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Oracle® OLAP Application Developer's Guide
10
g
Release 2 (10.2)
Part Number B14349-02
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Contents
List of Examples
List of Figures
List of Tables
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documents
Conventions
What's New in Oracle OLAP Applications Development?
Oracle Database 10
g
Release 10.2 Oracle OLAP
Oracle Database 10
g
Release 10.1.0.4 Oracle OLAP
Part I Fundamentals
1
Overview
OLAP Technology Within Oracle Database
Problems Maintaining Two Distinct Systems
Full Integration of Multidimensional Technology
Using OLAP to Answer Business Questions
Common Analytical Applications
Tools for Querying OLAP Data Stores
Formulating Queries
Creating Custom Measures
The Logical Dimensional Data Model
Logical Cubes
Logical Measures
Logical Dimensions
Logical Hierarchies and Levels
Logical Attributes
About Multidimensional Data Stores
Creating Analytic Workspaces
Summary Data
Deciding When to Use Analytic Workspaces
When to Use Analytic Workspaces
When to Use Relational Schemas
Structured and Unstructured Data Stores
Processing Analytic Queries
Creating Summary Data
How Analytic Workspaces Store Summary Data
How Relational Schemas Store Aggregate Data
Components of Oracle OLAP
OLAP Analytic Engine
Analytic Workspaces
Analytic Workspace Manager
OLAP Worksheet
SQL Interface to OLAP
OLAP DML
Analytic Workspace Java APIs
OLAP API
OLAP Catalog
Implementing an Analytic Workspace
Identifying Business Goals
Identifying Data Sources
Defining a Logical Model
Mapping, Loading, and Aggregating the Data
Generating Information-Rich Data
Implementing a Relational Data Warehouse for OLAP
Identifying Business Goals
Identifying Data Sources
Defining a Logical Model
Generating Summary Data
Upgrading Oracle Database 10
g
Release 1 Analytic Workspaces
Upgrading Oracle9
i
Analytic Workspaces
Upgrading the Physical Storage Format
Upgrading the Standard Form Metadata
2
The Sample Schema
Case Study Scenario
Reporting Requirements
Business Goals
Information Requirements
Business Analysis Questions
What products are profitable?
Who are our customers, and what and how are they buying?
What accounts are most profitable?
What is the performance of each distribution channel?
Is there still a seasonal variance to the business?
Summary of Information Requirements
Identifying Required Business Facts
Designing a Logical Data Model for Global Computing
Identifying Dimensions
Identifying Levels
Identifying Hierarchies
Identifying Stored Measures
The Global Schema
Part II Creating and Managing Analytic Workspaces
3
Creating an Analytic Workspace
Introduction to Analytic Workspace Manager
Model View
Object View
OLAP Worksheet
Getting Started with Analytic Workspace Manager
Installing Analytic Workspace Manager
Opening Analytic Workspace Manager
Defining a Database Connection
Opening a Database Connection
Identifying the Source Data
Schema Requirements
Star Schema
Snowflake Schema
Other
Making Transformations in Your Source Data
Choosing a Build Tool
Creating a Standard Form Workspace Using Analytic Workspace Manager
How Analytic Workspace Manager Saves Changes
Basic Steps for Creating a Standard Form Workspace
Adding Functionality to a Standard Form Analytic Workspace
Creating Logical Dimensions
Creating Dimensions
Defining a Time Dimension
Creating Unique Dimension Members
Opening the Create Dimension Dialog Box
Creating Levels
Creating Hierarchies
Creating Attributes
Automatically Defined Attributes
User Attributes
Creating Logical Cubes
Creating Cubes
Creating Measures
Creating Calculated Measures
Making Data Storage Decisions
What is Sparsity?
