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CH 13 MC

Implementing BI in an organization involves capturing not only business data (internal and external) but also the ____.
Analyzing decision support data to generate information is part of ____.
business intelligence
Data mining is part of the “____” section of the business intelligence framework.
A data mart is part of the “____” section of the business intelligence framework.
____’s main goal is to provide a comprehensive and consistent definition of all data within an organization.
The ____ contains business data extracted from the operational database and from external data sources.
data store
____ are in charge of presenting the data to the end user in a variety of ways.
Data visualization tools
____ provide a unified, single point of entry for information distribution.
Data is captured from the OLTP system and placed on the ____ on a near-real time basis.
data warehouse
BusinessObjects is a(n) ____ tool.
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.
____ systems provided no data extraction/integration process.
Traditional mainframe-based online transaction processing
From the data analyst’s point of view, decision support data differ from operational data in three main areas: time span, granularity, and ____.
A characteristic of decision support data is ____.
high query activity
A characteristic of operational data is ____.
high normalization
In 2008, Wal-Mart, the world’s largest company, had over four ____ of data in its data warehouses.
Data ____ implies that all business entities, data elements, data characteristics, and business metrics are described in the same way throughout the enterprise.
____ can serve as a test vehicle for companies exploring the potential benefits of data warehouses.
Data marts
There are 12 rules that define a(n) ____.
data warehouse
The basic star schema has four components: facts, ____, attributes, and attribute hierarchies.
Computed or derived facts are sometimes called ____ to differentiate them from stored facts.
In a star schema, dimensions are normally stored in ____.
dimension tables
In a star schema, attributes are often used to search, filter, or classify ____.
The ____ dimension of a data cube provides a framework from which sales patterns can be analyzed and possibly predicted.
The attribute hierarchy provides a top-down data organization that is used for two main purposes: ____ and drill-down/roll-up data analysis.
Fact and dimension tables are related by ____ keys.
In a typical star schema, each dimension record is related to thousands of ____ records.
A ____ schema is a type of star schema in which the dimension tables can have their own dimension tables.
____ splits a table into subsets of rows or columns and places the subsets close to the client computer to improve data access time.
In a MOLAP system, the MOLAP ____ allows end users to interact with the MOLAP server and request data for analysis.
The reliance on ____ as the design methodology for relational databases is seen as a stumbling block to its use in OLAP systems.
Decision support data tend to be non-normalized, ____, and pre-aggregated.
The ____ schema is designed to optimize data query operations rather than data update operations.
ROLAP extends ____ so that it can differentiate between access requirements for data warehouse data and operational data.
A ____ index is based on 0 and 1 bits to represent a given condition.
Conceptually, MDBMS end users visualize the stored data as a three-dimensional cube known as a ____.
data cube
A MOLAP system stores data in an MDBMS, using proprietary ____ and array technology to simulate the multidimensional cube.
What is one of the main characteristics of OLAP systems?
They support client/server architecture
What is a characteristic of ROLAP?
It uses the star schema
A(n) ____ is a dynamic table that not only contains the SQL query command to generate the rows, but also stores the actual rows.
materialized view

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