001.

Data warehouse is____ C

A The actual discovery phase of a B The stage of selecting the right data
knowledge discovery process for a KDD process
C A subject-oriented integrated time D Same as OLTP
variant non-volatile collection of data
in support of management
002. The data is stored, retrieved and updated in ____ A
A OLAP B OLTP
C SMTP D CLUSTER
003. ______ is a subject-oriented, integrated,time-variant, nonvolatile collection or data in B
support of management decisions
A Data Mining B Data warehousing
C Document Mining D Queuing
004. ___are designed to overcome any limitations placed on the warehouse by the nature of C
the relational data model.
A Operational Database B Relational Database
C Multidimensional Database D Data Repository
005. Abbreviation for OLAP B
A Online large Applications Process B Online Analytical Processing
C Online Algorithmic Processing D Online Adverting Policy
006. Data Warehouse performs_______ C
A Periodic Processing B Overtime processing
C Midnight processing D No processing
007. __________ is the heart of the warehouse. B
A Data Mining Database Servers B Data warehouse database servers
C Data mart Database servers D Relational Database Servers
008. __________represents the data contained in the data warehouse. B
A Relational Data B Meta Data
C Informal Data D Historical Data
009. Expansion for DSS in Data Warehouse is__________. A
A Decision Support System B Decision Single System
C Data Storage System D Data Support system
010. The time horizon in Data warehouse is usually __________ D
A 1-2 years B 3-4 years
C 5-6 years D 5-10 years
011. The source of all data warehouse data is the____________ A
A operational environment B Informal environment.
C Formal environment. D Technology environment
012. The star schema is composed of __________ fact table. A
A One B Two
C Three D four
013. ________maps the core warehouse metadata to business concepts, familiar and A
useful to end users.
A Application level metadata B Algorithmic level metadata
C Department Level Metadata D Core warehouse metadata
014. ________________defines the structure of the data held in operational databases and C
used byoperational applications.
A User level metadata B Data warehouse metadata
C Operational Metadata D Data Mining metadata
015. ________________ is held in the catalog of the warehouse database system. B
A Application level metadata B Algorithmic level metadata
C Department Level Metadata D Core warehouse metadata
016. The type of relationship in star schema is__ C
A Many-to-many B One-to-one
 C One-to-many D Many-to-one
017. A data warehouse is _____________. C
A Updated by end users. B Contains numerous naming
conventions and formats
C Organized around important subject D Contains only current data
areas.
018. The biggest drawback of the level indicator in the classic star-schema is that it C
limits_________.
A Quantify B Qualify
C Flexibility D Ability
019. Data warehouse contains_____________data that is never found in theoperational C
environment.
A Normalized B Informational
C Summary D denormalized
020. ___________ is a good alternative to the star schema. C
A Star schema B Snowflake schema
C Fact constellation D Star snowflake schema
021. Which of the following can be considered as the correct process of Data Mining? A
A Infrastructure, Exploration, Analysis, B Exploration, Infrastructure, Analysis,
Interpretation, Exploitation Interpretation, Exploitation
C Exploration, Infrastructure, D Exploration, Infrastructure, Analysis,
Interpretation, Analysis, Exploitation Exploitation, Interpretation
022. In Data warehouse, the load and index is____? C
A A process to upgrade the quality of B A simple initial parameters
data warehouse after it is moved into
a warehouse
C A process to load the data in the D A upgrading policy to ensure the
data warehouse and to create quality of data
necessary indexes
023. Which of the following retail analytic applications involve(s) the use of search A
techniques to gain insights into customer's buying patterns?
A Factor analysis B Regression analysis
C Data mining D Data scrapping
024. Fact tables are ___________. C
A Completely denormalized B Partially denormalized
C Completely normalized D Partially normalized
025. The process of removing deficiencies and loopholes in the data is called ____. D
A Data aggregation B Extraction of data
C Compression of data D Cleaning of data
026. ............................. is a comparison of the general features of the target class data C
objects against the general features of objects from one or multiple contrasting classes.
A Data Characterization B Data Classification
C Data discrimination D Data selection
027. ............................. is a summarization of the general characteristics or features of a B
target class of data.
A Data Characterization B Data Classification
C Data discrimination D Data selection
028. Which of the following is not a data mining functionality? C
A Characterization and Discrimination B Classification and regression
C Selection and interpretation D Clustering and Analysis
029. Which of the following is an essential process in which the intelligent methods are B
applied to extract data patterns?
A Warehousing B Data Mining
C Text Mining D Data Selection
030. What is KDD in data mining? B
A Knowledge Discovery in Databases B Knowledge discovery in datamining
C Knowing domain data D Knowledge of data driven
031. ETL stands for ____________ D
A Effect, transfer, and load B Explain, transfer and load
C Extract, transfer, and load D Extract, transform, and load
032. Which of the following statement is true regarding classification? B
A It is a measure of accuracy. B It is a subdivision of a set.
C It is the task of assigning a D It is a clustering process
classification
033. The output of KDD is ............. D
A Data B Information
C Query D Useful information
034. Strategic value of data mining is ...................... C
A Cost sensitive B Work sensitive
C Time sensitive D Technical sensitive
035. ............................. is the process of finding a model that describes and distinguishes D
data classes or concepts.
