Chapter 3 and Module CChapter 3 and Module C

DATABASES AND DATA DATABASES AND DATA WAREHOUSESWAREHOUSES

Building Business IntelligenceBuilding Business Intelligence

MORE CHERRIES PLEASEMORE CHERRIES PLEASE

Ben & Jerry’sBen & Jerry’s 190,000 pints of ice cream and 190,000 pints of ice cream and

frozen yogurtfrozen yogurt 50,000 grocery stores50,000 grocery stores In the U.S. and 12 other countriesIn the U.S. and 12 other countries Meticulously tracks every piece of Meticulously tracks every piece of

information on every pintinformation on every pint

MORE CHERRIES PLEASEMORE CHERRIES PLEASE

Noticed a problem with Cherry Garcia Noticed a problem with Cherry Garcia Ice CreamIce Cream

Complaints of not enough cherriesComplaints of not enough cherries Ben & Jerry’s could find no production Ben & Jerry’s could find no production

problemsproblems Eventually found that the wrong photo Eventually found that the wrong photo

was on the ice cream containerwas on the ice cream container Ben & Jerry’s analyzed all the Ben & Jerry’s analyzed all the

information to create business information to create business intelligenceintelligence

INTRODUCTIONINTRODUCTION Organizations need business Organizations need business

intelligenceintelligence Business intelligence (BI)Business intelligence (BI) – –

knowledge about your customers, knowledge about your customers, competitors, business partners, competitors, business partners, competitive environment, and competitive environment, and internal operations to make effective, internal operations to make effective, important, and strategic business important, and strategic business decisionsdecisions

INTRODUCTIONINTRODUCTION

IT tools help process information to IT tools help process information to create business intelligence create business intelligence according to…according to… OLTPOLTP OLAPOLAP

INTRODUCTIONINTRODUCTION Online transaction processing Online transaction processing

(OLTP)(OLTP) – the gathering and processing – the gathering and processing transaction information, and updating transaction information, and updating existing information to reflect the existing information to reflect the transactiontransaction Databases support OLTPDatabases support OLTP Operational databaseOperational database – databases that – databases that

support OLTPsupport OLTP Batch Processing – processing all of the Batch Processing – processing all of the

transactions at once; can be used to transactions at once; can be used to update a databaseupdate a database

INTRODUCTIONINTRODUCTION Online analytical processing Online analytical processing

(OLAP)(OLAP) – the manipulation of – the manipulation of information to support decision information to support decision makingmaking Databases can support some OLAPDatabases can support some OLAP Data warehouses only support OLAP, not Data warehouses only support OLAP, not

OLTPOLTP Data warehouses are special forms of Data warehouses are special forms of

databases that support decision makingdatabases that support decision making

OLTP, OLAP, and Business OLTP, OLAP, and Business IntelligenceIntelligence

THE RELATIONAL DATABASE THE RELATIONAL DATABASE MODELMODEL

There are many types of databasesThere are many types of databases The relational database model is the The relational database model is the

most popularmost popular

Relational databaseRelational database

Database CharacteristicsDatabase Characteristics

Collections of informationCollections of informationCreated with logical structuresCreated with logical structures Include logical ties within the Include logical ties within the informationinformation

Include built-in integrity constraintsInclude built-in integrity constraints

Database – Collection of Database – Collection of InformationInformation

Database – Logical Database – Logical StructureStructure

CharacterCharacter FieldField RecordRecord File (Table)File (Table) DatabaseDatabase Data WarehouseData Warehouse

Database – Physical Database – Physical StructureStructure

BitsBits BytesBytes WordsWords

Databases – Created with Databases – Created with Logical StructuresLogical Structures

Databases have many tablesDatabases have many tables In databases, the row number is In databases, the row number is

irrelevant; not true in spreadsheet irrelevant; not true in spreadsheet softwaresoftware

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

Database – Created with Database – Created with Logical StructuresLogical Structures

Data dictionary Data dictionary – contains the logical – contains the logical structure for the information in a databasestructure for the information in a database

Before you can enter information into a database, you must define the data dictionary for all the tables and their fields. For example, when you create the Truck table, you must specify that it will have three pieces of information and that Date of Purchase is a field in Date format.

