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Chapter 13 (MC)

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asdf Quiz on Chapter 13 (MC), created by . . on 09/12/2016.
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Question 1

Question
1.Implementing BI in an organization involves capturing not only business data (internal and external) but also the ____.
Answer
  • a.metadata
  • b.facts
  • c.information
  • d.rules

Question 2

Question
2.Analyzing decision support data to generate information is part of ____.
Answer
  • a.data warehousing
  • b.very large database systems
  • c.business intelligence
  • d.distributed processing

Question 3

Question
3.Data mining is part of the “____” section of the business intelligence framework.
Answer
  • a.Peopl
  • b.Management
  • c.Processes
  • d.Governance

Question 4

Question
4.A data mart is part of the “____” section of the business intelligence framework.
Answer
  • a.People
  • b.Management
  • c.Processes
  • d.Governance

Question 5

Question
5.____’s main goal is to provide a comprehensive and consistent definition of all data within an organization.
Answer
  • a.DBMS
  • b.OLAP
  • c.Data warehousing
  • d.MDM

Question 6

Question
6.The ____ contains business data extracted from the operational database and from external data sources.
Answer
  • a.data store
  • b.ETL tools
  • c.data visualization tool
  • d.data analysis tool

Question 7

Question
7.____ are in charge of presenting the data to the end user in a variety of ways.
Answer
  • a.Data stores
  • b.ETL tools
  • c.Data visualization tools
  • d.Data analysis tools

Question 8

Question
8.____provide a unified, single point of entry for information distribution.
Answer
  • a.Decision support systems
  • b.Portals
  • c.Data warehouses
  • d.Dashboards

Question 9

Question
9.Data is captured from the OLTP system and placed on the ____ on a near-real time basis.
Answer
  • a.decision support system
  • b.portal
  • c.data warehouse
  • d.dashboard

Question 10

Question
10.BusinessObjects is a(n) ____ tool
Answer
  • a.OLAP
  • b.data visualization
  • c.data mining
  • d.data warehouse

Question 11

Question
11.Had ____ been as pivotal to business operations a few years back, crises precipitated by the likes of Enron, WorldCom, and Arthur Andersen might have been avoided.
Answer
  • a.OLAP
  • b.data mining
  • c.governance
  • d.networking

Question 12

Question
12.____ systems provided no data extraction/integration process.
Answer
  • a.Third-generation Mobile BI and cloud-based
  • b.First-generation BI
  • c.First-generation departmental decision support
  • d.Traditional mainframe-based online transaction processing

Question 13

Question
13.From the data analyst’s point of view, decision support data differ from operational data in three main areas: time span, granularity, and ____.
Answer
  • a.usability
  • b.dimensionality
  • c.transaction processing
  • d.sparsity

Question 14

Question
14.A characteristic of decision support data is ____.
Answer
  • a.high query activity
  • b.high update volumes
  • c.highly normalized
  • d.low aggregation level

Question 15

Question
15.A characteristic of operational data is ____.
Answer
  • a.summarized data
  • b.hundreds of gigabytes
  • c.high normalization
  • d.historic data

Question 16

Question
16.In 2008, Wal-Mart, the world’s largest company, had over four ____ of data in its data warehouses.
Answer
  • a.megabytes
  • b.gigabytes
  • c.terabytes
  • d.petabytes

Question 17

Question
17.Data ____ implies that all business entities, data elements, data characteristics, and business metrics are described in the same way throughout the enterprise.
Answer
  • a.volatility
  • b.time-variation
  • c.subject-orientation
  • d.integration

Question 18

Question
18.____ can serve as a test vehicle for companies exploring the potential benefits of data warehouses.
Answer
  • a.Data networks
  • b.Data marts
  • c.Data cubes
  • d.OLAPs

Question 19

Question
19.There are 12 rules that define a(n) ____.
Answer
  • a.data warehouse
  • b.multidimensional cube
  • c.OLAP tool
  • d.star schema

Question 20

Question
20.The basic star schema has four components: facts, ____, attributes, and attribute hierarchies.
Answer
  • a.keys
  • b.relationships
  • c.cubes
  • d.dimensions

