MCQs

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Overall MCQs for Reference

What is duplicate data in data science?
a. Multiple identical records
b. Missing entries
c. Irrelevant columns
d. Outlier values
Answer: a. Multiple identical recordssciencedirect
Which of the following is the main consequence of duplicate data?
a. Improved accuracy
b. Loss of data integrity
c. Faster processing
d. Better visualization
Answer: b. Loss of data integrityexamveda
What term describes storing the same data in more than one location?
a. Data normalization
b. Data redundancy
c. Data validation
d. Data sampling
Answer: b. Data redundancyaskfilo
How are duplicate records usually detected?
a. Random sampling
b. Unique identifiers
c. Aggregation
d. Correlation
Answer: b. Unique identifiersnumerous
Which function in Pandas helps to remove duplicates?
a. drop_duplicates()
b. remove_duplicates()
c. clean_duplicates()
d. delete_duplicates()
Answer: a. drop_duplicates()placementpreparation
What is “deduplication” in data cleaning?
a. Sorting data
b. Removing duplicate records
c. Converting data formats
d. Filtering outliers
Answer: b. Removing duplicate recordskaggle
Which of the following is a drawback of duplicate data in analysis?
a. Faster results
b. Distorted analytics
c. Reduced memory usage
d. Clearer visualization
Answer: b. Distorted analyticsnumerous
In databases, what is a potential cause of duplicate data?
a. Lack of normalization
b. Frequent backups
c. Encryption errors
d. Transaction logging
Answer: a. Lack of normalizationsciencedirect
Which data cleaning step specifically addresses duplicate entries?
a. Standardize data formats
b. Remove irrelevant columns
c. Remove duplicate observations
d. Handle missing data
Answer: c. Remove duplicate observationstableau
What data issue is introduced by importing multiple datasets with overlapping records?
a. Missing data
b. Duplicate entries
c. Data normalization
d. Feature scaling
Answer: b. Duplicate entriesnumerous
Which technique helps to detect near-duplicate records?
a. Exact string matching
b. Fuzzy matching
c. Encryption
d. Data partitioning
Answer: b. Fuzzy matchingimprovado
What is an effect of storing duplicate data on disk?
a. Increases storage costs
b. Decreases processing time
c. Improves data accuracy
d. Reduces data size
Answer: a. Increases storage costsijraset
What impact does duplicate data have on machine learning models?
a. Higher accuracy
b. Lower accuracy
c. Shorter training time
d. No impact
Answer: b. Lower accuracydagshub
Deduplication is most effective when it is performed:
a. Before analysis
b. After visualization
c. During model evaluation
d. After reporting
Answer: a. Before analysiskaggle
In Pandas, which method identifies duplicate rows?
a. duplicated()
b. drop_missing()
c. find_duplicates()
d. copy()
Answer: a. duplicated()saidatascience
Which attribute can be used to uniquely identify a record?
a. Timestamp
b. Unique identifier (ID)
c. Data type
d. Value count
Answer: b. Unique identifier (ID)alation
What is a recommended action when duplicates are found in marketing data?
a. Ignore them
b. Merge contact records
c. Delete all data
d. Increase dataset size
Answer: b. Merge contact recordsimprovado
What is the effect of unchecked duplicate questions in MCQ repositories?
a. Increases repository value
b. Reduces content quality
c. Improves test fairness
d. Enhances coverage
Answer: b. Reduces content qualityceur-ws
Which algorithm is commonly used for deduplication in databases?
a. Clustering
b. Decision tree
c. Regression
d. Feature scaling
Answer: a. Clusteringijraset
Duplicate data can arise from which of the following sources?
a. Human error
b. Automated data imports
c. System integrations
d. All of the above
Answer: d. All of the abovenumerous
What kind of matching does advanced deduplication involve?
a. Only exact matching
b. Exact and fuzzy matching
c. Only fuzzy matching
d. Random matching
Answer: b. Exact and fuzzy matchingimprovado
Which metric is important for evaluating deduplication systems?
a. Recall
b. Variance
c. Skewness
d. Kurtosis
Answer: a. Recallijraset
What problem can duplicate records cause in data visualization?
a. Clearer charts
b. Misleading results
c. Improved structure
d. Reduced sample size
Answer: b. Misleading resultsnumerous
In large datasets, duplicate detection is known as:
a. Entity Resolution
b. Data Transformation
c. Data Encryption
d. Data Sampling
Answer: a. Entity Resolutionceur-ws
Which best practice ensures prevention of future duplicates?
a. Data validation at entry
b. Frequent backups
c. Outlier removal
d. Aggregation
Answer: a. Data validation at entryalation
Deduplication using NLP involves:
a. Parsing only numeric fields
