McGraw-Hill/Irwin ©2008 The McGraw-Hill Companies, All Rights Reserved DATABASES AND DATA WAREHOUSES Opening Case Searching for Revenue - Google DATABASES

McGraw-Hill/Irwin ©2008 The McGraw-Hill Companies, All Rights Reserved

DATABASES AND DATA

WAREHOUSES

Opening CaseSearching for

Revenue - Google

DATABASES AND DATA

WAREHOUSES

Opening CaseSearching for

Revenue - Google

CHAPTER 6CHAPTER 6

6-2

Chapter Six Overview

• SECTION 6.1 – DATABASE FUNDAMENTALS– Understanding Information– Database Fundamentals– Database Advantages– Relational Database Fundamentals– Database Management Systems– Integrating Data Among Multiple Databases

• SECTION 6.2 – DATA WARAEHOUSE FUNDAMENTALS– Accessing Organizational Information– History of Data Warehousing– Data Warehouse Fundamentals– Business Intelligence– Data Mining


SECTION 6.1SECTION 6.1

DATABASE FUNDAMENTALS


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LEARNING OUTCOMES

1. List, describe, and provide an example of each of the five characteristics of high quality information

2. Define the relationship between a database and a database management system

3. Describe the advantages an organization can gain by using a database.

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LEARNING OUTCOMES

4. Define the fundamental concepts of the relational database model

5. Describe the role and purpose of a database management system and list the four components of a database management system

6. Describe the two primary methods for integrating information across multiple databases

6-6

UNDERSTANDING INFORMATION

• Information is everywhere in an organization

• Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions

• Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing

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UNDERSTANDING INFORMATION

• Information granularity – refers to the extent of detail within the information (fine and detailed or coarse and abstract)– Levels– Formats– Granularities

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Information Quality

• Business decisions are only as good as the quality of the information used to make the decisions

• Characteristics of high quality information include:– Accuracy– Completeness– Consistency– Uniqueness– Timeliness

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Information Quality

• Low quality information example

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Understanding the Costs of Poor Information

• The four primary sources of low quality information include:

1. Online customers intentionally enter inaccurate information to protect their privacy

2. Information from different systems have different entry standards and formats

3. Call center operators enter abbreviated or erroneous information by accident or to save time

4. Third party and external information contains inconsistencies, inaccuracies, and errors

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Understanding the Costs of Poor Information

• Potential business effects resulting from low quality information include:– Inability to accurately track customers– Difficulty identifying valuable customers– Inability to identify selling opportunities– Marketing to nonexistent customers– Difficulty tracking revenue due to inaccurate

invoices– Inability to build strong customer relationships

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Understanding the Benefits of Good Information

• High quality information can significantly improve the chances of making a good decision

• Good decisions can directly impact an organization's bottom line

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• Information is everywhere in an organization

• Information is stored in databases– Database – maintains information about

various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

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• Database models include:– Hierarchical database model – information is

organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships

– Network database model – a flexible way of representing objects and their relationships

– Relational database model – stores information in the form of logically related two-dimensional tables

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DATABASE ADVANTAGES

• Database advantages from a business perspective include– Increased flexibility– Increased scalability and performance– Reduced information redundancy– Increased information integrity (quality)– Increased information security

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Increased Flexibility

• A well-designed database should:– Handle changes quickly and easily– Provide users with different views– Have only one physical view

• Physical view – deals with the physical storage of information on a storage device

– Have multiple logical views• Logical view – focuses on how users logically

access information

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Increased Scalability and Performance

• A database must scale to meet increased demand, while maintaining acceptable performance levels– Scalability – refers to how well a system can

adapt to increased demands– Performance – measures how quickly a

system performs a certain process or transaction

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Reduced Redundancy

• Databases reduce information redundancy– Redundancy – the duplication of information

or storing the same information in multiple places

• Inconsistency is one of the primary problems with redundant information

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Increased Integrity (Quality)

• Information integrity – measures the quality of information

• Integrity constraint – rules that help ensure the quality of information– Relational integrity constraint – rule that enforces

basic and fundamental information-based constraints– Business-critical integrity constraint – rule that

enforce business rules vital to an organization’s success and often require more insight and knowledge than relational integrity constraints

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Increased Security

• Information is an organizational asset and must be protected

• Databases offer several security features including:– Password – provides authentication of the user– Access level – determines who has access to the

different types of information – Access control – determines types of user access,

such as read-only access

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• Entity – a person, place, thing, transaction, or event about which information is stored– The rows in each table contain the entities– In Figure 6.5 CUSTOMER includes Dave’s Sub Shop

and Pizza Palace entities

• Entity class (table) – a collection of similar entities– In Figure 6.5 CUSTOMER, ORDER, ORDER LINE,

DISTRIBUTOR, and PRODUCT entity classes

RELATIONAL DATABASE FUNDAMENTALS

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• Attributes (fields, columns) – characteristics or properties of an entity class– The columns in each table contain the attributes– In Figure 6.5 attributes for CUSTOMER include:

• Customer ID• Customer Name• Contact Name• Phone


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• Primary keys and foreign keys identify the various entity classes (tables) in the database– Primary key – a field (or group of fields) that

uniquely identifies a given entity in a table– Foreign key – a primary key of one table that

appears an attribute in another table and acts to provide a logical relationship among the two tables


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Potential relational database for Coca-Cola

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DATABASE MANAGEMENT SYSTEMS

• Database management systems (DBMS) – software through which users and application programs interact with a database

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DATABASE MANAGEMENT SYSTEMS

• Four components of a DBMS

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Data Definition Component

• Data definition component – creates and maintains the data dictionary and the structure of the database

