Deck 7: Accessing Organizational Information Data Warehouses
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Deck 7: Accessing Organizational Information Data Warehouses
1
A data warehouse is a central location in which data is stored and managed.
False
2
A data warehouse is a logical collection of information, gathered from many different operational databases, that supports business analysis activities and decision-making tasks.
True
3
A data miner contains a subset of data warehouse information.
False
4
ETL, within a data warehouse model, stands for exit, track, and load.
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5
A data mart contains a subset of data warehouse information.
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6
Dirty data is erroneous or flawed data.The complete removal of dirty data from a source is impractical or virtually impossible.
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7
The primary purpose of a data warehouse is to perform transactional processes.
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8
ETL stands for extraction, transformation, and loading.
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9
According to Gartner Inc., dirty data is an MIS problem, not a business problem.
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10
Data warehouses struggle with combining too much standardized information.
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11
One example of a data aggregation is to gather information about particular groups based on specific variables such as age, profession, or income.
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12
Within the data warehouse model, the external databases could include competitor information, industry information, and stock market analysis.
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13
The complete removal of dirty data from a source is practical and possible.
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14
Data aggregation is the collection of data from various sources for the purpose of data processing.
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15
Duplicate data, inaccurate data, misleading data, and incorrect data are all problems associated with dirty data.
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16
Within the data warehouse model, the internal databases could include marketing, sales, inventory, and billing.
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17
The primary purpose of a data warehouse is to perform analytical process.
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18
Information cleansing or scrubbing is a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information.
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19
A repository is a central location in which data is stored and managed.
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20
Dirty data is erroneous or flawed data.
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21
Competitive monitoring can compare two or more data sets to identify patterns and trends.
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22
A data map is a technique for establishing a match, or balance, between the source data and the target data warehouse.
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23
A data set is an organized collection of data.
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24
Organizational data includes simple structured data elements in a database.
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25
A data point is an individual item on a graph or chart.
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26
In a data warehouse, information cleansing occurs first during the ETL process and again once the information is in the data warehouse.
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27
Comparative analysis can help managers with competitive monitoring where a company keeps tabs of its competitor's activities on the web using software that automatically tracks all competitor website activities such as discounts and new products.
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28
Source data identifies the primary location where data is collected.It can include invoices, spreadsheets, timesheets, transactions, and electronic sources such as other databases.
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29
A comparative analysis can compare two or more data sets to identify patterns and trends.
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30
A data lake is a business that collects personal information about consumers and sells that information to other organizations.
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31
Many firms complete data quality audits to determine the accuracy and completeness of its data.
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32
A data broker is an individual item on a graph or a chart.
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33
Effective data-driven decision management is reliant upon the quality of the data gathered and the effectiveness of its analysis and interpretation.
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34
While a traditional data warehouse stores data in files or folders, a data lake uses a flat architecture to store data.
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35
A data lake is a storage repository that holds a vast amount of raw data in its original format until the business needs it.
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36
Many organizations find themselves in the position of being data rich and information poor.Even in today's electronic world, managers struggle with the challenge of turning their business data into business intelligence.
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37
The banking industry uses business intelligence to understand customer credit card usage and nonpayment rates.
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38
Business intelligence is an approach to business governance that values decisions that can be backed up with verifiable data.
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39
A data mart is the process of analyzing data to extract information not offered by the raw data alone.
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40
The financial industry uses business intelligence to predict hardware failures.
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41
Which of the following describes ETL?
A)A process that extracts information from internal and external databases.
B)A process that transforms information using a common set of enterprise definitions.
C)A process that loads information into a data warehouse.
D)All of these.
A)A process that extracts information from internal and external databases.
B)A process that transforms information using a common set of enterprise definitions.
C)A process that loads information into a data warehouse.
D)All of these.
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42
Which of the following statements is true regarding customer information?
A)Customer information can exist in several operational systems.
B)Customer information in each operational system could change.
C)Customer information in each operational system can be different.
D)All of these.
A)Customer information can exist in several operational systems.
B)Customer information in each operational system could change.
C)Customer information in each operational system can be different.
D)All of these.
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43
Within the beginning stage of the data warehouse models process, which of the following are included in the internal databases?
A)Marketing, sales, inventory, and billing.
B)Data mart 1, data mart 2, data mart 3.
C)Competitor and industry information, mailing lists, and stock market analysis.
D)Marketing information, and stock market analysis numbers.
A)Marketing, sales, inventory, and billing.
B)Data mart 1, data mart 2, data mart 3.
C)Competitor and industry information, mailing lists, and stock market analysis.
D)Marketing information, and stock market analysis numbers.
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44
Gender can be referred to in many ways (Male, Female, M/F, 1/0) in a data warehouse.Ensuring gender is referenced the same way is an example of ___________.
A)Information scaling
B)Streamlining data points
C)Standardizing information
D)Standardizing protocols
A)Information scaling
B)Streamlining data points
C)Standardizing information
D)Standardizing protocols
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45
Which of the following occurs during data cleansing?
