book

Oracle 10g Data Warehousing

by Lilian Hobbs, Susan Hillson, Shilpa Lawande, Pete Smith

April 2011

Beginner to intermediate

872 pages

20h 7m

English

Digital Press

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Copyright
Dedication
Related Titles from Digital Press
Foreword
Preface
Acknowledgments
1. Data Warehousing
1.1. An Introduction to Oracle Database 10g1.1.1. The Economic Climate Influences Technology Spending1.1.2. Consolidation1.1.3. Consolidation of the Hardware1.1.4. Consolidation of Data into a Single Company View1.1.5. Consolidation of Applications1.1.6. The g in Oracle Database 10g—The Grid1.2. What Is a Data Warehouse?1.2.1. Why Do You Need a Data Warehouse?1.3. A Historical Perspective1.3.1. The Rise of the Data WarehouseThe Data Warehouse Is Used to Look beyond the Data to Find InformationThe Data Warehouse Requires a Different Database Design1.3.2. Data Warehouses Evolved As Separate SystemsThe Data Warehouse Is Built from the Operational Systems1.3.3. The Data MartIndependent Data Marts Were BuiltOperational Data Stores Appeared To Consolidate Reporting of Recent InformationIncrementally Building The Data Warehouse With Dependent Data Marts1.3.4. Reporting, Query, and Analysis Tools Became Browser Based1.3.5. OLAP and Data Mining Functionality Are Embedded in the Oracle Database1.4. Data Warehousing Features in the Oracle Database 10g1.5. Building a Data Warehouse Poses Many Challenges1.5.1. Managing the Warehouse1.5.2. The Role of Metadata1.5.3. Increasing Data Volume1.5.4. Higher Availability1.5.5. More Users/Better Performance1.5.6. New Types Of Applications1.6. The Future of Data Warehousing1.6.1. Real-Time Data Warehouses1.6.2. The Disappearance of the Separate Data Warehouse1.7. Summary
2. Designing a Warehouse
2.1. Designing a Warehouse2.1.1. Don’t Use Entity Relationship (E-R) Modeling2.1.2. Dimensional Modeling2.1.3. Fact Table2.1.4. Dimension Table2.1.5. Warehouse Keys2.1.6. Normalizing the Data Warehouse2.1.7. Data Warehouse or Data Mart2.1.8. The Easy Shopping Inc. Example2.2. Other Design Considerations2.2.1. Design to Manage2.2.2. Design for Performance2.3. Implementing the Design2.3.1. Single Database or Many?2.3.2. Naming Conventions2.3.3. Database Configuration AssistantUsing a Preconfigured Database2.3.4. Which Schema?2.3.5. Data Files and Tablespaces2.3.6. Creating the Fact and Dimension Tables2.3.7. Constraints2.3.8. Indexes2.3.9. Partitioning2.3.10. Materialized Views2.3.11. SecurityObject PrivilegesRoleSystem Privileges2.3.12. Using the Parallel Option2.4. Testing the Design2.5. The Schema for Easy Shopping Inc.
3. Architecture of a Data Warehouse
3.1. Introduction3.2. Hardware Configurations for a Warehouse3.2.1. Server ArchitecturesThe Single-Processor, Single-Disk ArchitectureThe Multidisk ArchitectureThe Multiprocessor Server ArchitectureClustered ServersMassively Parallel Processor Architectures3.2.2. The Oracle Database ArchitectureThe Oracle Instance and DatabaseThe Scalable Database: Oracle Database 10g RACOracle Database 10g Grid3.3. Hardware Components3.3.1. Memory3.3.2. Processors3.3.3. Storage Configurations for a WarehouseThe I/O SubsystemStriping and RAIDStripe and Mirror EverythingShared Storage3.4. Automatic Storage Management3.4.1. ASM Overview3.4.2. Administering ASMSetting up ASMConfiguring ASM during InstallationManaging ASM from the Command LineManaging ASM from Enterprise Manager Grid Control3.4.3. Using ASM in the Warehouse3.5. File Management in Oracle3.5.1. Oracle Managed Files3.5.2. Bigfiles and Big Databases3.6. Summary
4. Physical Design of the Data Warehouse
4.1. Introduction4.2. Data Partitioning4.2.1. How to Partition Data?4.2.2. Range Partitioning4.2.3. Hash Partitioning4.2.4. List Partitioning4.2.5. Composite PartitioningRange-Hash PartitioningRange-List Partitioning4.2.6. Multicolumn Partition Keys4.2.7. Choosing the Partitioning Method4.2.8. Partitioning Using Oracle Enterprise Manager4.2.9. Partition Maintenance Operations4.3. Indexing4.3.1. B*tree Indexes4.3.2. Bitmapped Indexes4.3.3. Bitmapped Join Indexes4.3.4. Function-based Indexes4.3.5. Partitioned IndexesGlobal IndexesLocal IndexesPrefixed Local IndexesNonprefixed Local Indexes4.3.6. Which Indexes to Create?Deciding between Local and Global IndexesNeed Help Deciding Which Indexes to Create?4.3.7. Using Oracle Enterprise Manager to Create Indexes4.4. Index-Organized Tables4.4.1. Creating an IOT4.4.2. Partitioning and Indexing an IOT4.4.3. Using an IOT in a Data Warehouse4.5. Data Compression4.5.1. Table Compression4.5.2. Index Compression4.6. Summary
