book

Predictive Analytics Using Oracle Data Miner

Name: Predictive Analytics Using Oracle Data Miner
Author: Brendan Tierney
ISBN: 9780071821759

by Brendan Tierney

August 2014

Beginner to intermediate

464 pages

10h 26m

English

McGraw Hill Computing

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Cover
About the Author
About the Technical Editor
Title Page
Copyright Page
Contents at a Glance
Contents
Acknowledgments
Introduction
PART I: Oracle Data Miner Fundamentals
Chapter 1: Oracle Data Miner
In-Database Data Mining with Oracle Data MiningOracle Advanced Analytics OptionOracle Data MiningOracle R Enterprise (ORE)History of Data Mining in OracleOracle Data Mining ComponentsOracle Data Mining ArchitectureOracle Data Miner GUI ToolOracle Data Mining Using SQL and PL/SQLOracle Statistical FunctionsApplications Powered by Oracle Data MiningHow Are Customers Using Oracle Advanced AnalyticsCustomer Success Stories

Chapter 2: The Predictive Modeling Lifecycle
Predictive Modeling LifecyclesKnowledge Discovery in Data (KDD) ProcessSEMMACRISP-DMBusiness UnderstandingData UnderstandingData PreparationModelingEvaluationDeploymentSummary
Chapter 3: How to Install, Set Up, and Get Started
Enabling the Oracle Advanced Analytics OptionCreating a Data Mining TablespaceCreating an ODM SchemaCreating a Connection for Your DM User in SQL DeveloperCreating the Oracle Data Mining RepositoryUsing SQL Developer to Create the ODM RepositoryUsing SQL Scripts to Create the ODM RepositorySetting Up Additional Users to Access ODMODM Schema System PrivilegesSetting Up and Using the Pre-built Database ApplianceSummary
PART II: Using the Oracle Data Miner Tool
Chapter 4: ODM Menus, Projects, and Workflows
The ODM MenusCreating a ProjectCreating, Exporting, and Importing a WorkflowCreating a WorkflowExporting a WorkflowImporting a WorkflowAdjusting the LayoutThe ODM Workflow MenuThe Components Workflow EditorSummary
Chapter 5: Exploring Your Data
Gathering Statistics and Exploring Your DataAdding a Data SourceData Source PropertiesThe Explore Data NodeBuilding Up a Story About the DataExploring the Data Based on Attribute GroupingGraphsCreating a GraphSQL Query NodeFeature SelectionSummary
Chapter 6: Data Preparation
AggregateUsing the Aggregation WizardAdding a New Aggregation-Level AttributeAdding an Aggregation ExpressionFilter ColumnsFilter Columns DetailsFilter RowsJoinSampleTransformAutomatic Data Preparation (ADP)Summary
Chapter 7: Association Rule Analysis
What Is Association Rule Analysis?Association Rule Analysis in OracleBuilding Association Rules Using ODMDefining the Data SourceCreating the Association NodeModel SettingsAssociation Node Properties TabViewing the Association RulesGenerated RulesGenerated ItemsetsAdding a Data Source Node for Transaction DescriptionsApplying Filters to the Association RulesOutputting and Persisting the Association RulesSummary
Chapter 8: Classification
What Is Classification?Classification Methods Available in OracleBuilding Classification ModelsModel SettingsProperty InspectorUsing Different Build and Test Data SetsCreating Additional Models and Removing Unwanted ModelsGenerating the ModelsEvaluating the Classification ModelsPerformancePerformance MatrixROCLiftProfitApplying a Classification Model to New DataSummary
Chapter 9: Clustering
What Is Clustering?Clustering Methods Available in OracleBuilding Clustering ModelsModel SettingsProperty InspectorCreating Additional Models and Removing Unwanted ModelsGenerating the ModelsEvaluating the Classification ModelsView Your Cluster ModelsCluster DetailsComparing Clusters: Multicluster-Multivariable ComparisonRenaming ClustersApplying a Clustering Model to New DataSummary
Chapter 10: Regression
What Is Regression?Regression Methods Available in OraclePreparing Your Data for RegressionBuilding Regression ModelsRegression Model SettingsProperty InspectorGenerating the Regression ModelsViewing the Regression ModelsRegression Model Test ResultsApplying a Regression Model to New DataSummary
Chapter 11: Anomaly Detection
What Is Anomaly Detection?Anomaly Detection in OracleBuilding an Anomaly Detection ModelModel SettingsProperty InspectorGenerating the ModelsEvaluating the Anomaly Detection ModelApplying the Model to Your DataSummary
PART III: Data Mining Using SQL and PL/SQL
Chapter 12: The ODM Data Dictionary, SQL, and PL/SQL Packages
ODM Data Dictionary ViewsODM SQL FunctionsODM PL/SQL PackagesDBMS_DATA_MINING PL/SQL PackageDBMS_PREDICTIVE_ANALYTICS PL/SQL PackageSummary
Chapter 13: Data Preparation
Data Preparation for Data MiningData SamplingData Aggregation and Pivoting the DataHandling Missing DataHistograms and BinningCreating a Target Variable/AttributeAutomatic Data Preparation in ODMADP with Transformation ListsUsing DBMS_DATA_MINING_TRANSFORM PL/SQL PackageList of Package Procedures and FunctionsExample of Using the DBMS_DATA_MINING_TRANSFORM PackageEmbedding Transformation List into the ModelSummary
Chapter 14: Association Rule Analysis
Setting Up Your DataSettings TableCreating the Association Rule Analysis ModelViewing the Association Rule Model Item Sets and RuleViewing the Frequent Item SetsViewing the Association RulesSummary
Chapter 15: Classification
Setting Up Your DataSettings TableCreating the Classification ModelsEvaluating the Classification ModelsPreparing the DataComputing the Confusion MatrixComputing the LiftComputing the ROCApplying the Model to New DataApplying the Model in Real TimeApplying the Model in BatchSummary
Chapter 16: Clustering
Setting Up Your DataViewing Your Existing Cluster ModelsSettings TableCreating a Cluster ModelExamining the Cluster ModelQuerying the Cluster Models in Your SchemaExamining the Cluster DetailsApplying the Cluster Model to New DataApplying the Cluster Model in Real TimeApplying the Cluster Model in Batch ModeCombining ClustersSummary
Chapter 17: Regression
Examining the Existing Regression Model(s)Settings Table for RegressionCreating a Regression ModelExamining and Evaluating the Regression ModelsGlobal Statistics for a GLM Regression ModelGLM Regression Model DetailsSVM Regression Model DetailsResidual StatisticsApplying Regression Model to Your DataUsing the Regression Model in Real TimeUsing the Regression Model in Batch ModeSummary
Chapter 18: Anomaly Detection
Examining the Existing Anomaly Detection Model(s)Settings TableCreating an Anomaly Detection ModelApplying the Anomaly Detection Model to Your DataUsing the Anomaly Detection Model in Real TimeUsing the Anomaly Detection Model in Batch ModeSummary
PART IV: Migration and Implementations
Chapter 19: How to Migrate Your ODM Models
Oracle Data Miner Script GenerationRunning the ODM Workflow ScriptsPL/SQL Procedures for ODM Model MigrationSystem Privileges Needed for Exporting and Importing ODM ModelsExporting an ODM ModelImporting and the ODM ModelDropping an ODM ModelRenaming an ODM ModelSummary
Chapter 20: Implementation-Related Topics
How to Add Your ODM Models to Your OBI DashboardsImporting the ODM ModelCreating a View to Include the ODM ModelImporting the View to the Physical Layer of the BI Repository (RPD)Adding New Columns to the Business Model LayerAdding to the OBI DashboardsHow to Build and Apply ODM Models in ParallelHow to Run Your ODM Workflows and ODM Models in ParallelHow to Run Your ODM Model in Real Time Using Parallel QueryHow to Run Your ODM Model in Batch Mode Using Parallel QueryPredictive QueriesSummary
Index