b. Comparing semantic similarity
c. Encrypting data
d. Sorting by timestamps
Answer: b. Comparing semantic similarityceur-ws
What is the recommended way to merge duplicates?
a. Keep the most recent record
b. Keep all records
c. Delete all records
d. Randomly select
Answer: a. Keep the most recent recordimprovado
What type of analysis can be distorted by duplicate records?
a. Regression
b. All types of analysis
c. Dimension reduction only
d. Visualization only
Answer: b. All types of analysisnumerous
Deduplication accuracy can be measured with:
a. ROC curve
b. Z-score
c. Confidence interval
d. R-squared
Answer: a. ROC curveijraset
When cleaning marketing data, which field combination helps detect duplicates?
a. Name and address
b. Country and continent
c. Time and date
d. Sales and revenue
Answer: a. Name and addressimprovado
What does maintaining a unique identifier in a dataset prevent?
a. Duplicate records
b. Missing data
c. Outliers
d. Irrelevant fields
Answer: a. Duplicate recordsalation
Which data quality issue arises from duplicate entries?
a. Lack of accuracy
b. Improved precision
c. More clarity
d. Increased memory space
Answer: a. Lack of accuracydagshub
Machine learning for duplicate detection uses:
a. Pattern recognition
b. Clustering algorithms
c. NLP
d. All of the above
Answer: d. All of the aboveijraset
Storage optimization systems use deduplication to:
a. Reduce redundancy
b. Increase duplicates
c. Add missing values
d. Randomize data
Answer: a. Reduce redundancyijraset
In entity resolution, “near-duplicates” refer to:
a. Slightly different records
b. Completely identical entries
c. Irrelevant columns
d. Outlier transactions
Answer: a. Slightly different recordsceur-ws
Which process checks data for duplicates before entry?
a. Real-time validation
b. Aggregation
c. Indexing
d. Normalization
Answer: a. Real-time validationijraset
How can duplicates affect pharmacovigilance reporting?
a. Reduce underreporting
b. Increase confusion and costs
c. No effect
d. Accelerate automation
Answer: b. Increase confusion and costspmc.ncbi.nlm.nih
What is the first step in a systematic data cleansing process?
a. Data validation and profiling
b. Outlier removal
c. Imputation
d. Transformation
Answer: a. Data validation and profilingimprovado
What combination of algorithms is effective for duplicate detection?
a. Supervised and unsupervised learning
b. Only unsupervised learning
c. Only supervised learning
d. Regression and classification
Answer: a. Supervised and unsupervised learningijraset
Duplicate data can negatively affect:
a. Data integrity
b. Storage efficiency
c. Analytics
d. All of the above
Answer: d. All of the aboveexamveda+1
What kind of tool is essential for large-scale deduplication in data repositories?
a. Automation tools
b. Manual review tools
c. Visualization software
d. Random sampling tools
Answer: a. Automation toolsnumerous
Data deduplication is vital for:
a. Modern storage systems
b. Small, static datasets
c. Visualization only
d. Data encryption
Answer: a. Modern storage systemsijraset
What is a real-world example of duplicate data affecting results?
a. Identical customer profiles in CRM
b. Unique entries in logs
c. Random outlier detection
d. Merged addresses in one record
Answer: a. Identical customer profiles in CRMnumerous
Which of the following can create duplicates in big data systems?
a. System integrations
b. Automated imports
c. Human error
d. All of the above
Answer: d. All of the abovenumerous
What does preprocessing for duplicate data involve?
a. Initial data scan for duplicates
b. Visualization setup
c. Model deployment
d. Algorithm selection
Answer: a. Initial data scan for duplicatesceur-ws
What value does deduplication add to data quality?
a. Increases reliability
b. Distorts analysis
c. Reduces storage
d. Improves model performance
Answer: a. Increases reliabilitydagshub+1
What technique can help in identifying near-duplicates in text fields?
a. NLP-based similarity
b. Sorting algorithms
c. Outlier analysis
d. Data normalization
Answer: a. NLP-based similarityceur-ws
What is necessary for de-duplication in AI applications?
a. Consistency checks
b. Unique identifiers
c. Automated alerts
d. All of the above
Answer: d. All of the aboveijraset
Which field is often profiled first for duplicate detection?
a. Transaction ID
b. Data type
c. Value range
d. Outlier percentage
Answer: a. Transaction IDimprovado
What is a major future challenge for duplicate detection systems?
a. Handling increasing data volumes
b. Reducing system integrations
c. Minimizing sample size
d. Improving encryption methods
Answer: a. Handling increasing data volumessciencedirect+1esalation+1

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