimensions
Rationale: Allow multiple versions of a record over time.
28. Data governance defines:
Answer: Policies for management, use, and security of data
Rationale: Ensures consistent, compliant data handling.
29. Transformation rules in ETL:
Answer: Convert raw data into warehouse-ready formats
Rationale: Ensures consistency and correctness.
30. Auditing ETL outputs includes checking:
Answer: Referential integrity and measure correctness
Rationale: Confirms model reliability for reporting.
practice exam 2026
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31–40: Schema & Joins
31. Star schema is optimized for:
Answer: Query performance
Rationale: Denormalized dimensions simplify joins.
32. Snowflake schema differs because:
Answer: Dimensions are normalized
Rationale: Reduces redundancy but can slow queries.
33. Inner join returns:
Answer: Only matching records in both tables
Rationale: Filters out non-matching rows.
34. Left outer join returns:
Answer: All left table records and matching right table records
Rationale: Ensures all primary table data is preserved.
35. Bridge tables resolve:
Answer: Many-to-many relationships
Rationale: Enables accurate aggregation and reporting.
36. Degenerate dimension example:
Answer: Claim number in fact table
Rationale: Transaction code with no descriptive attributes stored in fact table.
37. Fact table primary key is:
Answer: Surrogate key
Rationale: Ensures uniqueness and supports SCD tracking.
38. Slowly Changing Dimension Type 1:
Answer: Overwrites old data
Rationale: No historical tracking is preserved.
39. Fact table granularity determines:
Answer: Level of detail of records
Rationale: Critical for defining analytics scope.
40. Conformed dimensions ensure:
Answer: Consistency across different fact tables
Rationale: Avoids conflicting metrics.
practice exam 2026