A Data characterization B Data classification
C Data Dredging D Data Discrimination
036. Identify the term used to define the multidimensional model of the data warehouse. C
A Table B Tree
C Data Cube D Data Structure
037. Identify the type of relationship between fact and dimension. C
A One to one B Many to many
C One to many D Many to one
038. Why snowflake schema is applied? C
A Transformation B Aggregation
C Normalization D Generalization
039. Identify among the following for which system of data warehousing is mostly used. C
A Data mining and storage B Data Integration and data storage
C Reporting and data analysis D Data cleaning and data storage
040. Identify the main characteristic of OLTP. A
A Provides advanced database support B Does not support client/server
architecture
C Uses single dimension data analysis D Uses data cleaning process
techniques
041. A ____ is a specialized computer server that searches for information on the Web. A
A Web search engine B Meta data
C Warehouse D Neural network
042. _____ Technologies provide historical, current, and predictive views of business B
operations.
A Information Retrieval B Business Intelligence
C Transaction management D Web based
043. Discrimination descriptions expressed in the form of rules are referred to as C
A Target Rules B Association Rules
C Discriminant Rules D Classification Rules
044. You have a dataset of different flowers containing their petal lengths and color. Your B
model has to predict the type of flower for given petal lengths and color. This is a-
A Regression Task B Classification
C Clustering D Outlier Detection
045. A______ captures a transaction, such as a customer’s purchase, a flight booking, or a B
user’s clicks on a web page.
A Web data B Transactional Data
 C Sparse Matrix D Ordinal Data
046. Which model of data warehouses makes join indexing more attractive for cross-table B
search?
A Snow flake B Star model
C Cube model D Conceptual model
047. ______ a data cube that stores only those cube cells with an aggregate value (e.g., A
count) that is above some minimum support threshold
A Iceberg cube B Apex cube
C Concept hierarchy D Virtual warehouse
048. For a cube with n dimensions, there are a total of _______ cuboids, including the base B
cuboid.
A n cuboids B 2n cuboids
C 1 cuboid D 2n cuboids
049. Which operator computes aggregates over all subsets of the dimensions specified in C
the operation?
A Select B Binary
C Data cube D average
050. The level –O D cuboid also called_____ C
A base cuboid B null cuboid
C apex cuboid D semi cuboid
051. Reducing the number of attributes to solve the high dimensionality problem is called as B
---------------------.
A Compression B Dimensionality reduction
C Transformation D Integration
052. Given the following measurements for the variable age: 18, 22, 25, 42, 28, 43, 33, 35, B
56, 28 What is the mean absolute deviation for the variable age: 18, 22, 25, 42, 28, 43,
33, 35, 56, 28
A 9.0 B 8.8
C 8.5 D 5.3
053. Association analysis is used to discover patterns that describe ------------------ B
associated features in the data Association analysis is used to discover patterns that
describe ------------------ associated features in the data.
A Largely B Strongly
C Fewer D lengthy
054. Amongst which of the following step is performed by data scientist after acquiring the D
data?
A Data Integration B Data Transformation
C Data Dredging D Data Cleaning
055. Integration requires a ------------------- step that ensures that only valid and useful results B
are incorporated into the decision support system Integration requires a -------------------
step that ensures that only valid and useful results are incorporated into the decision
support system Integration requires a _____ step that ensures that only valid and
useful results are incorporated into the decision support system.
A Pruning B Postprocessing
C Preprocessing D indexing
056. The left hand side of the association rule is called_____ C
A Consequent B Inference
C Antecedent D onset
057. Data that are of no interest to the data mining task is called as_____ D
A Noisy data B Missing data
C Changing data D Irrelevant data
058. Data can be updated in _____ environment B
A data mining B operational
C informational D visual
059. In --------------, the value of an attribute is examined as it varies over time. B
A Regression B Time Series Analysis
C Sequence Discovery D Classification
060. Capability of data mining is to build ______ models. A
A Predictive B Imperative
C Introspective D business
061. Examples of Nominal can be: A
A ID Numbers, eye color, zip codes B Rankings, taste of potato chips,
grades, height
C Calendar dates, temperatures in D The temperature in Kelvin, length,
celsius or Fahrenheit, phone numbers time, counts
062. ___ of data removes or reduces noise (by applying smoothing techniques) and the A
treatment of missing values.
A Data preprocessing B Data post processing
C Nullifying data D normalization
063. For a given transaction database T, a ___ is an expression of the form X => Y, where B
X and Y are subsets of A and X => Y holds with confidence , if % of transactions in D
support X also support Y.
A classification rule B association rule
C decision rule D inference
064. In webmining, _____ is used to know the order in which URLs tend to be accessed. D
A Clustering B Associations
C Classification D Sequential analysis
065. Research on mining multi-types of data is termed as____ D
A Meta B Digital
C Graphics D multimedia
066. DMQL stands for? A
A Data Mining Query Language B Dataset Mining Query Language
C DBMiner Query Language D Data Marts Query Language
067. __________ refers to the description and model regularities or trends for objects B
whose behavior changes over time.
