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Overall MCQs for Reference
- Which type of data is most difficult to structure for analysis?
a. Tabular data
b. Unstructured data
c. Relational data
d. Time series data
Answer: b. Unstructured datasanfoundry - Which is NOT a typical step in structuring data?
a. Data cleaning
b. Data normalization
c. Data collection
d. Data modeling
Answer: c. Data collectionroadmap - What data structure is commonly used to represent hierarchical information?
a. Queue
b. Stack
c. Tree
d. Array
Answer: c. Treesimplilearn - When merging datasets, what technique is used to match corresponding columns?
a. Aligning schemas
b. Cross-validation
c. Data labeling
d. Feature selection
Answer: a. Aligning schemasroadmap - Which format commonly represents structured data?
a. Images
b. CSV files
c. Audio streams
d. Raw text
Answer: b. CSV filessanfoundry - What is a data frame used for in data science?
a. Storing images
b. Tabular storage
c. Binary classification
d. Feature extraction
Answer: b. Tabular storageinterviewbit - What is the process of converting inconsistent categories (like “Y” vs. “Yes”) into a uniform format called?
a. Data aggregation
b. Data transformation
c. Data unification
d. Data visualization
Answer: c. Data unificationroadmap - Which of the following is NOT a data structuring technique?
a. Sorting
b. Parsing
c. Clustering
d. Normalization
Answer: c. Clusteringdatacamp - Which data structure is appropriate for implementing recursion?
a. Queue
b. Stack
c. Array
d. Tree
Answer: b. Stacksanfoundry - Which is an example of unstructured data?
a. Relational tables
b. Text documents
c. Data frames
d. Spreadsheets
Answer: b. Text documentssanfoundry - What does “schema” refer to when structuring data?
a. Data type
b. Logical framework
c. Visualization method
d. Encryption protocol
Answer: b. Logical frameworkroadmap - What is the best structure for storing sequential data?
a. Linked list
b. Graph
c. Tree
d. Hash table
Answer: a. Linked listsimplilearn - What is data normalization?
a. Creating new variables
b. Scaling values to a standard range
c. Scrambling data order
d. Removing duplicates
Answer: b. Scaling values to a standard rangeroadmap - What feature does a relational database provide regarding structured data?
a. Variable column types
b. Organized rows and columns
c. Image encoding
d. Audio streaming
Answer: b. Organized rows and columnssanfoundry - Which process tags data with a source column?
a. Data projection
b. Data lineage tracking
c. Data filling
d. Data regression
Answer: b. Data lineage trackingroadmap - Which of the following is a data structuring task?
a. Data acquisition
b. Labeling the data
c. Presentation format
d. Both b and c
Answer: d. Both b and croadmap - Which method is best for structuring time-based data?
a. Hashing
b. Time series indexing
c. Feature selection
d. Random sampling
Answer: b. Time series indexingsanfoundry - What is sparse data?
a. Data with many duplicates
b. Data with mostly missing or zero values
c. Overly dense data
d. High-resolution images
Answer: b. Data with mostly missing or zero valuessanfoundry - What type of structure is used for tabular data in Python?
a. Dictionary
b. DataFrame
c. Set
d. Tuple
Answer: b. DataFrameinterviewbit - When combining multiple datasets, what problem may arise?
a. Schema mismatch
b. Overfitting
c. Underfitting
d. Model bias
Answer: a. Schema mismatchroadmap - Converting raw text into numerical features is called?
a. Tokenization
b. Normalization
c. Encoding
d. Aggregation
Answer: c. Encodingroadmap - What is the appropriate data structure for graphs?
a. Adjacency matrix
b. Stack
c. Array
d. Heap
Answer: a. Adjacency matrixsimplilearn - What does data structuring enable in data science?
a. Faster computation
b. Easier visualization
c. Better analysis
d. All of the above
Answer: d. All of the abovedatacamp - Which is NOT an example of structured data?
a. XML documents
b. SQL tables
c. PNG images
d. Excel spreadsheets
Answer: c. PNG imagessanfoundry - Which structure stores elements with unique keys?
a. Array
b. Dictionary
c. Stack
d. Matrix
Answer: b. Dictionaryinterviewbit - Tagging rows with a data source helps with?
a. Tracing provenance
b. Limiting memory
c. Increasing noise
d. Building clusters
Answer: a. Tracing provenanceroadmap - What is the first step in structuring raw data?
a. Data collection
b. Data cleaning
c. Data modeling
d. Data mining
Answer: b. Data cleaningroadmap - How do you resolve format conflicts in merged data?
a. Use pivot tables
b. Apply schema alignment
c. Encode images
d. Encrypt files
Answer: b. Apply schema alignmentroadmap - Which comes before data modeling in structuring data?
a. Data cleaning
b. Feature engineering
c. Model training
d. Prediction
Answer: a. Data cleaningroadmap - For multidimensional arrays, the data structure is called?
