Top 11
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Updated weekly · Last refresh Aug 30

University of Oklahoma Data Analyst Interview Questions

The questions to prepare for a University of Oklahoma Data Analyst interview. Questions from real interview reports rank first. Updated weekly.

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1
SQL & Data ManipulationStart here. 5 questions + 3 drills · ~70 min
Validating Data Before ReportingEasy

Explain how to validate SQL data before reporting, including null checks, duplicates, outliers, and aggregation reconciliation.

JoinsData WranglingQualityUniversity of Oklahoma
Handling Missing and Dirty SQL DataMedium

Explain how to profile, clean, and standardize missing or dirty data before analysis.

Data WranglingCase WhenQualityUniversity of Oklahoma
Describing SQL Data Extraction WorkEasy

Explain how you used PostgreSQL SQL queries and aggregations to extract analysis-ready data from a single dataset.

SQL & Data ManipulationData WranglingAggregationsUniversity of Oklahoma
Cleaning a Messy DatasetEasy

Tests data quality practices, validation, and handling missing or inconsistent values.

Data WranglingETLQualityUniversity of Oklahoma
Visualizing for ExecutivesMedium

Assesses how you choose visuals and communicate insights clearly for senior decision-makers.

presentation skillsdata visualizationstakeholder communicationUniversity of Oklahoma
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Resolve Conflicting Customer AttributesMedium
Practice
Practice drill

Use joins, CTEs, and row ranking to resolve conflicting customer profile values across ACME House systems.

JoinsData WranglingQualityRamsey SolutionsACME House
Clean Inconsistent Expense EntriesHard
Practice
Practice drill

Clean inconsistent expense records with CTEs, joins, CASE logic, and aggregation to summarize valid spend by department.

Data WranglingAggregationsQualityUniversity of Colorado Denver

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2
Behavioral & Leadership6 questions · ~48 min
Explaining Analysis to Non-Technical StakeholdersEasy

Tests communication of complex data to non-technical stakeholders, including clarity, stakeholder management, and actionable storytelling.

Influence Without AuthorityStakeholder ManagementCommunicationUniversity of Oklahoma
Persuading Stakeholders With DataMedium

Tests influence without authority by assessing how you use data, communication, and stakeholder management to drive adoption of a recommendation.

Influence Without AuthorityStakeholder ManagementCommunicationUniversity of Oklahoma
Prioritizing Competing Data RequestsMedium

Tests prioritization under pressure in a data engineering context, including stakeholder management, trade-off decisions, and ownership of outcomes.

Decision MakingStakeholder ManagementPrioritizationUniversity of Oklahoma
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The finish line: interview-readyComplete all 11 questions plus 3 hands-on drills to finish this plan.