MCQs

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Overall MCQs for Reference

What does data completeness primarily refer to in data science?
a. Ensuring data is unique
b. The absence of missing values and coverage of all required fields
c. Data being always in numeric format
d. Data processed using machine learning
Answer: b. The absence of missing values and coverage of all required fieldsmontecarlodata+2
Which of the following best describes a complete dataset?
a. Contains only numerical data
b. Contains all required observations and variables for a given analysis
c. Has no duplicate entries
d. Only contains present data points without context
Answer: b. Contains all required observations and variables for a given analysisatlan+1
In which step of the data lifecycle is data completeness first compromised?
a. Data collection
b. Data cleaning
c. Data visualization
d. Model deployment
Answer: a. Data collectionastera+2
What is a primary challenge to achieving data completeness?
a. Too many data visualization tools
b. Data entry errors or omissions
c. High computing cost
d. Cloud storage limitations
Answer: b. Data entry errors or omissionshevoacademy+2
What is record-level completeness?
a. The percentage of records that have every required field populated
b. Data with unique column names
c. The use of encryption for all data rows
d. Ensuring all data is stored in the cloud
Answer: a. The percentage of records that have every required field populatedacceldata+1
Which measure evaluates if each row in a dataset contains critical fields?
a. Field completeness
b. Record-level completeness
c. Data redundancy
d. Data de-identification
Answer: b. Record-level completenessmontecarlodata+1
What can result from incomplete data in business analytics?
a. More accurate decisions
b. Skewed analysis and unreliable insights
c. Faster processing speeds
d. Increased sample diversity
Answer: b. Skewed analysis and unreliable insightsclicdata+1
Which is NOT an example of data completeness?
a. Historical data coverage
b. Complete demographic profiles
c. Data anonymization
d. Geographical data representation
Answer: c. Data anonymizationatlan
Field completeness refers to:
a. All fields are present for at least one record
b. The percentage of a certain field that contains valid data across all records
c. Only ID columns are filled
d. All values in a column being zero
Answer: b. The percentage of a certain field that contains valid data across all recordsacceldata
Why is data completeness vital for data-driven decisions?
a. Ensures all analysis is based on a full representation, minimizing erroneous conclusions
b. Enables faster data entry
c. Increases database size
d. Allows only qualitative analysis
Answer: a. Ensures all analysis is based on a full representation, minimizing erroneous conclusionsdataversity+2
Which of the following directly impacts data completeness?
a. File encryption
b. Data integration from multiple sources
c. Data visualization
d. Parallel processing architectures
Answer: b. Data integration from multiple sourceshevoacademy+2
What kind of metric is used for evaluating data completeness?
a. Edit distance
b. Record completeness
c. Lossless compression ratio
d. Variance reduction
Answer: b. Record completenessacceldata
Which factor does NOT affect data completeness?
a. Poor data governance
b. Data entry automation
c. Data consistency
d. Lack of data ownership
Answer: c. Data consistencyatlan+1
Data completeness most closely relates to which aspect of data quality?
a. Data timeliness
b. Data accuracy
c. Data coverage
d. Data deduplication
Answer: c. Data coverageastera+1
A dataset that lacks all information for specific time periods demonstrates incomplete:
a. Historical data coverage
b. Real-time reporting
c. Data encryption
d. Data transformation
Answer: a. Historical data coverageatlan
Which of the following is a technique to improve data completeness?
a. Outlier detection
b. Data sampling and profiling
c. File format conversion
d. Model pruning
Answer: b. Data sampling and profilinghevoacademy
Which is an example of attribute completeness?
a. Every field in each row of a customer table is filled
b. At least one field is filled per record
c. Database contains only primary keys
d. All records are stored in a cloud environment
Answer: a. Every field in each row of a customer table is filledmontecarlodata
Missing demographic data in customer records primarily impacts:
a. Data completeness
b. Data redundancy
c. Data encryption
d. Data normalization
Answer: a. Data completenessatlan
Incomplete data from external sources most often results from:
a. Standardized data formats
b. Lack of control over external data collection
c. Overtraining of models
d. Visualization issues
Answer: b. Lack of control over external data collectionmontecarlodata
Redundancy checks in data completeness ensure that:
a. Records are unique and relevant
b. Data is always encrypted
c. All data is processed in real-time
d. Only numeric data is included
Answer: a. Records are unique and relevantacceldata
Which quality dimension does completeness belong to?
a. Data latency
b. Data quality
c. Data scalability
d. Data anonymization
Answer: b. Data qualitycollibra+1
In a health survey, what ensures findings are applicable to all sections?
a. Random sampling
b. Complete demographic data
c. Predictive modeling
d. Sampling error reduction
Answer: b. Complete demographic dataatlan
What does insufficient feedback loop cause in terms of data completeness?
a. Improved data reporting
b. Undetected incomplete or missing data
c. Enhanced data visualization
d. Increased data normalization
Answer: b. Undetected incomplete or missing datahevoacademy+1
Which methodology helps monitor data completeness over time?
a. Event sourcing
b. Automated monitoring and alerts
c. Blockchain logging
d. Manual CSV exports
Answer: b. Automated monitoring and alertshevoacademy
Data completeness problems can be best detected with:
a. Data profiling tools
b. Schema migration tools
c. Visualization-only tools
d. Data masking solutions
Answer: a. Data profiling toolsastera+1
Which solution helps address incomplete data due to legacy systems?
a. Updating to modern data platforms
b. Manual record entry
c. Advanced encryption
d. Selective sampling
Answer: a. Updating to modern data platformshevoacademy
Lack of data ownership can lead to which issue?
a. Missing or incomplete data due to unclear responsibility
b. Improved reporting accuracy
c. Data consistency
d. Database normalization
Answer: a. Missing or incomplete data due to unclear responsibilityatlan+1
