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CDW110V CABOODLE DATA MODEL FUNDAMENTALS EXAM 2026 – 200 REAL QUESTIONS & VERIFIED ANSWERS | EPIC CABOODLE TEST BANK (GRADED A+)

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Ace your CDW110V Caboodle Data Model Fundamentals Exam with confidence! This brand-new 2026 test bank features 200 actual exam questions with correct answers and detailed rationales — covering everything you need to master Epic's Caboodle data warehouse: star schema architecture (denormalized dimensions, fact tables, grains), conformed & role-playing dimensions, slowly changing dimensions (SCD Type 2), junk dimensions, degenerate dimensions, bridge tables, factless fact tables, surrogate vs. natural keys, ETL processes (incremental loads, watermarks, staging, audits, data lineage, CAB_METADATA, error logging), fact tables (FACT_ENCOUNTER, FACT_CHARGE, FACT_RESULT, FACT_ORDER, FACT_MAR, FACT_PATIENT_DAILY, FACT_SURGICAL_CASE, FACT_CLAIM, FACT_ED_TRACKING, FACT_PAYMENT, FACT_READMISSION, FACT_VACCINATION, FACT_INFECTION, FACT_MICROBIOLOGY), dimension tables (DIM_PATIENT, DIM_PROVIDER, DIM_DATE, DIM_DIAGNOSIS, DIM_DRG, DIM_LOCATION, DIM_FINANCIAL_CLASS, DIM_PAYER, DIM_ENCOUNTER_TYPE, DIM_CODE_VALUE, DIM_MODIFIER, DIM_MEDICATION, DIM_VACCINE, DIM_SPECIALTY, DIM_CARE_TEAM), data governance (retention policies, data quality rules, orphaned facts, late-arriving dimensions, test patient flags), and advanced query patterns (readmission rate, length of stay, case mix index, payer mix, ED wait times, OR utilization, rolling 12-month sums, gap in care, median LOS, surgical site infections, HAC flags, month-to-date revenue, year-over-year change). Every answer is verified and explained to help you master Epic Caboodle for certification. Perfect for Cogito analysts, reporting professionals, BI developers, and anyone working with Epic Caboodle. No fluff — just what you need to pass!

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CDW110V CABOODLE DATA MODEL FUNDAMENTALS
EXAM NEWEST 2026 ACTUAL EXAM TEST BANK|
COMPLETE 300 REAL EXAM QUESTIONS AND
CORRECT VERIFIED ANSWERS/ ALREADY GRADED A+
(BRAND NEW!!)
1. Caboodle is built on which database architecture pattern?
A) Snowflake schema
B) Star schema with denormalized dimensions
C) Third normal form (3NF)
D) Data vault
Correct Answer: B
Rationale: Caboodle uses a star schema optimized for analytics,
with denormalized dimension tables to reduce joins and improve
query performance. Snowflake schemas are normalized further,
which Caboodle avoids for speed.

2. Which Caboodle table typically contains measures like “total
charge amount”?
A) Dimension table
B) Fact table
C) Bridge table
D) Lookup table
1

,Correct Answer: B
Rationale: Fact tables store measurable, numeric facts (e.g.,
charges, quantities, lengths of stay) and foreign keys to
dimension tables for context.

3. What is the primary purpose of a date dimension in
Caboodle?
A) Store patient birthdays
B) Enable time-based trend analysis
C) Replace all datetime fields in facts
D) Validate date formats
Correct Answer: B
Rationale: A date dimension allows filtering, grouping, and
trending by attributes like fiscal period, day of week, holiday
flags, avoiding complex date functions in every query.

4. Caboodle’s ETL process loads data from:
A) Clarity database only
B) Clarity and non-Epic sources via custom mappings
C) Real-time API streams
D) Flat files only
Correct Answer: B
Rationale: Caboodle primarily sources from Clarity but supports

2

,other sources through Caboodle Extensions (e.g., legacy systems,
external labs).

5. Which column type is most commonly the primary key of a
dimension table?
A) Surrogate key (integer)
B) Natural key (string)
C) Composite key
D) Business key only
Correct Answer: A
Rationale: Surrogate keys (e.g., PATIENT_ID, ENCNTR_ID) are
system-generated integers used for fast joins and tracking
historical changes, independent of source system natural keys.

6. In a star schema, a “bridge table” is used to:
A) Store aggregated facts
B) Handle many-to-many relationships between dimensions and
facts
C) Replace a date dimension
D) Store ETL logs
Correct Answer: B
Rationale: Bridge tables resolve many-to-many relationships



3

, (e.g., multiple diagnoses per encounter, multiple providers per
procedure) by linking fact keys to dimension keys.

7. Which fact table would you query to analyze length of stay?
A) FACT_ENCOUNTER
B) FACT_PATIENT
C) FACT_CHARGE
D) FACT_DIAGNOSIS
Correct Answer: A
Rationale: FACT_ENCOUNTER contains encounter-level metrics
like LOS, admission and discharge timestamps, and expected
LOS (ELOS).

8. A “slowly changing dimension” (SCD) in Caboodle typically
uses:
A) Type 1 overwrite
B) Type 2 with effective date ranges
C) Type 3 with previous value column
D) No history tracking
Correct Answer: B
Rationale: Caboodle tracks historical changes using SCD Type 2
(e.g., PATIENT_DIM with EFFECTIVE_DATE, EXPIRATION_DATE,



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