a. Matrix
b. Tree
c. Graph
d. Hash table
Answer: a. Matrixsimplilearn - Which method deals with missing values in structured data?
a. Data imputation
b. Data sorting
c. Data hashing
d. Data encoding
Answer: a. Data imputationsanfoundry - What is the role of index columns?
a. Unique identification
b. Aggregation
c. Visualization
d. Compression
Answer: a. Unique identificationroadmap - What is a normalized database?
a. With redundant data
b. With minimal duplication
c. Containing only images
d. Storing only text
Answer: b. With minimal duplicationsanfoundry - What technique would you use to structure categorical data?
a. One-hot encoding
b. Decision trees
c. Random forests
d. Regression analysis
Answer: a. One-hot encodingroadmap - Which process helps maintain consistency when combining datasets?
a. Unifying categories
b. Random sampling
c. Feature selection
d. Data visualization
Answer: a. Unifying categoriesroadmap - What best describes feature engineering?
a. Transforming raw data into features
b. Encoding images
c. Compressing binary files
d. Indexing database tables
Answer: a. Transforming raw data into featuresinterviewkickstart - Why create a schema before structuring data?
a. To ensure consistency
b. To overfit models
c. To increase redundancy
d. To speed up visualization
Answer: a. To ensure consistencyroadmap - What is a disadvantage of unstructured data?
a. Easy analysis
b. Incompatible formats
c. Rapid visualization
d. Direct querying
Answer: b. Incompatible formatssanfoundry - Which of the following would best structure geospatial data?
a. Matrix
b. DataFrame
c. GIS model
d. Array
Answer: c. GIS modelsimplilearn - Which is used for structured data in databases?
a. SQL
b. HTML
c. JPEG
d. GIF
Answer: a. SQLsanfoundry - What helps avoid downstream issues in analytics?
a. Data unification
b. Data scrambling
c. Feature import
d. Index removal
Answer: a. Data unificationroadmap - For financial transaction logs, which one is crucial?
a. Timestamp indexing
b. Image encoding
c. Audio normalization
d. Random sampling
Answer: a. Timestamp indexingsanfoundry - What is a record in a database?
a. A collection of fields
b. An image file
c. A random pixel
d. A model prediction
Answer: a. A collection of fieldssimplilearn - Structuring data often aids in?
a. Predictive modeling
b. Data mining
c. Quantum computing
d. Encryption
Answer: a. Predictive modelingroadmap - What is a column in a data table?
a. Variable
b. Record
c. Attribute
d. Both a and c
Answer: d. Both a and csimplilearn - What does flattening data mean?
a. Removing nested structures
b. Encoding binary files
c. Compressing images
d. Randomizing samples
Answer: a. Removing nested structuresroadmap - What structure best represents social networks?
a. Tree
b. Queue
c. Graph
d. Stack
Answer: c. Graphsimplilearn - Which storage format is most common for structured data?
a. Spreadsheets
b. MP3 files
c. JPEG images
d. Videos
Answer: a. Spreadsheetssanfoundry - Which is NOT part of data structuring?
a. Schema design
b. Data visualization
c. Feature selection
d. Model validation
Answer: d. Model validationroadmap - What is “data wrangling” in structuring data?
a. Cleaning and organizing data
b. Training models
c. Deploying solutions
d. Query optimization
Answer: a. Cleaning and organizing datasanfoundry+1
- https://www.sanfoundry.com/1000-data-science-questions-answers/
- https://roadmap.sh/questions/data-science
- https://www.simplilearn.com/data-structure-interview-questions-and-answers-article
- https://www.interviewbit.com/data-science-mcq/
- https://www.datacamp.com/blog/data-structure-interview-questions
- https://www.sanfoundry.com/1000-data-structure-questions-answers/
- https://interviewkickstart.com/blogs/articles/data-science-mcq-answers
- https://www.geeksforgeeks.org/quizzes/top-50-data-structures-mcqs-with-answers/
- https://siteforinfotech.com/p/data-structure-mcq-sets.html
- https://www.gyansetu.in/blog/data-science-objective-type-mcq-quiz-interview-preparation/
- https://www.interviewbit.com/data-structure-mcq/
- https://www.geeksforgeeks.org/dsa/top-100-data-structure-and-algorithms-dsa-interview-questions-topic-wise/
- https://www.placementpreparation.io/mcq/data-science/page/2/
- https://www.scribd.com/document/783318391/Data-Structure-Multiple-Choice-Questions-and-Answers
- https://www.scribd.com/document/687893030/Data-Structure-MCQ-Multiple-Choice-Questions
- https://examradar.com/mcqs/data-structure-mcqs/
- https://mentr-me.com/question/7-most-important-data-science-mcq-with-answers-pdf
- https://www.includehelp.com/mcq/data-science-mcqs.aspx
- https://www.interviewbit.com/data-structure-interview-questions/
- https://www.acmecollinsschool.com/data-science-mcq-questions.html