Question 21

Question
21.Computed or derived facts are sometimes called ____to differentiate them from stored facts.
Answer
  • a.details
  • b.attributes
  • c.metrics
  • d.fact tables

Question 22

Question
22.In a star schema, dimensions are normally stored in ____.
Answer
  • a.attributes
  • b.indexes
  • c.fact tables
  • d.dimension tables

Question 23

Question
23.In a star schema, attributes are often used to search, filter, or classify ____.
Answer
  • a.tables
  • b.stars
  • c.fact
  • d.dimensions

Question 24

Question
24.The ____ dimension of a data cube provides a framework from which sales patterns can be analyzed and possibly predicted.
Answer
  • a.time
  • b.cube
  • c.third
  • d.multi

Question 25

Question
25.The attribute hierarchy provides a top-down data organization that is used for two main purposes: ____and drilldown/roll up data analysis
Answer
  • a.hierarchy
  • b.de-normalization
  • c.normalization
  • d.aggregation

Question 26

Question
26.Fact and dimension tables are related by ____ keys.
Answer
  • a.shared
  • b.primary
  • c.foreign
  • d.linked

Question 27

Question
27.In a typical star schema, each dimension record is related to thousands of ____ records.
Answer
  • a.attribute
  • b.fact
  • c.key
  • d.star

Question 28

Question
28.A ____ schema is a type of star schema in which the dimension tables can have their own dimension tables.
Answer
  • a.snowflake
  • b.starflake
  • c.mesh
  • d.matrix

Question 29

Question
29.____splits a table into subsets of rows or columns and places the subsets close to the client computer to improve data access time
Answer
  • a.Normalization
  • b.Meta modeling
  • c.Replication
  • d.Partitioning

Question 30

Question
30.In a MOLAP system, the MOLAP ____ allows end users to interact with the MOLAP server and request data for analysis.
Answer
  • a.GUI
  • b.operational database
  • c.multidimensional database
  • d.data cube

Question 31

Question
31.The reliance on ____ as the design methodology for relational databases is seen as a stumbling block to its use in OLAP systems.
Answer
  • a.normalization
  • b.denormalization
  • c.star schema
  • d.multidimensional schema

Question 32

Question
32.Decision support data tend to be non-normalized, ____, and pre-aggregated.
Answer
  • a.unique
  • b.duplicated
  • c.relational
  • d.sorted

Question 33

Question
33.The ____ schema is designed to optimize data query operations rather than data update operations.
Answer
  • a.relational
  • b.circle
  • c.star
  • d.matrix

Question 34

Question
34.ROLAP extends ____ so that it can differentiate between access requirements for data warehouse data and operational data.
Answer
  • a.SQL
  • b.OLAP
  • c.DDS
  • d.BI

Question 35

Question
35.A ____ index is based on 0 and 1 bits to represent a given condition.
Answer
  • a.logical
  • b.multidimensional
  • c.star
  • d.bitmapped

Question 36

Question
36.Conceptually, MDBMS end users visualize the stored data as a three-dimensional cube known as a____.
Answer
  • a.multi cube
  • b.data matrix
  • c.data cube
  • d.hyper cube

Question 37

Question
37.A MOLAP system stores data in an MDBMS, using proprietary ____ and array technology to simulate the multidimensional cube.
Answer
  • a.table
  • b.matrix
  • c.network
  • d.cube

Question 38

Question
38.What is one of the main characteristics of OLAP systems?
Answer
  • a.They use single-dimensional data analysis techniques.
  • b.They provide complex command-line end-user interfaces.
  • c.They provide minimal database support.
  • d.They support client/server architecture.

Question 39

Question
39.What is a characteristic of ROLAP?
Answer
  • a.It uses the star schema
  • b.It does not require high resources.
  • c.It is limited to predefined dimensions.
  • d.It has low flexibility.

Question 40

Question
40.A(n) ____is a dynamic table that not only contains the SQL query command to generate the rows, but also stores the actual rows.
Answer
  • a.OLAP
  • b.materialized view
  • c.star schema
  • d.data cube
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