A)Clean data marts
B)Clean redundant customer data
C)Clean accurate data
D)Clean correct data
A)Clean data marts
B)Clean redundant customer data
C)Clean accurate data
D)Clean correct data
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46
What is the ultimate outcome of a data warehouse?
A)Data goals
B)Data relationships
C)Data marketing
D)Data marts
A)Data goals
B)Data relationships
C)Data marketing
D)Data marts
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47
What is extraction, transformation, and loading?
A)It is a process of entering data, tracking data, and loading it into a database
B)It is a process that extracts information from internal and external databases, transforms it using a common set of enterprise definitions, and loads it into a data warehouse
C)It is a process that is performed at the end of the data warehouse model prior to putting the information in a cube
D)It is a process that is performed at the beginning of the data mining model
A)It is a process of entering data, tracking data, and loading it into a database
B)It is a process that extracts information from internal and external databases, transforms it using a common set of enterprise definitions, and loads it into a data warehouse
C)It is a process that is performed at the end of the data warehouse model prior to putting the information in a cube
D)It is a process that is performed at the beginning of the data mining model
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48
Which of the following contains a subset of data warehouse information?
A)Data miner
B)Data mart
C)Data pool
D)Data analyzing tool
A)Data miner
B)Data mart
C)Data pool
D)Data analyzing tool
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49
Which of the following is an example of an external database in the data warehouse model?
A)Marketing information
B)Sales information
C)Competitor information
D)All of these
A)Marketing information
B)Sales information
C)Competitor information
D)All of these
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50
Why were data warehouses created?
A)Numbers and types of operational databases increased as businesses grew.
B)Many companies had information scattered across multiple systems with different formats.
C)Completing reporting requests from numerous operational systems took days or weeks.
D)All of these.
A)Numbers and types of operational databases increased as businesses grew.
B)Many companies had information scattered across multiple systems with different formats.
C)Completing reporting requests from numerous operational systems took days or weeks.
D)All of these.
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51
Which of the following statements is true?
A)The more complete an organization wants its information to be, the less it costs.
B)The more accurate an organization wants its information to be, the less it costs.
C)The less accurate an organization wants its information to be, the more it costs.
D)The more complete and accurate an organization wants its information to be, the more it costs.
A)The more complete an organization wants its information to be, the less it costs.
B)The more accurate an organization wants its information to be, the less it costs.
C)The less accurate an organization wants its information to be, the more it costs.
D)The more complete and accurate an organization wants its information to be, the more it costs.
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52
What are the primary differences between a data warehouse and a data mart?
A)Data warehouses make quick decisions, data marts make slow decisions.
B)Data warehouse tackle ethical issues, data marts tackle hypothetical issues.
C)Data warehouses have a more organization wide focus, data marts have functional focus.
D)Data warehouses have a physical focus, data marts have logical focus.
A)Data warehouses make quick decisions, data marts make slow decisions.
B)Data warehouse tackle ethical issues, data marts tackle hypothetical issues.
C)Data warehouses have a more organization wide focus, data marts have functional focus.
D)Data warehouses have a physical focus, data marts have logical focus.
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53
Which of the following occurs during data cleansing?
A)Clean missing records
B)Clean redundant records
C)Clean inaccurate data
D)All of these
A)Clean missing records
B)Clean redundant records
C)Clean inaccurate data
D)All of these
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54
What do data warehouses support?
A)OLAP
B)Analytical processing
C)OLTP
D)OLAP and analytical processing
A)OLAP
B)Analytical processing
C)OLTP
D)OLAP and analytical processing
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55
Which of the following are examples of external databases in the data warehouse model?
A)Marketing, sales, inventory, and billing.
B)Data mart 1, data mart 2, and data mart 3.
C)Competitor and industry information, mailing lists, and stock market analysis.
D)Marketing information, sales information, and stock market analysis.
A)Marketing, sales, inventory, and billing.
B)Data mart 1, data mart 2, and data mart 3.
C)Competitor and industry information, mailing lists, and stock market analysis.
D)Marketing information, sales information, and stock market analysis.
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56
The primary purpose of a data warehouse is to _____________.
A)Combine strategic information
B)Organize departments
C)Interface between the computer and employees
D)All of these
A)Combine strategic information
B)Organize departments
C)Interface between the computer and employees
D)All of these
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57
Which of the following is incorrect in terms of data warehousing and business intelligence?
A)Information from other operational applications is not included.
B)Operational systems are integrated.
C)Operational information is mainly current.
D)Operational information frequently has quality issues.
A)Information from other operational applications is not included.
B)Operational systems are integrated.
C)Operational information is mainly current.
D)Operational information frequently has quality issues.
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58
A data set is an individual item on a graph or chart.
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59
A central location in which data is stored and managed is called a data mart.
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60
A data warehouse is a _________ collection of information, gathered from many different ___________ databases, that supports business analysis activities and decision-making tasks.