5. Loading Data into the Warehouse
5.1. The ETL Process5.2. Extracting Data from the Operational Systems5.2.1. Identifying Data That Has Changed5.2.2. Oracle Change Data CapturePublishing Change DataSynchronous CDCAsynchronous CDCSubscribing to Change DataCreating a SubscriptionProcessing the Change DataStep 1: Extend the windowStep 2: Select Data from the Subscriber ViewStep 3: Purge the WindowEnding the SubscriptionTransporting the Changes to the Staging Area5.3. Transforming the Data into a Common Representation5.3.1. Integrating Data from Multiple Sources5.3.2. Cleansing Data5.3.3. Deriving New Data5.3.4. Generating Warehouse Keys5.3.5. Choosing the Optimal Place to Perform the Transformations5.4. Loading the Warehouse5.4.1. Using SQL*Loader to Load the WarehouseUsing Oracle Enterprise Manager Load WizardThe Control File5.4.2. The Data FileSQL*Loader Modes of OperationData Load OptionsScheduling the Load OperationMonitoring Progress of the Load OperationInspecting the SQL*Loader LogOptimizing SQL*Loader PerformanceSQL*Loader Direct Path Load of a Single PartitionStep 1: Create a TablespaceStep 2: Add a PartitionStep 3: Disable All Referential Integrity Constraints and TriggersStep 4: Load the DataStep 5: Inspect the LogStep 6: Reenable All Constraints and Triggers, Rebuild IndexesSQL*Loader Parallel Direct Path LoadStep 1: Disable All Constraints and TriggersStep 2: Drop all IndexesStep 3: Load the DataStep 4: Inspect the LogStep 5: Reenable All Constraints and Triggers, Recreate All IndexesTransformations Using SQL*LoaderSQL*Loader Postload OperationsStep 1: Inspect the LogsStep 2: Process the Load ExceptionsStep 3: Reenable Data Integrity ConstraintsStep 4: Handle Constraint ViolationsStep 5: Enabling Constraints without ValidationCheck for Unusable IndexesRebuild unusable indexes5.4.3. Loading the Warehouse Using Data PumpData Pump Import/Export—impdp and expdpSpecifying the Location of the Datafile and Log Files for Data Pump ToolsMoving Data between DatabasesImproved Job Monitoring and Control5.4.4. Loading the Warehouse Using External TablesCreating an External TableAccessing Data Stored in an External TableLoading Data From an External TableLoading Data in Parallel Using External TablesUsing Data Pump External Tables to Move and Load Data5.4.5. Loading the Warehouse Using Transportable TablespacesStep 1: Create a Tablespace in the OLTP SystemStep 2: Move the Data for April 2004 into a Table in the Newly Created TablespaceStep 3: Alter the Tablespace So That It Is Read-OnlyStep 4: EXPORT the MetadataStep 5: Convert the Datafiles (Optional)Step 6: Transport the TablespaceStep 7: Import the MetadataStep 8: Alter the Tablespace to Read/Write5.4.6. Loading the Dimensions Using SQL MERGE5.5. Transformations inside the Oracle Database5.5.1. Transformations That Cleanse Data and Derive New DataProcessing With More Power: The REGEXP FunctionsRegular Expression Basics and SearchingRegular Expressions and SubstringsRegular Expressions to Manipulate Data5.5.2. Validating Data Using a Dimension5.5.3. Looking up the Warehouse Key5.5.4. Table Functions5.5.5. Transformations That Split One Data Source into Multiple Targets5.5.6. Moving Data from a Staging Table into the Fact TableStep 1: Create a New Tablespace for the Jan Purchases and the Jan Purchases IndexStep 2: Add a Partition to the Purchases TableStep 3: Move the table into the new partitionMoving Data Using Exchange PartitionMoving Data Between Tables Using Direct Path InsertCreating a New Table Using Create Table As Select5.6. Postload Operations5.6.1. Step 1: Gather Optimizer Statistics for the Tables5.6.2. Step 2: Verify the Dimensions5.6.3. Step 3: Refresh the materialized views5.6.4. Step 4: Gather Optimizer Statistics for the Materialized Views5.6.5. Step 5: Back up the Database Table, or Partition5.6.6. Step 6: Publish the Data5.7. Using Tools for the ETL process5.8. Summary

