databases and data warehouses

McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved

©2005 The McGraw-Hill Companies,

All rights reservedMcGraw-Hill/Irwin


CHAPTER 3CHAPTER 3

DATABASES AND DATA WAREHOUSES

DATABASES AND DATA WAREHOUSES

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OPENING CASE STUDYOPENING CASE STUDY

• Chrysler Spins a Competitive Advantage with Supply Chain Management Software

• Chapter 2 – supply chain management is a key business initiative

• Chrysler’s SCM is called SPIN, a Web-based system

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OPENING CASE STUDYOPENING CASE STUDY

• Behind SPIN are powerful databases• Databases store a wealth of information

– Inventory– Work-in-progress– Supplier information– Recall notices– Customer purchases

• This chapter – databases and data warehouses

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STUDENT LEARNING OUTCOMESSTUDENT LEARNING OUTCOMES

1. Describe business intelligence and its role2. Compare databases and data warehouses

by OLTP and OLAP3. List/describe key characteristics of a

relational database4. Define 5 software components of a DBMS

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STUDENT LEARNING OUTCOMESSTUDENT LEARNING OUTCOMES

5. List/describe key characteristics of a data warehouse

6. Define 4 major types of data-mining tools

7. List key considerations in managing information as a resource

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INTRODUCTIONINTRODUCTION

• Organizations need business intelligence

• Business intelligence (BI) – knowledge about your customers, competitors, business partners, competitive environment, and internal operations to make effective, important, and strategic business decisions

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• IT tools help process information to create business intelligence according to:– OLTP

– OLAP

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• Online transaction processing (OLTP) – the gathering of input information, processing that information, and updating existing information to reflect the gathered and processed information– Databases support OLTP

– Operational database – databases that support OLTP

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• Online analytical processing (OLAP) – the manipulation of information to support decision making– Databases can support some OLAP

– Data warehouses only support OLAP, not OLTP

– Data warehouses are special forms of databases that support decision making

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THE RELATIONAL DATABASE MODEL

THE RELATIONAL DATABASE MODEL

• There are many types of databases

• The relational database model is the most popular

• Relational database – uses a series of logically related two-dimensional tables or files to store information in the form of a database

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Databases Are…Databases Are…

• Collections of information

• Created with logical structures

• With logical ties within the information

• With built-in integrity constraints

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Databases – Collections of InformationDatabases – Collections of Information

• Databases have many tables

• Consider Solomon Enterprises that provides concrete to home and commercial builders. Tables or files include:– Order

– Customer

– Concrete Type

– Employee

– Truck

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Databases – Collections of InformationDatabases – Collections of Information

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Databases – Created with Logical Structures

Databases – Created with Logical Structures

• In databases, the row number is irrelevant

• Not true in spreadsheet software

• In databases, column names are very important. Column names are created in the data dictionary

• Data dictionary – contains the logical structure of the information in a database

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Databases – With Logical Ties Within the Information


• Logical ties must exist between the tables or files in a database

• Logical ties are created with primary and foreign keys

• Primary key – field (or group of fields in some cases) that uniquely describes each record

• Can you find primary keys in Figure 3.1 on page 129?

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• Foreign key – primary key of one file that appears in another file

• Foreign keys help you create logical ties within the information in a database

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Databases – With Built-In Integrity Constraints

Databases – With Built-In Integrity Constraints

• Integrity constraints – rules that help ensure the quality of the information

• Examples– Primary keys must be unique

– Foreign keys must be present

– Sales price cannot be negative

– Phone number must have area code

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DATABASE MANAGEMENT SYSTEM TOOLS


• Database management system (DBMS) – helps you specify the logical organization for a databases and access and use the information within a database– Word processing software = document

– Spreadsheet software = workbook

– DBMS software = database

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• 5 software components:1. DBMS engine

2. Data definition subsystem

3. Data manipulation subsystem

4. Application generation subsystem

5. Data administration subsystem

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DBMS EngineDBMS Engine

• DBMS engine – accepts logical requests from the various other DBMS subsystems, converts them into their physical equivalent, and actually accesses the database and data dictionary as they exist on a storage device

• DBMS engine separates the logical from the physical

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DBMS EngineDBMS Engine

• Physical view – how information is physically arranged, stored, and accessed on some type of storage device

• Logical view – how you as a knowledge worker need to arrange and access information

• With a database, you only concern yourself with your logical view

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Data Definition SubsystemData Definition Subsystem

• Data definition subsystem – helps you create and maintain the data dictionary and define the structure of the files in a database

• You must create a data dictionary before entering information into a database

• Module J covers this for Microsoft Access

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Data Manipulation SubsystemData Manipulation Subsystem

• Data manipulation subsystem – helps you add, change, and delete information

• This is your primary DBMS interface as you work with a database– Views

– Report generators

– QBE tools

– SQL

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ViewsViews

• View – allows you to see the contents of a database file– Make whatever changes you want

– Perform simple sorting

– Query to find the location of information

– Looks similar to a workbook with no row numbers

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ViewsViews

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Report GeneratorsReport Generators

• Report generator – helps you quickly define formats of reports and what information you want to see in a report

• You can save report formats and generate reports at any time with up-to-date information

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QBE ToolsQBE Tools

• Query-by-example (QBE) tool – helps you graphically design the answer to a question

• “What driver most often delivers concrete to Triple A Homes?”