A)Logical, operational
B)Physical, operational
C)Logical, transactional
D)Physical, transactional
A)Logical, operational
B)Physical, operational
C)Logical, transactional
D)Physical, transactional
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61
Which of the following questions can be answered using business intelligence?
A)Where has the business been?
B)Where is the business now?
C)Where is the business going?
D)All of these.
A)Where has the business been?
B)Where is the business now?
C)Where is the business going?
D)All of these.
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62
Which of the following is a problem associated with dirty data?
A)Non formatted data
B)Misleading data
C)Incorrect data
D)All of these
A)Non formatted data
B)Misleading data
C)Incorrect data
D)All of these
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63
Companies can choose information cleansing software from several vendors.Which of the following is not a vendor mentioned in your text?
A)Oracle.
B)SAS.
C)Ascential Software.
D)McAffee.
A)Oracle.
B)SAS.
C)Ascential Software.
D)McAffee.
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64
Which of the following is not an information cleansing activity?
A)Identifies redundant records.
B)Identifies inaccurate or incomplete data.
C)Identifies missing records or attributes.
D)Identifies sales trends.
A)Identifies redundant records.
B)Identifies inaccurate or incomplete data.
C)Identifies missing records or attributes.
D)Identifies sales trends.
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65
Which of the following is a problem associated with dirty data?
A)Inaccurate data
B)Nonintegrated data
C)Violates business rules
D)All of these
A)Inaccurate data
B)Nonintegrated data
C)Violates business rules
D)All of these
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66
What is it called when a manager has too much data and information to make a decision?
A)Data rich, information poor
B)Data rich, content poor
C)Data rich, communication poor
D)Data rich, intelligence
A)Data rich, information poor
B)Data rich, content poor
C)Data rich, communication poor
D)Data rich, intelligence
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67
Business analysis is difficult from operational databases.Which of the following is a reason why?
A)Every department has its own method for recording data.
B)Data standards do not apply across departments.
C)The data, if available, were often incorrect or incomplete.
D)All of these.
A)Every department has its own method for recording data.
B)Data standards do not apply across departments.
C)The data, if available, were often incorrect or incomplete.
D)All of these.
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68
Which of the following is not a dirty data problem?
A)Duplicate data.
B)Inaccurate data.
C)Specific data.
D)Nonintegrated data.
A)Duplicate data.
B)Inaccurate data.
C)Specific data.
D)Nonintegrated data.
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69
Which of the following is a problem associated with dirty data?
A)Accurate data
B)Integrated data
C)Violates business rules
D)All of these
A)Accurate data
B)Integrated data
C)Violates business rules
D)All of these
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70
Which of the following is a problem associated with dirty data?
A)Inaccurate data
B)Misleading data
C)Non formatted data
D)All of these
A)Inaccurate data
B)Misleading data
C)Non formatted data
D)All of these
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71
Which of the following is a problem associated with dirty data?
A)Duplicate data
B)Incorrect data
C)Violates business rules
D)All of these
A)Duplicate data
B)Incorrect data
C)Violates business rules
D)All of these
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72
What is erroneous or flawed data?
A)Dirty data
B)Information cleansing
C)Information Scrubbing
D)ETL
A)Dirty data
B)Information cleansing
C)Information Scrubbing
D)ETL
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73
Which of the following is a problem associated with dirty data?
A)Formatted data
B)Misleading data
C)Correct data
D)All of these
A)Formatted data
B)Misleading data
C)Correct data
D)All of these
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74
What determines the accuracy and completeness of organizational data?
A)Data quantity audit
B)Data quality audit
C)Data intelligence audit
D)Data accuracy audit
A)Data quantity audit
B)Data quality audit
C)Data intelligence audit
D)Data accuracy audit
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75
What is information that people use to support their decision-making efforts?
A)Information cleansing and scrubbing
B)Data-mining tools
C)Data mining
D)Business intelligence
A)Information cleansing and scrubbing
B)Data-mining tools
C)Data mining
D)Business intelligence
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76
What is erroneous or flawed data?
A)Data set.
B)Dirty data.
C)Data map.
D)Data point.
A)Data set.
B)Dirty data.
C)Data map.
D)Data point.
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77
What is another term for information cleansing?
A)Information mining
B)Information scrubbing
C)Information scrapping
D)Information marts
A)Information mining
B)Information scrubbing
C)Information scrapping
D)Information marts
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78
Which of the following is a problem associated with dirty data?
A)Duplicate data
B)Correct data
C)Accurate data
D)All of these
A)Duplicate data
B)Correct data
C)Accurate data
D)All of these
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79
Business analysis is difficult to achieve from operational databases.Which of the following is not a reason why?
A)Inconsistent data definitions.
B)Lack of data standards.
C)Effective direct data access.
D)Poor data quality.
A)Inconsistent data definitions.
B)Lack of data standards.
C)Effective direct data access.
D)Poor data quality.
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80
Which of the following is the common term for the representation of multidimensional information?
A)Block
B)Square
C)Column
D)Cube
A)Block
B)Square
C)Column
D)Cube
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