6. Querying the Data Warehouse
6.1. Introduction6.2. The Query Optimizer6.2.1. EXPLAIN PLAN6.2.2. Join Method BasicsNested Loops JoinSort-Merge JoinHash JoinHow to Pick the Join Method?6.2.3. Star Transformation6.2.4. Partition PruningRange PartitioningHash PartitioningList PartitioningComposite Partitioning6.2.5. Partition-Wise Join6.3. Parallel Execution6.3.1. SQL Statements That Can Be Parallelized6.3.2. Setting up Parallel Execution6.3.3. Hardware Requirements for Parallel Execution6.4. SQL Features for Querying the Data Warehouse6.4.1. SQL Extensions for AggregationCUBEROLLUPGROUPING SETSGROUPING and GROUPING_ID FunctionsUser-Defined Aggregates6.4.2. SQL Functions for AnalysisRanking FunctionsPARTITION BY ClauseRelative Ranking FunctionsWIDTH_BUCKET FunctionPeriod-over-Period Comparison Functions—LAG and LEADWindow Aggregate FunctionsSpecifying a Logical WindowConverting Sparse Data into Dense FormOUTER JOINPartition Outer JoinReporting AggregatesFirst and Last FunctionsInverse PercentileHypothetical RANK and Distribution FunctionsStatistical Analysis FunctionsDBMS_STATS_FUNC PackageCASE ExpressionWITH Clause6.4.3. The SQL Model ClauseA Simple CalculationMore about RULESCell ReferencingUPDATE versus UPSERTRule OrderingIterationSome Examples of the SQL Model Clause6.5. Summary
7. Summary Management
7.1. Summary Tables7.1.1. Why Do You Need Summary Management?7.1.2. Summary Management with Oracle7.2. Creating a Materialized View7.2.1. Naming the Materialized View7.2.2. The Physical Storage for the Materialized View7.2.3. When Should the Materialized View Be Populated with Data?7.2.4. How Should the Materialized View Be Refreshed?7.2.5. When should the Materialized View be refreshed?7.2.6. Enabling the Materialized View for Query Rewrite7.2.7. Specifying the Contents of the Materialized View7.2.8. Creating a Materialized View in Enterprise Manager7.2.9. Using Summary Management with Existing Summary Tables7.2.10. Partitioning the Materialized View7.2.11. Indexing the Materialized View7.2.12. Security of Materialized Views7.3. Refresh7.3.1. Using the DBMS_MVIEW Refresh Procedures7.3.2. Using Enterprise Manager for Refresh7.3.3. Fast RefreshFast Refresh Using Materialized View LogsMaterialized View Log OptionsUsing Oracle Enterprise Manager to Define Materialized View LogsOther Requirements for Fast Refresh7.3.4. Partition Change TrackingWhen and How to Perform PCT RefreshCreating a Materialized View That Supports PCT RefreshJoin Dependency ExpressionPartition KeyPartition Marker7.3.5. Refresh PerformanceOptimizer StatisticsSet the Parameter atomic_refresh to FALSEUse PCT Refresh and Partitioned Materialized ViewsUse Parallel ExecutionBuild and Refresh Multiple Materialized Views Using REFRESH_ALLEnable Query Rewrite during Refresh7.3.6. Nested Materialized ViewsWhy Use Nested Materialized Views?Refreshing Nested Materialized Views7.4. EXPLAIN_MVIEW Utility7.4.1. Running EXPLAIN_MVIEW procedure7.4.2. Using Oracle Enterprise Manager to run EXPLAIN_MVIEW7.5. TUNE_MVIEW Utility7.6. Summary
8. Dimensions
8.1. Concepts8.2. Creating a Dimension8.2.1. Defining a Dimension with a Single Hierarchy8.2.2. Defining a Dimension with Multiple Hierarchies8.2.3. Defining a Dimension with Attributes8.2.4. Defining a Dimension with Normalized Tables8.2.5. Creating Dimensions with Oracle Enterprise Manager8.3. Describing a Dimension8.4. Validating a Dimension8.5. Summary
9. Query Rewrite