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QBE ToolsQBE Tools

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SQLSQL

• Structured query language (SQL) – standardized fourth-generation language found in most DBMSs

• Performs the same task as a QBE tool– But uses a sentence structure instead of point-

and-click interface

• SQL is used mostly by IT people

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Application Generation SubsystemApplication Generation Subsystem

• Application generation subsystem – contains facilities to help you develop transaction-intensive applications– Data entry screen (called forms)

– Programming languages

• Used mostly by IT specialists

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Data Administration SubsystemData Administration Subsystem

• Data administration subsystem – helps you manage the overall database environment– Backup and recovery

– Security management

– Query optimization

– Concurrency control

– Change management

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• Backup and recovery– Periodically back up information

– Recover a database if a failure occurs

• Security management– Who has access to what information

– Who can perform certain tasks (e.g., add, change, or delete) on information

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• Query optimization– Restructure physical view of information to

optimize response times to queries

• Concurrency control– What happens if two people makes changes to

the same information at the same time?

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• Change management– What is the effect of structural changes to a

database?

– What if you add a new column?

– What happens if you delete a column?

– What happens if you change a column’s attributes?

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DATA WAREHOUSES AND DATA MINING

DATA WAREHOUSES AND DATA MINING

• Data warehouses support OLAP and decision making

• Data warehouses do not support OLTP

• Data-mining tools are the tools you use to work with a data warehouse– DBMS software = database

– Data-mining tools = data warehouse

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What Is a Data Warehouse?What Is a Data Warehouse?

• Data warehouse – logical collection of information – gathered from operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks

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• Multidimensional

• Rows and columns

• Also layers

• Many times called hypercubes

• What are the dimensions in Figure 3.8 on page 142?

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What Are Data-Mining Tools?What Are Data-Mining Tools?

• Data-mining tools – software tools that you use to query information in a data warehouse– Query-and-reporting tools

– Intelligence agents

– Multidimensional analysis tools

– Statistical tools

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What Are Data-Mining Tools?What Are Data-Mining Tools?

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Query-And-Reporting ToolsQuery-And-Reporting Tools

• Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment

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Intelligent AgentsIntelligent Agents

• Use various artificial intelligence tools such as neural networks and fuzzy logic to form the basis for “information discovery” and building business intelligence

• Help you find hidden patterns in information

• Chapter 4 focuses more on these

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Multidimensional Analysis ToolsMultidimensional Analysis Tools

• Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives– Bring new layers to the front

– Reorganize rows and columns

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Statistical ToolsStatistical Tools

• Help you apply various mathematical models to the information stored in a data warehouse to discover new information– Regression

– Analysis of variance

– And so on

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Data MartsData Marts

• Data warehouses can support all of an organization’s information

• Data marts have subsets of an organizationwide data warehouse

• Data mart – subset of a data warehouse in which only a focused portion of the data warehouse information is kept

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Data MartsData Marts

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Data Mining as a Career OpportunityData Mining as a Career Opportunity

• Knowledge of data mining can be a substantial career opportunity for you– Query and Analysis and Enterprise Analytic Tools

(Business Objects)

– Business Intelligence and Information Access tools (SAS)

– Many in Cognos (the data warehouse leader)

– PowerAnalyzer (Informatica)

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Considerations in Using a Data Warehouse

Considerations in Using a Data Warehouse

• Do you need a data warehouse?– Perhaps database OLAP is sufficient

• Do all employees need the entire data warehouse?– If no, build smaller data marts

• How up-to-date must the information be?

• What data-mining tools do you need?

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MANAGING THE INFORMATION RESOURCE


• Information is an organizational resource

• Just like people, capital, and equipment

• It must be managed effectively

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• Who should oversee your organization’s information resource?– Chief information officer (CIO) – oversees an

organization’s information resource

– Data administration – plans for, oversees the development of, and monitors the information resource

– Database administration – technical and operational aspects of managing information

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• Is information ownership a consideration?– If you create information, you “own” it

– You will also share it with others

– Because you “own” it, you are responsible for its quality

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• How “clean” must your information be?– Duplicate information (records) must be

eliminated

– Inaccurate information must be corrected

– Information forms the basis of business intelligence

– If your business intelligence is bad, you will make poor decisions

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CAN YOU…CAN YOU…

1. Describe business intelligence and its role2. Compare databases and data warehouses

by OLTP and OLAP3. List/describe key characteristics of a

relational database4. Define 5 software components of a DBMS

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CAN YOU…CAN YOU…

5. List/describe key characteristics of a data warehouse

6. Define 4 major types of data-mining tools

7. List key considerations in managing information as a resource


CHAPTER 3CHAPTER 3

End of Chapter 3End of Chapter 3

databases and data warehouses

Documents

information logical

powerful databases databases

manipulation of information

access information

database logical ties

process information

existing information

chapter databases