The correct answer is to build a customer matching rule that uses multiple attributes (email, phone, name) with a confidence score. This is the right approach because merging data from systems with different identifier schemas requires probabilistic matching, which evaluates the likelihood that records refer to the same entity rather than relying on a single, unreliable key. In this scenario, email is not unique in one system, and phone numbers may be missing or formatted inconsistently, so a deterministic match on one field would fail. On the CompTIA Data+ DA0-001 exam, this tests your understanding of data integration and record linkage techniques, often appearing in questions about deduplication or master data management. A common trap is choosing a simple merge on email alone, forgetting that non-unique identifiers cause false positives. Remember the memory tip: “One field fails, multiple fields prevail”—confidence scores let you weigh evidence across attributes for a unified view.
DA0-001 Mining and Acquiring Data Practice Question
This DA0-001 practice question tests your understanding of mining and acquiring data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
An e-commerce company is merging customer data from three legacy systems. Two systems use email as unique identifier, but one system allows multiple customers per email. The third uses phone number. To create a unified customer view, the analyst should first:
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Build a customer matching rule that uses multiple attributes (email, phone, name) with a confidence score
Option B is correct because merging data from systems with different identifier schemas requires a probabilistic matching approach. Using multiple attributes (email, phone, name) with a confidence score allows the analyst to resolve conflicts where email is not unique and phone numbers may be missing or formatted differently, creating a unified customer view without forcing a single key.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Request the IT team to modify the legacy system
Why it's wrong here
Modifying legacy systems may be costly or impossible.
✓
Build a customer matching rule that uses multiple attributes (email, phone, name) with a confidence score
Why this is correct
Multi-attribute matching handles non-unique identifiers and improves accuracy.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use email as primary key and ignore conflicts
Why it's wrong here
This would lose data for customers sharing an email.
✗
Assign new unique IDs and discard existing identifiers
Why it's wrong here
Discarding existing identifiers prevents linking to source systems.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume a single unique identifier (email) can be forced as a primary key, ignoring the real-world data quality issue of non-unique emails, which the question explicitly states.
Detailed technical explanation
How to think about this question
Probabilistic matching uses algorithms like Fellegi-Sunter or Jaro-Winkler to compare fields and assign weights based on agreement/disagreement patterns. In practice, a confidence score threshold (e.g., 0.85) determines matches, while lower scores may require manual review or fuzzy matching on name and address. This approach is standard in ETL pipelines for customer data integration (CDI) and master data management (MDM) systems.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the DA0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Mining and Acquiring Data — This question tests Mining and Acquiring Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Build a customer matching rule that uses multiple attributes (email, phone, name) with a confidence score — Option B is correct because merging data from systems with different identifier schemas requires a probabilistic matching approach. Using multiple attributes (email, phone, name) with a confidence score allows the analyst to resolve conflicts where email is not unique and phone numbers may be missing or formatted differently, creating a unified customer view without forcing a single key.
What should I do if I get this DA0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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