9.1. Setting up Query Rewrite9.1.1. How Can We Tell If a Query Was Rewritten?9.2. Types of Query Rewrite9.2.1. SQL Text Match9.2.2. Aggregate Rollup9.2.3. Join-back9.2.4. Computing Other Aggregates in the Query9.2.5. Filtered Data9.2.6. Rewrite Using Materialized Views with No Aggregation9.2.7. Rewrite Using DimensionsUsing the HIERARCHY ClauseUsing the ATTRIBUTE Clause9.2.8. Rewrite Using ConstraintsUsing the NOVALIDATE and RELY Clauses on Constraints9.3. Query Rewrite Integrity Modes9.3.1. Comparing ENFORCED and TRUSTED Modes9.3.2. Comparing TRUSTED and STALE_TOLERATED Modes9.4. Query Rewrite and Partition Change Tracking9.4.1. Query Rewrite with PCT Using Partition Key9.4.2. Query Rewrite Using PCT with Partition Marker9.5. Troubleshooting Query Rewrite with EXPLAIN_REWRITE9.6. Advanced Query Rewrite Techniques9.6.1. Optimizer Hints for Query RewriteForcing an Error When Query Rewrite Is Not Possible9.6.2. Query Rewrite and Bind Variables9.6.3. Query Rewrite with Complex SQL ConstructsSet OperatorsSubqueries in the FROM ClauseMultiple Occurrences of a Table in the FROM ClauseGrouping SetsAnalytical Functions9.6.4. Query Rewrite Using Nested Materialized Views9.6.5. Rewrite Equivalences9.6.6. Using Query Rewrite during Refresh9.7. Summary
10. Tuning Query Performance
10.1. Monitoring Performance10.1.1. SQL Tuning SetsCreating a SQL Tuning Set in Oracle Enterprise ManagerCreating a SQL Tuning Set Using the DBMS_SQLTUNE Package10.2. Advisor Central10.3. SQL Access Advisor10.3.1. SQL Access Advisor WizardChoosing a Workload SourceSpecifying Tuning ParametersGenerating RecommendationsViewing the Results of the AnalysisRecommendations ViewSQL Statement ViewImplementing the Recommendations10.3.2. DBMS_ADVISOR PL/SQL PackageStep 1: Creating a Workload Named MY_WORKLOADStep 2: Specifying Workload Parameters for FilteringStep 3: Load Workload StatementsStep 4: Create a SQL Access Advisor Task and Set ParametersStep 5: Create a Link between Workload and TaskStep 6: Execute the Task to Generate Recommendations10.3.3. TemplatesStep1: Defining a TemplateStep2: Create a Task Using the Template10.3.4. Quick_Tune10.4. SQL Tuning Advisor10.4.1. SQL Tuning Advisor in Enterprise ManagerProfiles10.4.2. The DBMS_SQLTUNE PL/SQL Package10.5. Memory Advisor10.5.1. Tuning PGA MemoryMonitoring PGA Memory UsageTuning PGA_AGGREGATE_TARGET10.5.2. SGA Memory AdvisorShared Pool AdviceBuffer Cache Advice10.6. Troubleshooting Parallel Execution10.6.1. Using EXPLAIN PLAN to Display Parallel Plans10.6.2. Problems Due to Resource Constraints10.7. Plan Stability10.7.1. Creating an Outline10.7.2. Using an Outline10.8. Summary
11. Managing the Warehouse
11.1. What Has to Be Managed11.2. Managing Using Oracle Enterprise Manager11.2.1. The Enterprise Manager Console11.2.2. Overview of Enterprise Manager11.2.3. Enterprise Manager Database ControlHomePerformanceAdministrationMaintenance11.2.4. Enterprise Manager Grid Control11.2.5. Enterprise Manager Administrators11.2.6. Creating and Using Groups11.2.7. Scheduling JobsThe Oracle Database 10g SchedulerEnterprise Manager Job System11.3. Monitoring the Warehouse11.3.1. Automatic Workload Repository (AWR)11.3.2. Automatic Database Diagnostic Monitor (ADDM)11.3.3. Using Alerts11.4. Reorganizing the Warehouse11.4.1. Why Reorganize?11.4.2. Partition MaintenanceRolling Window Partition MaintenanceExchanging a PartitionMerging PartitionsSplitting PartitionsCoalescing Hash PartitionsTruncating PartitionsMoving PartitionsPartitions Facilitate Management11.4.3. Index Changes11.4.4. Online Redefinition of TablesOnline Redefinition via Enterprise ManagerOnline Redefinition Using the DBMS_REDEFINITION PackageStep 1: Create an Interim TableStep 2: Start the Redefinition ProcessStep 3: Create the Dependant ObjectsStep 4: Synchronize the TablesStep 5: Finish the RedefinitionStep 6: Gather Statistics on the Redefined Table11.4.5. Online Segment Shrink11.5. Refreshing