MCQs

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Overall MCQs for Reference

Which dimension assesses whether data accurately reflects the real-world entity?
a. Validity
b. Timeliness
c. Completeness
d. Accuracy
Answer: d. Accuracywayground
What is the main goal of data profiling?
a. To monitor data quality
b. To assess data quality
c. To resolve data issues
d. To discover value frequencies and formats of data
Answer: d. To discover value frequencies and formats of datawayground
What is the purpose of a data quality scorecard?
a. To assess data quality
b. To discover data quality issues
c. To visualize results
d. To monitor and control data quality
Answer: c. To visualize resultswayground
Which role typically leads activities associated with the data quality process?
a. Data Steward
b. Data Quality Analyst
c. Technical Owner
d. Business Owner
Answer: a. Data Stewardwayground
What does completeness in data mean?
a. Data is free from errors
b. All required data is available
c. Data is current
d. Data is relevant
Answer: b. All required data is availablewayground
If data quality is assessed after profiling, what is the next step?
a. Data Profiling
b. Issue Remediation
c. Root Cause Analysis
d. Data Quality Scorecards
Answer: b. Issue Remediationwayground
Which of the following is NOT a dimension of data quality?
a. Accessibility
b. Timeliness
c. Marketing Strategy
d. Consistency
Answer: c. Marketing Strategystudocu
What is data wrangling in data quality assessment?
a. Data deletion
b. Data visualization
c. Data cleaning and transforming
d. Data encryption
Answer: c. Data cleaning and transforminggyansetu
Metadata describes:
a. Data visualization
b. Data analysis
c. Data preservation
d. Information: What? Who? Where? When? How?
Answer: d. Information: What? Who? Where? When? How?studocu
Which type of error directly impacts data quality?
a. Logical errors
b. Typographical errors
c. Measurement errors
d. All of the above
Answer: d. All of the abovehellointern
When do data audits take place in data quality management?
a. At data ingestion
b. Periodically
c. Only after cleaning
d. Never needed
Answer: b. Periodicallyhellointern
Which of the following indicates good quality data?
a. Outliers
b. Accurate classification
c. Good classifier
d. Results of t-test
Answer: b. Accurate classificationstudocu
A high classification accuracy in an analysis is usually a result of:
a. Good quality data
b. Good classifier
c. None of the above
d. Results of t-test
Answer: a. Good quality datastudocu
What is the main impact of poor data quality on a business?
a. Loss of reputation
b. Increased costs
c. Decision errors
d. All of the above
Answer: d. All of the aboveacademy.cognopia
Which approach is most common for measuring data quality?
a. Manual inspection
b. Automated scripts
c. Data quality scorecards
d. External vendor audits
Answer: c. Data quality scorecardshellointern
What is ‘timeliness’ in data quality assessment?
a. Data should be current and up-to-date
b. Data should be complete
c. Data should be accurate
d. Data should be unique
Answer: a. Data should be current and up-to-datewayground
Which data quality tool feature is essential?
a. Ability to define quality rules
b. Data visualization
c. Data encryption
d. Report generation only
Answer: a. Ability to define quality ruleswayground
Which step comes first in the data quality improvement process?
a. Implement remediation measures
b. Identify data quality issues
c. Monitor effectiveness
d. Prioritize issues
Answer: b. Identify data quality issueshellointern
Which metric is not typically used for assessing data quality?
a. Completeness
b. Relevance
c. Volume
d. Consistency
Answer: c. Volumehellointern
Data validation rules are used to check:
a. Data accuracy, completeness, consistency
b. Data encryption efficiency
c. Data format only
d. Data migration status
Answer: a. Data accuracy, completeness, consistencyhellointern
The objective of the Discover phase in a data project is:
a. How can I document the data?
b. To determine which data mining technique will be used
c. How and where can I find additional data
d. Assure data quality
Answer: d. Assure data qualitystudocu
Data quality dimensions include:
a. Accessible, accurate, complete, consistent, relevant, comprehensive, easy to read and interpret
b. Accessible
c. Consistent
d. Non-commercial data
Answer: a. Accessible, accurate, complete, consistent, relevant, comprehensive, easy to read and interpretstudocu
Data quality scorecard monitors:
a. Data profiling
b. Control charts
c. Data quality
d. Data encryption
Answer: c. Data qualityhellointern
Which is a non-technical concern of data quality?
a. Data format
b. Data encryption
c. Data privacy laws
d. Sources of the data