Overview

Build Next-Generation In-Database Predictive Analytics Applications with Oracle Data Miner

“If you have an Oracle Database and want to leverage that data to discover new insights, make predictions, and generate actionable insights, this book is a must read for you! In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides you through the basic concepts of data mining and offers step-by-step instructions for solving data-driven problems using SQL Developer’s Oracle Data Mining extension. Brendan takes it full circle by showing you how to deploy advanced analytical methodologies and predictive models immediately into enterprise-wide production environments using the in-database SQL and PL/SQL functionality. Definitely a must read for any Oracle data professional!” --Charlie Berger, Senior Director Product Management, Oracle Data Mining and Advanced Analytics

Perform in-database data mining to unlock hidden insights in data. Written by an Oracle ACE Director, Predictive Analytics Using Oracle Data Miner shows you how to use this powerful tool to create and deploy advanced data mining models. Covering topics for the data scientist, Oracle developer, and Oracle database administrator, this Oracle Press guide shows you how to get started with Oracle Data Miner and build Oracle Data Miner models using SQL and PL/SQL packages. You'll get best practices for integrating your Oracle Data Miner models into applications to automate the discovery and distribution of business intelligence predictions throughout the enterprise.

Install and configure Oracle Data Miner for Oracle Database 11g Release 11.2 and Oracle Database 12c
Create Oracle Data Miner projects and workflows
Prepare data for data mining
Develop data mining models using association rule analysis, classification, clustering, regression, and anomaly detection
Use data dictionary views and prepare your data using in-database transformations
Build and use data mining models using SQL and PL/SQL packages
Migrate your Oracle Data Miner models, integrate them into dashboards and applications, and run them in parallel
Build transient data mining models with the Predictive Queries feature in Oracle Database 12c

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