Exam 13: Business Intelligence and Data Warehouses

______________________________ is a collection of concepts,techniques,and processes for the proper identification,definition,and management of data elements within an organization.

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Question 1

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Master data management
MDM
Master data management (MDM)

Describe the use of SQL in relation to ROLAP.

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Most decision support data requests require the use of multiple-pass SQL queries or multiple nested SQL statements.To Answer this criticism,ROLAP extends SQL so that it can differentiate between access requirements for data warehouse data (based on the star schema)and operational data (normalized tables).In that way,a ROLAP system is able to generate the SQL code required to access the star schema data.Query performance is also improved because the query optimizer is modified to identify the SQL code's intended query targets.For example,if the query target is the data warehouse,the optimizer passes the requests to the data warehouse.However,if the end user performs drill-down queries against operational data,the query optimizer identifies that operation and properly optimizes the SQL requests before passing them through to the operational DBMS.

The attribute hierarchy provides a top-down data organization that is used for two main purposes: ____ and drill-down/roll-up data analysis.

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MOLAP is a logical choice for companies that already use relational databases for their operational data.

(True/False)

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Question 4

Data ____________________ tools provide advanced visual analysis and techniques to enhance understanding of business data.

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Question 5

What is a data cube?

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Question 6

The decision support database query optimizer must be enhanced to support non-normalized structures.

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Question 7

____________________ are qualifying characteristics that provide additional perspectives to a given fact.

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Question 8

The basic star schema has four components: facts,____,attributes,and attribute hierarchies.

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Question 9

Data warehouse data are organized and summarized by table,such as CUSTOMER and ADDRESS.

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Question 10

A characteristic of operational data is ____.

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Question 11

The data warehouse designer must define common business dimensions that will be used by the data analyst to narrow a search,group information,or describe attributes.

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Question 12

____________________ is a measurement of the density of the data held in the data cube and is computed by dividing the total number of actual values in the cube by the total number of cells in the cube.

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Question 13

To support a(n)____________________ adequately,the DBMS might be required to use advanced hardware,such as multiple disk arrays,and even more importantly,to support multiple-processor technologies,such as a symmetric multiprocessor (SMP)or a massively parallel processor (MPP).

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Question 14

Conceptually,MDBMS end users visualize the stored data as a three-dimensional cube known as a ____.

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Question 15

____'s main goal is to provide a comprehensive and consistent definition of all data within an organization.

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Question 16

Normalizing fact tables improves data access performance and saves data storage space.

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Question 17

____________________ use Web-based technologies to present key business performance indicators or information in a single integrated view,generally using graphics in a clear,concise,and easy to understand manner.

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Question 18

The ____ schema is designed to optimize data query operations rather than data update operations.

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Question 19

Data ____ implies that all business entities,data elements,data characteristics,and business metrics are described in the same way throughout the enterprise.

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Question 20

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______________________________ is a collection of concepts,techniques,and processes for the proper identification,definition,and management of data elements within an organization.

Describe the use of SQL in relation to ROLAP.

The attribute hierarchy provides a top-down data organization that is used for two main purposes: ____ and drill-down/roll-up data analysis.

MOLAP is a logical choice for companies that already use relational databases for their operational data.

Data ____________________ tools provide advanced visual analysis and techniques to enhance understanding of business data.

What is a data cube?

The decision support database query optimizer must be enhanced to support non-normalized structures.

____________________ are qualifying characteristics that provide additional perspectives to a given fact.

The basic star schema has four components: facts,____,attributes,and attribute hierarchies.

Data warehouse data are organized and summarized by table,such as CUSTOMER and ADDRESS.

A characteristic of operational data is ____.

The data warehouse designer must define common business dimensions that will be used by the data analyst to narrow a search,group information,or describe attributes.

____________________ is a measurement of the density of the data held in the data cube and is computed by dividing the total number of actual values in the cube by the total number of cells in the cube.

To support a(n)____________________ adequately,the DBMS might be required to use advanced hardware,such as multiple disk arrays,and even more importantly,to support multiple-processor technologies,such as a symmetric multiprocessor (SMP)or a massively parallel processor (MPP).

Conceptually,MDBMS end users visualize the stored data as a three-dimensional cube known as a ____.

____'s main goal is to provide a comprehensive and consistent definition of all data within an organization.

Normalizing fact tables improves data access performance and saves data storage space.

____________________ use Web-based technologies to present key business performance indicators or information in a single integrated view,generally using graphics in a clear,concise,and easy to understand manner.

The ____ schema is designed to optimize data query operations rather than data update operations.

Data ____ implies that all business entities,data elements,data characteristics,and business metrics are described in the same way throughout the enterprise.

Database Systems

Data Models

The Relational Database Model

Entity Relationship (ER)Modeling

Advanced Data Modeling

Normalization of Database Tables

Introduction to Structured Query Language (SQL)

Advanced SQL

Database Design

Transaction Management and Concurrency Control

Database Performance Tuning and Query Optimization

Distributed Database Management Systems

Database Connectivity and Web Technologies

Database Administration and Security

Filters