DTSA 5504 DATA MINING PIPELINE
EXAMINATION TEST 2026 QUESTIONS WITH
SOLUTIONS GRADED A+
◉ What is data mining? Answer: Knowledge discovery from data
(Extraction of interesting patterns or knowledge from huge amounts of
data.)
◉ Benefits of data mining. Answer: Scalability and efficiency
◉ The four views of data mining. Answer: Data, Application,
Knowledge, Technique
◉ What are the 5Vs of Data Mining? Answer: Volume, Variety, Velocity,
Veracity, Value
◉ Relational, transactional data (Data View). Answer: E.g., student
records, bank accounts, store purchases
◉ Sequential, temporal, streaming data (Data View). Answer: E.g., gene
sequences, stock prices, sensor readings
,◉ Spatial, spatial-temporal data (Data View). Answer: E.g., land use,
bird migration, traffic condition
◉ Text, multimedia, Web data (Data View). Answer: E.g., news articles,
audio/video/image data, hypertext
◉ Graph, network data (Data View). Answer: E.g., social network,
power grid, co-authorship
◉ Market Analysis, target advertisement (Application View). Answer:
E.g., customer profiling, product recommendation
◉ Healthcare, medical research (Application View). Answer: E.g.,
disease diagnosis, patient care, drug discovery
◉ Science and engineering (Application View). Answer: E.g., air
pollution, marine life, electric vehicles
◉ Security (Application View). Answer: E.g., surveillance,
intrusion/crime, fraud, cyberattack
◉ Government, nonprofit (Application View). Answer: E.g., urban
planning, traffic control, education
, ◉ Frequent pattern , correlation (Knowledge View). Answer: E.g.,
Songs listened together or in certain sequence
◉ Categorization (Knowledge View). Answer: E.g., Similarity among
user with certain purchases, differences between two patient groups
◉ Anomaly, outliers (Knowledge View). Answer: E.g., sensor errors,
fraud activities, extreme events
◉ Changes over time (Knowledge View). Answer: E.g., emerging new
patterns, shift of user interest
◉ What are the five different techniques for data mining? Answer:
Frequent pattern analysis, classification/prediction, clustering, anomaly
detection, trend and evolution analysis
◉ Frequent Pattern Analysis. Answer: Includes frequent itemset,
frequent sequence, frequent structure, association rules, correlation
analysis
◉ Classification. Answer: Includes pre-defined classes, training data,
and distinguishable classes
EXAMINATION TEST 2026 QUESTIONS WITH
SOLUTIONS GRADED A+
◉ What is data mining? Answer: Knowledge discovery from data
(Extraction of interesting patterns or knowledge from huge amounts of
data.)
◉ Benefits of data mining. Answer: Scalability and efficiency
◉ The four views of data mining. Answer: Data, Application,
Knowledge, Technique
◉ What are the 5Vs of Data Mining? Answer: Volume, Variety, Velocity,
Veracity, Value
◉ Relational, transactional data (Data View). Answer: E.g., student
records, bank accounts, store purchases
◉ Sequential, temporal, streaming data (Data View). Answer: E.g., gene
sequences, stock prices, sensor readings
,◉ Spatial, spatial-temporal data (Data View). Answer: E.g., land use,
bird migration, traffic condition
◉ Text, multimedia, Web data (Data View). Answer: E.g., news articles,
audio/video/image data, hypertext
◉ Graph, network data (Data View). Answer: E.g., social network,
power grid, co-authorship
◉ Market Analysis, target advertisement (Application View). Answer:
E.g., customer profiling, product recommendation
◉ Healthcare, medical research (Application View). Answer: E.g.,
disease diagnosis, patient care, drug discovery
◉ Science and engineering (Application View). Answer: E.g., air
pollution, marine life, electric vehicles
◉ Security (Application View). Answer: E.g., surveillance,
intrusion/crime, fraud, cyberattack
◉ Government, nonprofit (Application View). Answer: E.g., urban
planning, traffic control, education
, ◉ Frequent pattern , correlation (Knowledge View). Answer: E.g.,
Songs listened together or in certain sequence
◉ Categorization (Knowledge View). Answer: E.g., Similarity among
user with certain purchases, differences between two patient groups
◉ Anomaly, outliers (Knowledge View). Answer: E.g., sensor errors,
fraud activities, extreme events
◉ Changes over time (Knowledge View). Answer: E.g., emerging new
patterns, shift of user interest
◉ What are the five different techniques for data mining? Answer:
Frequent pattern analysis, classification/prediction, clustering, anomaly
detection, trend and evolution analysis
◉ Frequent Pattern Analysis. Answer: Includes frequent itemset,
frequent sequence, frequent structure, association rules, correlation
analysis
◉ Classification. Answer: Includes pre-defined classes, training data,
and distinguishable classes
