McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Bachelor of Science in Computer Science TY (BSc CS) , Master of Science in Computer Science (MSc CS) , Bachelor of Science in Computer Science (BSc CS) .
| 51. |
............................. is the process of finding a model that describes and distinguishes data classes or concepts. |
| A. | data characterization |
| B. | data classification |
| C. | data discrimination |
| D. | data selection |
| Answer» A. data characterization | |
| 52. |
The full form of KDD is .................. |
| A. | knowledge database |
| B. | knowledge discovery database |
| C. | knowledge data house |
| D. | knowledge data definition |
| Answer» A. knowledge database | |
| 53. |
The out put of KDD is ............. |
| A. | data |
| B. | information |
| C. | query |
| D. | useful information |
| Answer» A. data | |
| 54. |
. The full form of OLAP is |
| A. | online analytical processing |
| B. | online advanced processing |
| C. | online advanced preparation |
| D. | online analytical performance |
| Answer» C. online advanced preparation | |
| 55. |
......................... is a subject-oriented, integrated, time-variant, nonvolatile collection or data in support of management decisions. |
| A. | data mining |
| B. | data warehousing |
| C. | document mining |
| D. | text mining |
| Answer» A. data mining | |
| 56. |
The data is stored, retrieved and updated in .................... |
| A. | olap |
| B. | oltp |
| C. | smtp |
| D. | ftp |
| Answer» B. oltp | |
| 57. |
An .................. system is market-oriented and is used for data analysis by knowledge workers, including managers, executives, and analysts. |
| A. | olap |
| B. | oltp |
| C. | both of the above |
| D. | none of the above |
| Answer» A. olap | |
| 58. |
........................ is a good alternative to the star schema. |
| A. | star schema |
| B. | snowflake schema |
| C. | fact constellation |
| D. | star-snowflake schema |
| Answer» A. star schema | |
| 59. |
The ............................ exposes the information being captured, stored, and managed by operational systems. |
| A. | top-down view |
| B. | data warehouse view |
| C. | data source view |
| D. | business query view |
| Answer» C. data source view | |
| 60. |
The type of relationship in star schema is ............... |
| A. | many to many |
| B. | one to one |
| C. | one to many |
| D. | many to one |
| Answer» A. many to many | |
| 61. |
The .................. allows the selection of the relevant information necessary for the data warehouse. |
| A. | top-down view |
| B. | data warehouse view |
| C. | data source view |
| D. | business query view |
| Answer» D. business query view | |
| 62. |
Which of the following is not a component of a data warehouse? |
| A. | metadata |
| B. | current detail data |
| C. | lightly summarized data |
| D. | component key |
| Answer» C. lightly summarized data | |
| 63. |
Which of the following is not a kind of data warehouse application? |
| A. | information processing |
| B. | analytical processing |
| C. | data mining |
| D. | transaction processing |
| Answer» D. transaction processing | |
| 64. |
Data warehouse architecture is based on ....................... |
| A. | dbms |
| B. | rdbms |
| C. | sybase |
| D. | sql server |
| Answer» B. rdbms | |
| 65. |
.......................... supports basic OLAP operations, including slice and dice, drill-down, roll-up and pivoting. |
| A. | information processing |
| B. | analytical processing |
| C. | data mining |
| D. | transaction processing |
| Answer» C. data mining | |
| 66. |
The core of the multidimensional model is the ....................... , which consists of a large set of facts and a number of dimensions. |
| A. | multidimensional cube |
| B. | dimensions cube |
| C. | data cube |
| D. | data model |
| Answer» B. dimensions cube | |
| 67. |
The data from the operational environment enter ........................ of data warehouse. |
| A. | current detail data |
| B. | older detail data |
| C. | lightly summarized data |
| D. | highly summarized data |
| Answer» A. current detail data | |
| 68. |
A data warehouse is ...................... |
| A. | updated by end users. |
| B. | contains numerous naming conventions and formats |
| C. | organized around important subject areas |
| D. | contain only current data |
| Answer» A. updated by end users. | |
| 69. |
Business Intelligence and data warehousing is used for .............. |
| A. | forecasting |
| B. | data mining |
| C. | analysis of large volumes of product sales data |
| D. | all of the above |
| Answer» B. data mining | |
| 70. |
Data warehouse contains ................ data that is never found in the operational environment. |
| A. | normalized |
| B. | informational |
| C. | summary |
| D. | denormalized |
| Answer» A. normalized | |
| 71. |
................... are responsible for running queries and reports against data warehouse tables. |
| A. | hardware |
| B. | software |
| C. | end users |
| D. | middle ware |
| Answer» D. middle ware | |
| 72. |
The biggest drawback of the level indicator in the classic star schema is that is limits ............ |
| A. | flexibility |
| B. | quantify |
| C. | qualify |
| D. | ability |
| Answer» B. quantify | |
| 73. |
............................. are designed to overcome any limitations placed on the warehouse by the nature of the relational data model. |
| A. | operational database |
| B. | relational database |
| C. | multidimensional database |
| D. | data repository |
| Answer» A. operational database | |
| 74. |
KDD describes the _________. |
| A. | whole process of extraction of knowledge from data |