Answer: d. Sources of the datastudocu
Data profiling typically reveals:
a. Frequencies and formats of data
b. Only data errors
c. Outliers only
d. No valuable insights
Answer: a. Frequencies and formats of datawayground
What is the threshold for quality data use in most organizations?
a. 90%
b. 95%
c. 99%
d. 100%
Answer: b. 95%wayground
What step follows issue remediation in continuous data quality improvement?
a. Root cause analysis
b. Monitor and evaluate
c. Data cleansing
d. Data migration
Answer: b. Monitor and evaluatehellointern
Data enrichment in quality management refers to:
a. Adding missing values
b. Transformation of irrelevant data
c. Improving the depth and breadth of data
d. Encrypting sensitive data
Answer: c. Improving the depth and breadth of datahellointern
Which of these is the result of robust data quality procedures?
a. Improved business decisions
b. Data redundancy
c. Higher storage costs
d. Reduced accessibility
Answer: a. Improved business decisionsacademy.cognopia
Data stewardship is most closely related to:
a. Data ownership
b. Data management
c. Data migration
d. Data profiling
Answer: b. Data managementwayground
What best describes the process of data cleaning?
a. Removal of duplicates
b. Correction of errors
c. Transformation of formats
d. All of the above
Answer: d. All of the abovehellointern
Which is NOT a method for identifying data quality issues?
a. Profiling
b. Validation
c. Random sampling
d. Auditing
Answer: c. Random samplinghellointern
Which data quality metric measures uniqueness in a dataset?
a. Accuracy
b. Validity
c. Uniqueness
d. Timeliness
Answer: c. Uniquenesswayground
Which dimension checks if all required records are present in a database?
a. Accuracy
b. Completeness
c. Consistency
d. Validity
Answer: b. Completenesswayground
What is the main cause of low data quality?
a. Initial data conversion
b. Manual data entry
c. Batch feed
d. All of the above
Answer: d. All of the abovescribd
How is consistency evaluated in datasets?
a. Matching formats across records
b. Check for duplicates
c. Accuracy of values
d. Correct metadata
Answer: a. Matching formats across recordswayground
What is data reconciliation?
a. Removal of redundant entries
b. Matching data between sources for consistency
c. Data enrichment
d. Data scoring
Answer: b. Matching data between sources for consistencyhellointern
Which process involves identifying outliers in datasets?
a. Data profiling
b. Data migration
c. Data encryption
d. Data backup
Answer: a. Data profilinghellointern
A control chart in data quality displays:
a. Process variability
b. Top management activity
c. Inspector actions
d. Database schema
Answer: a. Process variabilitymsibm
Which function is used for outlier detection in Python data analysis?
a. dropna()
b. zscore()
c. loc[]
d. head()
Answer: b. zscore()gyansetu
To ensure reliability, data quality procedures should be:
a. Continuous
b. Annual
c. One-time
d. Scheduled quarterly
Answer: a. Continuoushellointern
What does the uniqueness dimension in data quality mean?
a. No duplicate entries exist
b. Data is valid to real-world situations
c. Data is complete
d. Data is current
Answer: a. No duplicate entries existwayground
Data quality improvement starts with:
a. Data migration
b. Identify and prioritize problems
c. Cleansing and transformation
d. Profiling
Answer: b. Identify and prioritize problemshellointern
What type of data is “Temperature in Celsius”?
a. Ordinal
b. Nominal
c. Interval
d. Categorical
Answer: c. Intervalgyansetu
Which of these is NOT a direct indicator of poor data quality?
a. Missing values
b. Outliers
c. Duplicate records
d. High completeness score
Answer: d. High completeness scorehellointern
Data preservation means:
a. Saving data for future reference
b. Encrypting sensitive data
c. Analyzing only quality data
d. Removing historical data
Answer: a. Saving data for future referencestudocu
Scientific data is usually:
a. A result of guessing
b. Collected via instruments
c. Datasets in spreadsheets
d. Personal opinions
Answer: b. Collected via instrumentsstudocu
Which phase in data management involves correcting spelling mistakes?
a. Discover
b. Plan
c. Describe
d. Model
Answer: c. Describestudocu
In your plan phase, you need to:
a. Determine who will collect the data
b. Propose hypothesis based on research
c. Propose a machine learning model
d. Monitor and maintain data quality
Answer: d. Monitor and maintain data qualitystudocu
Which is NOT considered a legitimate data quality improvement step?
a. Implement remediation measures
b. Continuous monitoring
c. Ignoring feedback loops
d. Periodic evaluation
Answer: c. Ignoring feedback loopshellointern

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