Data 360 Consultant Data Ingestion And Modeling Practice Question
An organization is ingesting high-volume transaction data via the Ingestion API. During testing, they notice that duplicate transaction IDs are being ingested as separate records into the DSO. What mechanism ensures idempotency or prevents unwanted duplicates in Data Cloud ingestion?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Ensure that a unique primary key is defined in the Ingestion API schema so Data Cloud can upsert records correctly.
Data Cloud ingestion relies on primary keys defined in the schema. If incoming records share the same primary key, Data Cloud performs an upsert based on the primary key to prevent duplicate records in the DSO.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Write an Apex deduplication trigger before sending payloads to the API.
Why it's wrong here
Apex cannot be used in external API client applications or Data Cloud ingestion pipelines.
- ✓
Ensure that a unique primary key is defined in the Ingestion API schema so Data Cloud can upsert records correctly.
Why this is correct
Defining a primary key ensures Data Cloud upserts records instead of creating duplicate entries for the same key.
- ✗
Enable Identity Resolution match rules specifically for transaction IDs.
Why it's wrong here
Identity resolution is designed for profile objects (Individuals), not transactional fact tables.
- ✗
Set the data stream refresh frequency to real-time batching.
Why it's wrong here
Refresh frequency does not control API upsert behavior.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Salesforce exam blueprint
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