A Outlier Analysis B Evolution Analysis
C Prediction D Classification
068. In Data Characterization, class under study is called as? C
A Study Class B Initial Class
C Target Class D Final Class
069. Examples of Ordinal can be: B
A ID Numbers, eye color, zip codes B Rankings, taste of potato chips,
grades, height
C Calendar dates, temperatures in D The temperature in Kelvin, length,
celsius or Fahrenheit, phone numbers time, counts
070. How many categories of functions involved in Data Mining? A
A 2 B 3
C 4 D 5
071. PCA is used to find __________. D
A Relationship between components B Linear regression
C Linear relation D Inter relation
072. PCA is a ________. B
A Non linear model B Linear model
C Continuous model D Repeated model
073. Correlation coefficient test is used to apply on _____ type of data. B
A Nominal data B Numeric data
C Complex data D Imaginary data
074. ________is a tool which is used to reduce the dimension of the data. A
 A Principal components analysis B Product Components analysis
C Chi-square test D Pre Complex analysis
075. Chi-square test is used perform for _____ type of data. A
A Nominal data B Numeric data
C Complex data D Imaginary data
076. Which of the following is a process of converting continuous data into categorical data? A
A Discretization B Specialization
C Classification D indexing
077. ______ refers to the phenomenon that many types ofdata analysis become C
significantly harder as the dimensionality of the dataincreases.
A Data Transformation B Binning
C Curse of Dimensionality D Partial Materialization
078. _____ is a process of converting given data into number of frequencies. C
A Integration B Normalization
C Binning D Clustering
079. _______ is process of combining of two or more objects into a single object. B
A Generalization B Aggregation
C Specialization D multitasking
080. ______ is a commonly used approach for selecting a subset of the data objects to be B
analyzed.
A Classification B Sampling
C Integration D Binning
081. A____ rule says that there can be no missing values between the lowest and highest A
values for the attribute, and that all values must also be unique.
A Unique B Consecutive
C Association D general
082. What is Summarization in data mining? D
A Setting up a target data B Data mining procedure to sort data
C A method to find data D To represent the derivate data with
visualization and reports.
083. Data about data is referred to as _____ C
A Mixed data B Information
C Meta data D Sample Data
084. In __________, data encoding schemes are applied so as to obtain a reduced or C
“compressed” representation of the original data
A Data Integration B Data Transformation
C Data Reduction D Data Consolidation
085. ______ is a step in data cleaning, that involves finding the “best” line to fit two A
attributes (or variables) so that one attribute can be used to predict the other.
A Regression B Clustering
C Binning D Noisy data handling
086. The data tuples used for chi-square test can be shown in _____ . C
A Multiplication B Bar chart
C Contingency tables D histograms
087. An attribute is ______ if it derives from one or more other attributes. A
A Redundant B Zero attribute
C Key attribute D Complex attribute
088. The process of matching up equivalent real-world entities from multiple data sources is D
called___
A Normalization B Indexing
C Materialization D Entity Identification Problem
089. Which tools use simple domain knowledge to detect errors and make corrections in the A
data?
A Data scrubbing B Data Auditing
 C Data Analytic D Data Reduction
090. _____ tools allow users to specify transforms through a graphical user interface (GUI). C
A Data Scrubbing B Migration Tools
C ETL Tools D Data Auditing
091. The analysis performed to uncover the interesting statistical correlation between B
associated -attributes value pairs are known as the _____
A data reduction B correlation
C normalization D pruning
092. Effect of one attribute value on a given class is independent of values of other attribute A
is called
A value independence. B class conditional independence.
C conditional independence. D unconditional independence.
093. Data transformation includes __________. A
A a process to change data from a B a process to change data from a
detailed level to a summary level. summary level to a detailed level.
C joining data from one source into D separating data from one source into
various sources of data. various sources of data.
094. 2
The statistic tests the hypothesis that A and B are _________, then there is no B
correlation between them.
A Dependent B Independent
C Null D garbage
095. Correlation coefficient is also called____ B
A Min-max coefficient B Pearson coefficient
C Wavelet coefficient D Zero coefficient
096. In which of the following sampling model, the exclusive partitions of the data set are C
obtained?
A Simple random sample with B Simple random sample without
replacement replacement
C Stratified sampling D Cluster sample
097. If each bucket in a histogram represents only a single attribute–value/frequency pair, A
the buckets are called ______
A Singleton buckets B Simple buckets
C Mixed buckets D Unique buckets
098. _____ models approximate discrete multidimensional probability distributions. C
A Linear regression B Non-linear regression
C Log linear regression D Polynomial regression
099. _______is a linear signal processing technique that, when applied to a data vector X, B
transforms it to a numerically different vector, X 0 , of wavelet coefficients
A PCA B Wavelet Transforms
C Attribute Subset Selection D Sampling
100. ______reduces the data set size by removing irrelevant or redundant attributes . C
A PCA B Wavelet Transforms
C Attribute Subset Selection D Sampling