Master Data Analyst Interview Questions UK: 8 Real Questions and What Interviewers Want

Applying for a Master Data Analyst job in the UK? Here is what you are likely to be asked. These questions come from our Master Data Analyst question bank of 12 questions, written for UK employers at mid-level level.

Eight Master Data Analyst interview questions, and what the interviewer is thinking

1. How do match rules and survivorship rules work when creating a golden record, and how do you set match thresholds?

Why they ask: Matching and survivorship are the heart of master data work and need both technical and business judgement.

2. What controls would you put around creating and changing vendor master data to reduce errors and fraud?

Why they ask: Vendor data is a prime target for payment fraud, and finance teams expect master data staff to guard it.

3. What does a typical day as a Master Data Analyst involve?

Why they ask: They want to confirm you understand the combination of stewardship, quality and process work.

4. How do you manage hierarchies and relationships in master data, such as parent and child customers or product categories?

Why they ask: Hierarchies are essential for reporting and credit control, and they are easy to get wrong.

5. What standards and attributes matter for product or material master data, and how do you keep classification consistent?

Why they ask: Product data quality affects procurement, logistics and e-commerce, and each area needs standards.

6. Which measures would you use to track master data quality and the performance of the master data process?

Why they ask: Measuring improvement shows you can manage quality and justify the function.

7. You receive an email apparently from a supplier asking you to change their bank details urgently. What do you do?

Why they ask: Payment redirection fraud is widespread, so they test your instinct to verify.

8. Tell me about a time you cleansed and migrated master data into a new system.

Why they ask: Migrations expose the real quality of master data, so they want evidence of method and rigour.

A sample answer to question 1

How do match rules and survivorship rules work when creating a golden record, and how do you set match thresholds?

Match rules decide which records refer to the same real-world entity. Deterministic rules need exact agreement on a reliable identifier, such as company number or VAT number. Probabilistic or fuzzy rules score similarity across fields like name, address and postcode, using techniques such as Levenshtein distance or phonetic matching, and produce a confidence score. I set two thresholds: above the upper one records are merged automatically, between the two they go to a data steward for review, and below the lower one they're left separate. The thresholds come from testing on a sample reviewed by the business, since too loose creates false merges and too tight leaves duplicates. Survivorship rules then decide which value wins in the golden record, for example most recent, most trusted source, most complete or a combination by attribute, such as finance system for bank details and CRM for contact names. I'd document the rules, retain the source values for traceability, and review match results regularly as the data changes.

Common mistake to avoid: Setting thresholds without testing; Discarding source values after merging

Want the rest?

Full model answers, key points and common mistakes for all 12 questions are on the Master Data Analyst interview questions page. The first five are free, no sign-up needed.