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Database > Chapter 9 > Flashcards

Chapter 9 Flashcards

1
Q

The analysis of summarized data to support decision making is called:

A

B) informational processing.

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2
Q

The characteristic that indicates that a data warehouse is organized around key high-level entities of the enterprise is:

A

A) subject-oriented.

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3
Q

When we consider data in the data warehouse to be time-variant, we mean:

A

B) data in the warehouse contain a time dimension so that they may be used to study

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4
Q

Which of the following advances in information systems contributed to the emergence of data warehousing?

A

A) Improvements in database technology, particularly the relational data model
B) Advances in computer hardware, especially affordable mass storage and parallel computer architectures
C) Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms
D) All of the above

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5
Q

Which of the following factors drive the need for data warehousing?

A

A) Businesses need an integrated view of company information.

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6
Q

Which of the following organizational trends does not encourage the need for data warehousing?

A

C) Downsizing

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7
Q

Informational systems are designed for all of the following EXCEPT:

A

A) running a business in real time.

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8
Q

Operational and informational systems are generally separated because of which of the following factors?

A

A) A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications.
B) A properly designed data warehouse adds value to data by improving their quality and consistency.
C) A separate data warehouse eliminates contention for resources that results when informational applications are confounded with operational processing.
D) All of the above.

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9
Q

A data mart is a(n):

A

C) data warehouse that is limited in scope.

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10
Q

One characteristic of independent data marts is complexity for end users when they need to access data in separate data marts. This complexity is caused by not only having to access data from separate databases, but also from:

A

A) the possibility of a new generation of inconsistent data systems, the data marts themselves.

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11
Q

All of the following are limitations of the independent data mart EXCEPT:

A

D) it is often more expedient to build a data mart than a data warehouse.

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12
Q

A dependent data mart:

A

B) is filled exclusively from the enterprise data warehouse with reconciled data.

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13
Q

An operational data store (ODS) is a(n):

A

C) integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users.

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14
Q

A logical data mart is a(n):

A

B) data mart created by a relational view of a slightly denormalized data warehouse.

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15
Q

All of the following are unique characteristics of a logical data mart EXCEPT:

A

C) the process of creating a logical data mart is lengthy.

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16
Q

The real-time data warehouse is characterized by which of the following?

A

A) It accepts near-real time feeds of transaction data.
B) Data are immediately transformed and loaded into the warehouse.
C) It provides near-real-time access for the transaction processing systems to an enterprise data warehouse.
D) All of the above.

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17
Q

________ technologies are allowing more opportunities for real-time data warehouses.

A

C) RFID

18
Q

All of the following are some beneficial applications for real-time data warehousing EXCEPT:

A

D) data entry.

19
Q

Data that are detailed, current, and intended to be the single, authoritative source of all decision support applications are called ________ data.

A

A) reconciled

20
Q

A database action that results from a transaction is called a(n):

A

B) event.

21
Q

Data that are never physically altered once they are added to the store are called ________ data.

A

C) periodic

22
Q

Which of the following is an objective of derived data?

A

A) ease of use for decision support systems
B) faster response time for user queries
C) support data mining applications
D) All of the above

23
Q

A star schema contains both fact and ________ tables.

A

C) dimension

24
Q

Every key used to join the fact table with a dimension table should be a ________ key.

A

B) surrogate

25
Q

The level of detail in a fact table determined by the intersection of all the components of the primary key, including all foreign keys and any other primary key elements, is called the:

A

B) grain.

26
Q

Conformed dimensions allow users to do the following:

A

A) share nonkey dimension data.
B) query across fact tables with consistency.
C) work on facts and business subjects for which all users have the same meaning.
D) all of the above.
Answer: D

27
Q

Factless fact tables may apply when:

A

A) we are tracking events.

C) we are taking inventory of the set of possible occurrences.

28
Q

An expanded version of a star schema in which all of the tables are fully normalized

A

A) snowflake schema.

29
Q

All of the following are ways to handle changing dimensions EXCEPT:

A

D) create a snowflake schema.

30
Q

________ is an ill-defined term applied to databases where size strains the ability of commonly used relational DBMSs to manage the data.

A

D) Big data

31
Q

________ is/are a new technology which trade(s) off storage space savings for

A

B) Column databases

32
Q

Advances in computer hardware, particularly the emergence of affordable mass storage and parallel computer architectures, was one of the key advances that led to the emergence of data warehousing.

A

TRUE

33
Q

The development of the relational data model did not contribute to the emergence of data warehousing.

A

FALSE

34
Q

The need for data warehousing in an organization is driven by its need for an integrated view of high-quality data.

A

TRUE

35
Q

When multiple systems in an organization are synchronized, the need for data warehousing increases.

A

FALSE

36
Q

Informational systems are designed to support decision making based on historical point-in-time and prediction data.

A

TRUE

37
Q

A separate data warehouse causes more contention for resources in an organization.

A

FALSE

38
Q

An independent data mart is filled with data extracted from the operational environment without the benefit of a data warehouse.

A

TRUE

39
Q

A data mart is a data warehouse that contains data that can be used across the entire organization.

A

FALSE

40
Q

Organizations adopt data mart architectures because it is easier to have separate, small data warehouses than to get all organizational parties to agree to one view of the organization in a central data warehouse.

A

TRUE

41
Q

Independent data marts do not generally lead to redundant data and efforts.

A

FALSE

42
Q

An enterprise data warehouse is the control point and single source of all data made available to end users for decision support applications.

A

TRUE

Database (6 decks)

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