Databases – With Logical Databases – With Logical Ties Within the InformationTies Within the Information

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

Logical ties are created with primary Logical ties are created with primary and foreign keysand foreign keys

Primary keyPrimary key Composite primary keyComposite primary key Foreign keyForeign key

Database – Logical Ties within Database – Logical Ties within the Informationthe Information

Customer Number is the primary key for Customer and appears in Order as a foreign key

Databases – With Built-In Databases – With Built-In Integrity ConstraintsIntegrity Constraints

Integrity constraintsIntegrity constraints – rules that help – rules that help ensure the quality of the informationensure the quality of the information

ExamplesExamples Primary keys must be uniquePrimary keys must be unique Foreign keys must be presentForeign keys must be present Sales price cannot be negativeSales price cannot be negative Phone number must have area codePhone number must have area code

Steps in Developing a Steps in Developing a DatabaseDatabase

Step 1: Define Entity Classes (tables) Step 1: Define Entity Classes (tables) and Primary Keysand Primary Keys

Step 2: Defining Relationships Step 2: Defining Relationships Among Entity ClassesAmong Entity Classes ERD (entity relationship diagram)ERD (entity relationship diagram) NormalizationNormalization

Step 3: Defining Information For Step 3: Defining Information For Each RelationEach Relation

Step 4: Use A Data Definition Step 4: Use A Data Definition Language To Create Your DatabaseLanguage To Create Your Database

DATABASE MANAGEMENT DATABASE MANAGEMENT SYSTEM TOOLSSYSTEM TOOLS

5 Components of a DBMS5 Components of a DBMS1.1. DBMS engineDBMS engine

2.2. Data definition subsystemData definition subsystem

3.3. Data manipulation subsystemData manipulation subsystem ViewsViews Report generatorsReport generators QBE toolsQBE tools SQLSQL

4.4. Application generation subsystemApplication generation subsystem

5.5. Data administration subsystemData administration subsystem

ViewView

Binoculars

Report GeneratorReport Generator

Query-by-Example ToolQuery-by-Example Tool

Structured Query LanguageStructured Query Language

SQLSQL – standardized fourth-generation – standardized fourth-generation query language found in most DBMSsquery language found in most DBMSs

Sentence-structure equivalent to QBESentence-structure equivalent to QBEMostly used by IT professionalsMostly used by IT professionalsNon-procedural language, which Non-procedural language, which makes it different from other makes it different from other programming languagesprogramming languages

DATA WAREHOUSES AND DATA WAREHOUSES AND DATA MININGDATA MINING

Data warehouses support OLAP and Data warehouses support OLAP and decision makingdecision making

Data warehouses do not support OLTPData warehouses do not support OLTP

Data warehouseData warehouse Data martData mart Data-miningData-mining

DATA WAREHOUSES AND DATA DATA WAREHOUSES AND DATA MININGMINING

Data MartsData Marts

Data-Mining ToolsData-Mining Tools

Data Warehouse Data Warehouse ConsiderationsConsiderations

Do you really need one, or does your Do you really need one, or does your database environment support all your database environment support all your functions?functions?

Do all employees need a big data Do all employees need a big data warehouse or a smaller data mart?warehouse or a smaller data mart?

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

What data-mining tools do you need?What data-mining tools do you need?

INFORMATION OWNERSHIPINFORMATION OWNERSHIP

Information is a resource you must Information is a resource you must manage and organize to help the manage and organize to help the organization meet its goals and organization meet its goals and objectivesobjectives

You need to considerYou need to consider Strategic management supportStrategic management support Sharing information with responsibilitySharing information with responsibility Information cleanlinessInformation cleanliness

Strategic Management Strategic Management SupportSupport

• Data administration Data administration – function – function that plans for, oversees the that plans for, oversees the development of, and monitors the development of, and monitors the information resourceinformation resource

• Database administration Database administration – – function responsible for the more function responsible for the more technical and operational aspects of technical and operational aspects of managing organizational informationmanaging organizational information

Sharing InformationSharing Information

Everyone can share – while not Everyone can share – while not consuming – informationconsuming – information

But someone must “own” it by But someone must “own” it by accepting responsibility for its quality accepting responsibility for its quality and accuracyand accuracy

Information CleanlinessInformation Cleanliness

Related to ownership and responsibility for Related to ownership and responsibility for quality and accuracyquality and accuracy

No duplicate informationNo duplicate informationNo redundant records with slightly No redundant records with slightly different data, such as the spelling of a different data, such as the spelling of a customer namecustomer name

GIGO – if you have garbage information GIGO – if you have garbage information you get garbage information for decision you get garbage information for decision making making