the Warehouse11.6. Gathering Optimizer Statistics11.6.1. Automatic Statistics Collection11.6.2. Manual Statistics Collection11.6.3. Collecting System Statistics11.6.4. Dynamic Sampling11.7. Parallel Management Tasks11.8. Maintaining Security11.8.1. Virtual Private Database11.9. Monitoring Space Usage11.9.1. Automated Space Management11.9.2. Resumable Space Allocation11.10. Other Management Issues11.10.1. Building a Test System11.10.2. Testing New Software11.10.3. Timing Data Loads11.10.4. Evaluating/Practicing Management Tasks11.10.5. Determine Query Response Times11.11. Summary
12. Backup and Recovery
12.1. Strategy12.1.1. Methods of Performing a Backup and RecoveryBackupLogical BackupPhysical BackupIncremental BackupsBlock Change TrackingRestore and Recovery12.1.2. Simplifying Recovery with Flash Recovery AreaSetting up the Flash Recovery Area12.2. Backup12.2.1. Creating a Backup Configuration12.2.2. Full BackupsPredefined Backup Strategy12.2.3. Incremental Backups12.2.4. Tablespace Backups12.2.5. Backup File Sizes12.3. The Recovery Catalog12.3.1. Creating the Recovery Catalog12.3.2. Registering the EASYDW database with RMAN12.4. Restore and Recover12.5. Summary
13. Oracle Warehousing Tools
13.1. Which Tool13.2. Oracle Warehouse Builder13.2.1. Setting up Warehouse Builder13.2.2. Oracle Warehouse Builder Client13.2.3. Data Sources and TargetsOracle Database SourceOracle Database TargetFile Data Source13.2.4. Defining the Tables in Our Data Warehouse13.2.5. Creating Dimensions13.2.6. Creating a Cube13.2.7. Defining Source to Target MappingsMapping a Source to a TargetComputing a ValueJoining Tables to Obtain DataKey LookupFiltering DataUsing Data Generators13.2.8. Validating the Design13.2.9. Generating the Design13.2.10. Deploying the DesignConfiguring the Physical Design13.3. Oracle Discoverer13.3.1. Why Discoverer?Query Using Discoverer ViewerDynamic Reports with GraphsDrilling on the Data13.3.2. Setting up the EnvironmentEnd-User LayerBusiness AreaRestricting the Visible ColumnsFoldersChanging Item DetailsCreating New ItemsCreating JoinsHierarchiesItem Classes—List of ValuesSummariesSecurity Issues13.3.3. Query Using Discoverer Plus13.4. Oracle Reports 10g13.4.1. Creating a Report Using the Report Builder13.4.2. More Oracle Reports ExamplesMatrix ReportConditional Report13.4.3. Publishing the Report13.5. Summary
14. Data Warehousing and the Web
14.1. Overview14.1.1. Internet and Intranet14.1.2. Oracle Software for the Data Warehouse14.2. Oracle Application Server 10g14.2.1. Why Set up a Portal?14.2.2. OracleAS Portal14.2.3. Getting Started with Oracle Application Server 10g14.3. Publishing Data on the Web14.3.1. DiscovererCreating a Public Connection14.3.2. Publishing a Portlet14.3.3. Embedding a Static Report14.4. Oracle Personalization14.5. The Data Warehouse and E-Business Intelligence
15. OLAP
15.1. Why Do We Need the Oracle OLAP Option?15.1.1. OLAP Applications15.1.2. ROLAP and MOLAP15.1.3. Oracle OLAP15.2. Oracle OLAP Architecture15.3. Analytic Workspaces15.3.1. The Multidimensional Model15.3.2. Creating Analytic Workspaces15.4. The OLAP Catalog15.4.1. Defining OLAP Metadata for a Relational SchemaCreating OLAP Metadata in Oracle Enterprise Manager15.4.2. OLAP Metadata Views and Validation15.5. The Analytic Workspace Manager15.5.1. The Create Analytic Workspace WizardSetting Storage Options for the Analytic Workspace15.5.2. Refreshing the Analytic Workspace15.5.3. Creating an Aggregation Plan15.5.4. Analytic Workspace EnablersEnabling Analytic Workspace for OLAP API and BI BeansEnabling Analytic Workspace for Discoverer15.6. Querying Analytic Workspaces15.6.1. OLAP DMLAttaching to an Analytic WorkspaceStandard Form EntitiesReporting and Aggregating Data with OLAP DMLDefining Formulas and Custom MeasuresForecasting Using OLAP DML15.6.2. DBMS_AW package15.6.3. SQL Access to Analytic Workspaces15.6.4. OLAP API and BI Beans15.7. Summary