| B. | extraction of data |
| C. | extraction of information |
| D. | extraction of rules |
| Answer» A. whole process of extraction of knowledge from data | |
| 75. |
SQL helps to find _______. |
| A. | the interesting data |
| B. | hidden information |
| C. | intermediate data |
| D. | data under constraints that are already known |
| Answer» D. data under constraints that are already known | |
| 76. |
Translation of problem to learning technique is called as _______. |
| A. | reengineering. |
| B. | translational engineering. |
| C. | representational engineering. |
| D. | learning algorithm. |
| Answer» C. representational engineering. | |
| 77. |
Which one of the following is not a part of empirical cycle in scientific research? |
| A. | Observation |
| B. | Theory. |
| C. | Self learning. |
| D. | Prediction. |
| Answer» C. Self learning. | |
| 78. |
________and __________ are the important qualities of good learning algorithm. |
| A. | Consistent, Complete. |
| B. | Information content, Complex. |
| C. | Complete, Complex. |
| D. | Transparent, Complex. |
| Answer» A. Consistent, Complete. | |
| 79. |
Redundancy refers to the elements of a message that can be derived from other parts of _________. |
| A. | different message. |
| B. | irrelevant message. |
| C. | same message. |
| D. | complete message. |
| Answer» C. same message. | |
| 80. |
Metadata describes __________. |
| A. | contents of database. |
| B. | structure of contents of database. |
| C. | structure of database. |
| D. | database itself. |
| Answer» B. structure of contents of database. | |
| 81. |
The partition of overall data warehouse is _______. |
| A. | database. |
| B. | data cube. |
| C. | data mart. |
| D. | operational data. |
| Answer» C. data mart. | |
| 82. |
__________ is used to load the information from operational database. |
| A. | Replication technique. |
| B. | Reengineering technique. |
| C. | Engineering technique. |
| D. | Transformation engineering. |
| Answer» A. Replication technique. | |
| 83. |
___________ multiprocessing machines share same hard disk and internal memory. |
| A. | Massively parallel. |
| B. | Symmetric. |
| C. | Parallel. |
| D. | Asymmetric. |
| Answer» B. Symmetric. | |
| 84. |
A trivial result that is obtained by an extremely simple method is called _______. |
| A. | naive prediction. |
| B. | accurate prediction. |
| C. | correct prediction. |
| D. | wrong prediction. |
| Answer» A. naive prediction. | |
| 85. |
The information on two attributes is displayed in ____________ in scatter diagram. |
| A. | visualization space. |
| B. | scatter space. |
| C. | cartesian space. |
| D. | interactive space. |
| Answer» C. cartesian space. | |
| 86. |
OLAP stands for ________. |
| A. | Online Analytical Processing. |
| B. | Online Linear Analytical Processing. |
| C. | Online Animated Process. |
| D. | Online Analytical Problem. |
| Answer» A. Online Analytical Processing. | |
| 87. |
K-nearest neighbor is one of the _______. |
| A. | learning technique. |
| B. | OLAP tool. |
| C. | purest search technique. |
| D. | data warehousing tool. |
| Answer» C. purest search technique. | |
| 88. |
The intermediate unit in perceptron is ________. |
| A. | photoreceptors. |
| B. | associators. |
| C. | responders. |
| D. | receptors. |
| Answer» B. associators. | |
| 89. |
OLAP is used to explore the ___________ knowledge. |
| A. | shallow. |
| B. | deep. |
| C. | multidimensional. |
| D. | hidden. |
| Answer» C. multidimensional. | |
| 90. |
A natural way to visualize the process of training a self-organizing map is called __________. |
| A. | kohonen movie. |
| B. | kohonen map. |
| C. | frame. |
| D. | scatter diagram. |
| Answer» A. kohonen movie. | |
| 91. |
Hidden knowledge can be found by using ________. |
| A. | searching algorithm. |
| B. | pattern recognition algorithm. |
| C. | searching algorithm. |
| D. | clues. |
| Answer» B. pattern recognition algorithm. | |
| 92. |
Deep knowledge can be found only by using ________. |
| A. | clues. |
| B. | OLAP. |
| C. | SQL. |
| D. | algorithm |
| Answer» A. clues. | |
| 93. |
The next stage to data selection in KDD process ______. |
| A. | enrichment. |
| B. | coding. |
| C. | cleaning. |
| D. | reporting. |
| Answer» C. cleaning. | |
| 94. |
Enrichment means ____. |
| A. | adding external data. |
| B. | deleting data. |
| C. | cleaning data. |
| D. | selecting the data. |
| Answer» A. adding external data. | |
| 95. |
The decision support system is used only for _______. |
| A. | cleaning. |
| B. | coding. |
| C. | selecting. |
| D. | queries. |
| Answer» D. queries. | |
| 96. |
In _________ approach data ware house is build first and all information needed is selected. |
| A. | top-down. |
| B. | client/server. |
| C. | bottom-up. |
| D. | DSS. |
| Answer» A. top-down. | |
| 97. |
The DB vendor who is able to operate massively parallel computers is ________. |
| A. | TCS. |
| B. | IBM. |
| C. | CTS. |
| D. | Wipro. |
| Answer» B. IBM. | |
| 98. |
Which of the following is closely related to statistical significance and transparency? |
| A. | Classification Accuracy. |
| B. | Transparency. |
| C. | Statistical significance. |
| D. | Search Complexity. |
| Answer» B. Transparency. | |
| 99. |
________ is a creative activity that has to be performed repeatedly in order to get best results. |
| A. | Cleaning |
| B. | Reporting |
| C. | Coding. |
| D. | Selection. |
| Answer» C. Coding. | |
| 100. |
_________ is an example for case based-learning. |
| A. | Decision trees. |
| B. | Neural networks. |
| C. | Genetic algorithm. |
| D. | K-nearest neighbor. |
| Answer» D. K-nearest neighbor. | |
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