Data validation enhances completeness by:
a. Detecting and flagging missing values
b. Encrypting all fields
c. Normalizing text formats
d. Creating new data entries
Answer: a. Detecting and flagging missing valueshevoacademy+1
What is the impact of obsolete data systems on completeness?
a. Can result in missing and incomplete data due to incompatibility with new formats
b. Always increases completeness
c. Improves data accessibility
d. Prevents all data quality issues
Answer: a. Can result in missing and incomplete data due to incompatibility with new formatshevoacademy
Which of the following datasets is more likely to be complete?
a. A dataset with all columns and rows populated for required information
b. One with only ID fields filled
c. Dataset with some fields left blank
d. Dataset with only recent records
Answer: a. A dataset with all columns and rows populated for required informationmontecarlodata+1
A major risk of incomplete data in healthcare analytics is:
a. Enhanced patient outcomes
b. Skewed analyses impacting critical healthcare decisions
c. Increased system speed
d. More robust datasets
Answer: b. Skewed analyses impacting critical healthcare decisionsclicdata+1
Data completeness is a prerequisite for:
a. Data consistency checks
b. Reliable and valid statistical inference
c. File compression
d. Data encryption
Answer: b. Reliable and valid statistical inferencegeeksforgeeks+1
A high percentage of missing data in key fields generally indicates:
a. High completeness
b. Low completeness
c. Enhanced accuracy
d. Better encryption
Answer: b. Low completenessgeeksforgeeks
What does data coverage in completeness metrics refer to?
a. Proportion of required data elements present for entities or attributes
b. All data stored in the cloud
c. Data only collected for sales
d. Only numeric data is included
Answer: a. Proportion of required data elements present for entities or attributesacceldata
Which organizational practice is key to ensuring data completeness?
a. Clear data governance and ownership
b. Decentralized cloud storage
c. Data encryption only
d. Manual entry of all data
Answer: a. Clear data governance and ownershipastera+1
Which KPI could indicate data completeness?
a. Field completeness ratio
b. Download speed
c. Cloud cost reduction
d. User engagement rate
Answer: a. Field completeness ratiomontecarlodata+1
In the context of IoT sensor data, completeness means:
a. All necessary sensor readings are present for the required intervals
b. Data is always normalized
c. All data is encrypted
d. Sensors use the same protocol
Answer: a. All necessary sensor readings are present for the required intervalsatlan
Which practice does not contribute to improving data completeness?
a. Randomly deleting old records
b. Regular data validation and quality checks
c. Automated monitoring for missing values
d. Stakeholder feedback on data issues
Answer: a. Randomly deleting old recordsatlan+1
A data completeness gap is illustrated by:
a. Records that lack one or more critical fields needed for use
b. Completion of all optional fields
c. Having redundant data entries
d. Over-normalized datasets
Answer: a. Records that lack one or more critical fields needed for usemontecarlodata
Which technology advancement helps continuously monitor completeness?
a. Data observability and automated tools
b. Manual spreadsheet analysis
c. Only using relational databases
d. File-based archiving
Answer: a. Data observability and automated toolshevoacademy+1
The impact of incomplete transaction data could be:
a. Inaccurate financial reporting and missed trends
b. Higher data redundancy
c. Encrypted financial statements
d. Fewer backup operations
Answer: a. Inaccurate financial reporting and missed trendsclicdata+1
What role does visualization play in communicating data completeness?
a. Makes gaps in data completeness visible to stakeholders
b. Reduces computing needs
c. Hides data quality issues
d. Increases only data security
Answer: a. Makes gaps in data completeness visible to stakeholdersmontecarlodata
A missing value in a mandatory field during data migration is an issue of:
a. Data completeness
b. Data timeliness
c. Data normalization
d. Data transformation
Answer: a. Data completenessastera+1
Data profiling for completeness involves:
a. Assessing the percentage of missing values for each field
b. Assessing model prediction accuracy
c. Checking file download speeds
d. Monitoring storage usage
Answer: a. Assessing the percentage of missing values for each fieldacceldata+1
Data completeness can be tracked using:
a. Stacked bar charts showing completeness for different fields
b. Encryption software statistics
c. User login frequency
d. API response times
Answer: a. Stacked bar charts showing completeness for different fieldsmontecarlodata
Which scenario is an example of incomplete data impacting e-commerce?
a. Product listings missing key fields like category or description
b. All products having review scores
c. Only numerical prices for products
d. Duplicate transaction IDs
Answer: a. Product listings missing key fields like category or descriptionmontecarlodata
Best practice for defining completeness for a new data system:
a. Specify which fields or records constitute a “minimally complete” entry for each use case
b. Wait until after deployment to monitor completeness
c. Only collect partial information initially
d. Use only sample records for configuration
Answer: a. Specify which fields or records constitute a “minimally complete” entry for each use casemontecarlodata
The primary goal of data completeness as a quality metric is to:
a. Ensure all required data is present for reliable analysis and decision-making
b. Reduce storage costs
c. Increase cloud resource utilization
d. Decrease network latency
Answer: a. Ensure all required data is present for reliable analysis and decision-makingdataversity+2
What effect can missing key fields in customer records have on marketing?
a. Limits outreach and segmentation, reducing campaign effectiveness
b. Increases website traffic
c. Improves data normalization
d. Enhances data encryption
Answer: a. Limits outreach and segmentation, reducing campaign effectivenessatlan+1
Why is continuous monitoring necessary for data completeness?
a. Data sources and requirements change over time, so automated checks are needed to maintain completeness
b. It reduces electricity costs
c. Only increases database size
d. Disables data backup
Answer: a. Data sources and requirements change over time, so automated checks are needed to maintain completenesshevoacademy+2

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