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CHAPTER 08
Accessing Organizational
Information – Data
Warehouse
McGraw-Hill/Irwin
Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.
LEARNING OUTCOMES
1. Describe the roles and purposes of data
warehouses and data marts in an
organization.
2. Explain the relationship between business
intelligence and a data warehouse.
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HISTORY OF DATA WAREHOUSING
• Data warehouses extend the transformation of
data into information
• In the 1990’s executives became less
concerned with the day-to-day business
operations and more concerned with
overall business functions
• The data warehouse provided the
ability to support decision making
without disrupting the day-to-day operations
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DATA WAREHOUSE FUNDAMENTALS
• Data Warehouse—A logical collection of
information – gathered from many different
operational databases – that supports business
analysis activities and decision-making tasks
• The primary purpose of a data warehouse is to
aggregate information throughout an
organization into a single repository for
decision-making purposes
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DATA WAREHOUSE FUNDAMENTALS
• Extraction, Transformation, and Loading
(ETL)—A process that extracts information from
internal and external databases, transforms the
information using a common set of enterprise
definitions, and loads the information into a data
warehouse
• Data Mart—Contains a subset of data
warehouse information
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MULTIDIMENSIONAL ANALYSIS AND
DATA MINING
• Databases contain information in a series of
two-dimensional tables
• In a data warehouse and data mart, information
is multidimensional; it contains layers of
columns and rows
– Dimension—A particular attribute of
information
– Cube—Common term for the representation
of multidimensional information
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MULTIDIMENSIONAL ANALYSIS AND
DATA MINING
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MULTIDIMENSIONAL ANALYSIS AND DATA
MINING
• Data Mining—The process of analyzing data to
extract information not offered by the raw data
alone
• To perform data mining users need data-mining
tools
– Data-Mining Tool—Uses a variety of techniques to
find patterns and relationships in large volumes of
information and infers rules that predict future
behavior and guide decision making
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INFORMATION SCRUBBING OR
CLEANSING
• An organization must maintain high-quality data in the
data warehouse
• Information Cleansing or Scrubbing—A process that
weeds out and fixes or discards inconsistent,
incorrect, or incomplete information
• Looking at customer information highlights
why information cleansing is necessary
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INFORMATION SCRUBBING OR
CLEANSING
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INFORMATION SCRUBBING OR
CLEANSING
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BUSINESS INTELLIGENCE
• Business Intelligence—Information that people use to
support their decision-making efforts
• In modern businesses, increasing standards,
automation, and technologies have led to vast amounts
of available information
• Business Intelligence has now become the
art of sifting through large amounts of data,
extracting information, and turning that
information into actionable knowledge
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ENABLING BUSINESS INTELLIGENCE
• Competitive organizations accumulate business
intelligence to gain sustainable competitive
advantage
– Technology—The most significant enabler of
business intelligence
– People—This usually means a manager who is in
the field and close to the customer rather than an
analyst rich in data but poor in experience
– Culture—The extent to which the BI attitude
flourishes in an organization depends in large part on
the organization’s culture
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