1. CHAPTER 08 Accessing Organizational Information – Data Warehouse
McGraw-Hill/Irwin
Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.

2. LEARNING OUTCOMES
Describe the roles and purposes of data warehouses and data marts in an organization.
Explain the relationship between business intelligence and a data warehouse.
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3. 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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4. 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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5. 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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6. 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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7. MULTIDIMENSIONAL ANALYSIS AND DATA MINING
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8. 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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9. 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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10. INFORMATION SCRUBBING OR CLEANSING
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11. INFORMATION SCRUBBING OR CLEANSING
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12. 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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13. 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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