16. Oracle Data Mining
16.1. Oracle Database 10g Data Mining Option16.2. Oracle Data Mining Techniques16.2.1. Association Rules16.2.2. ClusteringClustering Algorithms16.2.3. Feature Extraction16.2.4. ClassificationTesting a Classification ModelComputing LiftClassification Algorithms16.2.5. Regression16.2.6. The PMML Standard16.3. Preparing Data for Oracle Data Mining16.3.1. Data Format16.3.2. Data PreparationBinning or DiscretizationNormalizingAttribute Importance16.4. Using Oracle Data Mining Interfaces16.4.1. Installation and Configuration16.4.2. Data Mining Analysis Flow16.4.3. An Example Using the Java APIBuilding a ModelApplying a Model16.4.4. An Example Using the PL/SQL ProceduresData PreparationBuilding a ModelApplying a Model16.5. Summary
17. High Availability and a Data Warehouse
17.1. Introduction17.2. What Is a Highly Available System?17.2.1. Characteristics of a highly available systemReliabilityRecoverabilityContinuous Operation17.2.2. Role of Operational Best Practices17.3. Overview of Oracle Database 10g High Availability Features17.4. Protecting against Hardware/Software Failures17.4.1. Real-Application Clusters (RAC)17.4.2. Reliable StorageAutomatic Storage ManagementIntegration with HARD-Compliant Storage17.4.3. Failure Detection and MonitoringAutomatic Proactive Notifications17.4.4. Resource Management17.5. Protecting against Data Loss17.5.1. Recovering from Media Failure17.5.2. Recovery from Human Errors with FlashbackFlashback TableFlashback DropFlashback QueryFlashback Database17.5.3. Disaster Recovery Using Data GuardData Guard ConceptsPhysical StandbyLogical StandbyLogical Standby Databases and Data WarehouseData Guard ConfigurationData Guard BrokerUsing Oracle Enterprise Manager to Configure Data GuardData Guard Protection ModesMaximum Protection ModeMaximum Performance ModeMaximum Availability ModeSwitching Roles From Primary to Standby Database17.5.4. Oracle Maximum Availability Architecture17.5.5. Protecting Metadata17.6. Managing Planned Downtime17.6.1. Dynamic Instance Reconfiguration17.6.2. Online Maintenance17.6.3. Online Redefinition17.6.4. Rolling UpgradesUsing RACUsing Data Guard17.7. Information Lifecycle Management17.8. Summary
A. The Schema for Easy Shopping Inc.
A.1. Creating the Tablespaces and Data FilesA.2. Creating the Tables, Constraints, and IndexesA.3. Defining SecurityA.4. Final Steps
B. Product Information

Content preview from Oracle 10g Data Warehousing

Chapter 16. Oracle Data Mining

Data mining is a process that finds hidden patterns and relationships in data to help make better business decisions.

In the course of running a business, you may encounter data in different forms. Operational data tells you day-to-day information about your customers—what did John Doe buy on August 5, 2002? In the data warehouse, data is organized according to predefined relationships using fact and dimension tables. You can then use OLAP tools to find out various facts about your business: How many people bought electronic products from your store and what was the average amount they spent? How many customers who bought electronic products were engineers? These are all questions based on existing data.

However, you ...

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Oracle 10g Data Warehousing

by Lilian Hobbs, Susan Hillson, Shilpa Lawande, Pete Smith

Chapter 16. Oracle Data Mining

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