• The data definition component includes the data dictionary– Data dictionary – a file that stores definitions of

information types, identifies the primary and foreign keys, and maintains the relationships among the tables

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Data Definition Component

• Data dictionary essentially defines the logical properties of the information that the database contains

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Data Manipulation Component

• Data manipulation component – allows users to create, read, update, and delete information in a database

• A DBMS contains several data manipulation tools:– View – allows users to see, change, sort, and query the

database content– Report generator – users can define report formats – Query-by-example (QBE) – users can graphically

design the answers to specific questions– Structured query language (SQL) – query language

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• Sample report using Microsoft Access Report Generator

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• Sample report using Access Query-By-Example (QBE) tool

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• Results from the query in Figure 6.10

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• SQL version of the QBE Query in Figure 6.10

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Application Generation and Data Administration Components

• Application generation component – includes tools for creating visually appealing and easy-to-use applications

• Data administration component – provides tools for managing the overall database environment by providing faculties for backup, recovery, security, and performance

• IT specialists primarily use these components

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INTEGRATING DATA AMONG MULTIPLE DATABASES

• Integration – allows separate systems to communicate directly with each other– Forward integration – takes information

entered into a given system and sends it automatically to all downstream systems and processes

– Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and processes

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INTEGRATING DATAAMONG MULTIPLE DATABASES

• Forward and backward integration

6-37

INTEGRATING DATAAMONG MULTIPLE DATABASES

• Building a central repository specifically for integrated information

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OPENING CASE QUESTIONSGoogle

1. How did the Web site RateMyProfessors.com solve its problem of low-quality information?

2. Review the five common characteristics of high-quality information and rank them in order of importance to Google’s business

3. What would be the ramifications to Google’s business if the search information it presented to its customers was of low quality?

6-39


4. Describe the different types of databases. Why should Google use a relational database?

5. Identify the different types of entity, entity classes, attributes, keys, and relationships that might be stored in Google’s AdWords relational database


SECTION 6.2SECTION 6.2

DATA WAREHOUSE

FUNDAMENTALS

DATA WAREHOUSE

FUNDAMENTALS

6-41

LEARNING OUTCOMES

7. Describe the roles and purposes of data warehouses and data marts in an organization

8. Compare the multidimensional nature of data warehouses (and data marts) with the two-dimensional nature of databases

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LEARNING OUTCOMES

9. Identify the importance of ensuring the cleanliness of information throughout an organization

10.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

6-45


• 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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6-47

Multidimensional Analysis

• 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

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• Cube – common term for the representation of multidimensional information

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• 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

6-50

Information Cleansing or Scrubbing

• 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

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• Contact information in an operational system

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• Standardizing Customer name from Operational Systems

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• Accurate and complete information

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BUSINESS INTELLIGENCE

• Business intelligence – information that people use to support their decision-making efforts

• Principle BI enablers include:– Technology– People– Culture

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DATA MINING

• Data-mining software includes many forms of AI such as neural networks and expert systems

6-57

DATA MINING

• Common forms of data-mining analysis capabilities include:

– Cluster analysis– Association detection– Statistical analysis

6-58

Cluster Analysis

• Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

• CRM systems depend on cluster analysis to segment customer information and identify behavioral traits

6-59

Association Detection

• Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information

– Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services

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Statistical Analysis

• Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis

– Forecast – predictions made on the basis of time-series information

– Time-series information – time-stamped information collected at a particular frequency

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6. How could Google use a data warehouse to improve its business operations?

7. Why would Google need to scrub and cleanse the information in its data warehouse?

8. Identify a data mart that Google’s marketing and sales department might use to track and analyze its AdWords revenue

6-62

CLOSING CASE ONEFishing for Quality

1. Explain the importance of high-quality information for the Alaska Department of Fish and Game

2. Review the five common characteristics of high quality information and rank them in order of importance for the Alaska Department of Fish and Game

3. How could data warehouses and data marts be used to help the Alaska Department of Fish and Game improve the efficiency and effectiveness of its operations?

6-63

CLOSING CASE ONEFishing for Quality

4. What two data marts might the Alaska Department of Fish and Game want to build to help it analyze its operational performance?

5. Do the managers at the Alaska Department of Fish and Game actually have all of the information they require to make an accurate decision? Explain the statement “it is never possible to have all of the information required to make the best decision possible”

6-64

CLOSING CASE TWOMining the Data Warehouse

1. Explain how Ben & Jerry’s is using business intelligence tools to remain successful and competitive in a saturated market

2. Identify why information cleansing and scrubbing is critical to California Pizza Kitchen’s business intelligence tool’s success

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CLOSING CASE TWOMining the Data Warehouse

3. Illustrate why 100 percent accurate and complete information is impossible for Noodles & Company to obtain

4. Describe how each of the companies above is using BI from their data warehouse to gain a competitive advantage

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CLOSING CASE THREE Harrah’s

1. Identify the effects poor information might have on Harrah’s service-oriented business strategy

2. How does Harrah’s uses database technologies to implement its service-oriented strategy?

3. Harrah’s was one of the first casino companies to find value in offering rewards to customers who visit multiple Harrah’s locations. Describe the effects on the company if it did not build any integrations among the databases located at each of its casinos

6-67

4. Estimate the potential impact to Harrah’s business if there is a security breach in its customer information

5. Identify three different types of data marts Harrah’s might want to build to help it analyze its operational performance


6-68

6. What might occur if Harrah’s fails to clean or scrub its information before loading it into its data warehouse?

7. Describe cluster analysis, association detection, and statistical analysis and explain how Harrah’s could use each one to gain insights into its business


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McGraw-Hill/Irwin ©2008 The McGraw-Hill Companies, All Rights Reserved DATABASES AND DATA WAREHOUSES Opening Case Searching for Revenue - Google DATABASES