Exam 9: Data Warehousing and Data Integration

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:

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Question 1

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What is the role of metadata in the three-layer data architecture?

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Question 2

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Metadata describe other data. There are three types of metadata used in the three-layer architecture:
1. Operational-describes the data in the operational systems that feed the enterprise data warehouse. May exist in different formats and is often poor quality.
2. Enterprise data warehouse metadata describe the reconciled data layer as well as the rules for extracting, transforming, and loading operational data into reconciled data.
3. Data mart metadata-describe the derived data layer and the rules for transforming reconciled data to derived data.

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

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Question 3

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Discuss the difference between transient data and periodic data.

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Question 4

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

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Question 5

Factless fact tables may apply when:

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Question 6

Discuss the ETL process.

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Question 7

What types of applications would benefit from real-time data warehousing?

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Question 8

One of the biggest challenges of the extraction process is managing changes in the source system.

(True/False)

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Question 9

Data reconciliation occurs in two stages, an initial load and subsequent updates.

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Question 10

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

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Question 11

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

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Question 12

Informational and operational data differ in all of the following ways EXCEPT:

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Question 13

Reconciled data are data that have been selected, formatted, and aggregated for end-user decision support applications.

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Question 14

What are some approaches to handling slowly changing dimensions?

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Question 15

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

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Question 16

There are six major steps to ETL.

(True/False)

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Question 17

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

(True/False)

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Question 18

A snowflake schema is usually heavily aggregated.

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Question 19

________ duplicates data across databases.

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Question 20

Showing 1 - 20 of 150

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:

What is the role of metadata in the three-layer data architecture?

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

Discuss the difference between transient data and periodic data.

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

Factless fact tables may apply when:

Discuss the ETL process.

What types of applications would benefit from real-time data warehousing?

One of the biggest challenges of the extraction process is managing changes in the source system.

Data reconciliation occurs in two stages, an initial load and subsequent updates.

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

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

Informational and operational data differ in all of the following ways EXCEPT:

Reconciled data are data that have been selected, formatted, and aggregated for end-user decision support applications.

What are some approaches to handling slowly changing dimensions?

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

There are six major steps to ETL.

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

A snowflake schema is usually heavily aggregated.

________ duplicates data across databases.

The Database Environment and Development Process

Modeling Data in the Organization

The Enhanced E-R Model

Logical Database Design and the Relational Model

Introduction to SQL

Advanced SQL

Databases in Applications

Physical Database Design and Database Infrastructure

Big Data Technologies

Analytics and Its Implications

Data and Database Administration With Focus on Data Quality

Distributed Databases

Object-Oriented Data Modeling

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