Sparsity Patterns
Physical Storage of Sparse Data
Manually Calculating Sparsity in a Cube
Ordering the Dimensions in a Cube
Partitioning Large Measures
Defining Rules for Summarizing Data
Basic Strategy for Summarizing Analytic Workspace Data
Selecting Levels to Aggregate in the Builds
Choosing Aggregation Methods
Mapping Logical Objects to Data Sources
Mapping Dimensions
Mapping Cubes
Maintaining the Data
Submitting Maintenance Tasks to the Oracle Job Queue
Managing Maintenance Jobs
Defining Measure Folders
Supporting Multiple Languages
Creating Calculation Plans
Case Study: Creating the Global Analytic Workspace
Defining the GLOBAL_AW User
Examining Sparsity Characteristics for GLOBAL
Identifying Levels for Precalculation
Creating the GLOBAL Analytic Workspace
Creating GLOBAL Dimensions and Attributes
Creating GLOBAL Cubes and Measures
Mapping the GLOBAL Logical Model to Data Sources
Loading and Aggregating the Data
Creating Calculated Measures
Creating a Measure Folder
Case Study: Creating the Sales History Analytic Workspace
Creating the SH Analytic Workspace
Defining Database Parameters
Defining Tablespaces for Sales History
Defining the SH_AW User
Defining the Logical Dimensions for Sales History
Defining TIMES_DIM
Defining CUSTOMERS_DIM
Defining PRODUCTS_DIM, CHANNELS_DIM, and PROMOTIONS_DIM
Defining the Logical Sales Cube for Sales History
About the Sparsity Advisor
Sample Program for Evaluating Sales History Tables
Interpreting the Results from the Sparsity Advisor
Maintaining Sales History
4
Predicting Future Performance
Creating a Forecast
Steps for Creating a Forecast
Creating the Forecast Time Periods
Defining a Measure for the Results
Defining Supporting Variables (Optional)
Developing a Forecast Program
Generating a Forecast
Aggregating the Forecast Data
Case Study: Forecasting Global Sales
Defining the Sales Forecast Measure for Global Sales
Defining a Variable for Seasonal Adjustment
Developing a Forecasting Program for Global Sales
Historical and Forecast Time Periods
The FORECAST_SALES Program
Generating the Global Sales Forecast
Aggregating the Sales Forecast Measure
5
Developing Java Applications for OLAP
Building Analytical Java Applications
About Java
The Java Solution for OLAP
Oracle Java Development Environment
Introducing OracleBI Beans
Metadata
Navigation
Formatting
Graphs
Crosstabs
Data Beans
Wizards
JSP Tag Library
Understanding the OLAP API
How the OLAP API Accesses Dimensional Data
Calculation Capabilities
Intelligent Caching
Managing Data Sources for OracleBI Beans and the OLAP API
Building Java Applications that Manage Analytic Workspaces
6
Administering Oracle OLAP
Administration Overview
Creating Tablespaces for Analytic Workspaces
Creating an UNDO Tablespace
Creating a Permanent Tablespace for Analytic Workspaces
Creating a Temporary Tablespace for Analytic Workspaces
Querying the Size of an Analytic Workspace
Setting Up User Names
SQL Access For DBAs and Application Developers
SQL Access for Analysts
Access to Database Objects Using OracleBI Beans
Access to the Oracle JVM
Initialization Parameters for Oracle OLAP
Procedure: Setting System Parameters for OLAP
About the PGA_AGGREGATE_TARGET Setting
Initialization Parameters for OracleBI Beans
Permitting Access to External Files
Creating a Directory Object
Granting Access Rights to a Directory Object
Example: Creating and Using a Directory Object
Understanding Data Storage
Analytic Workspace Tables
System Tables and Views
Monitoring Performance
Copying and Backing Up Analytic Workspaces
Part III Creating a Relational Data Warehouse
7
Using the OLAP Catalog
Choosing a Method for Creating OLAP Catalog Metadata
For Source Data in a Basic Star or Snowflake Schema
For Dimension Tables with Complex Hierarchies
For Other Schema Configurations
Overview of the OLAP Catalog
OLAP Catalog Components
About CWM1
About CWM2
Steps for Creating OLAP Metadata
Creating Metadata Using Enterprise Manager Database Control
Procedure: Accessing OLAP Management
Defining Metadata for Dimension Tables
Information That You Supply for Dimensions
Time Dimension
Procedure: Defining a Logical Dimension in the OLAP Catalog
Defining Metadata for Fact Tables
Information That You Supply for Cubes
Procedure: Defining a Logical Cube in the OLAP Catalog
Case Study: Creating Metadata for the GLOBAL Star Schema
Defining a Logical Time Dimension for the Global Schema
Defining a Logical Price and Cost Cube for the Global Schema
Creating Metadata Using PL/SQL
CWM2 Packages for Creating OLAP Dimensions
CWM2 Packages for Creating Cubes
CWM2 Package for Mapping Metadata
CWM2 Package for Creating Level-Based Dimension Tables
CWM2 Packages for Classification and Validation
8
Materialized Views for the OLAP API
Summary Management with Oracle OLAP
Overview and Requirements
Materialized Views Required for a Cube
Materialized Views and OLAP Metadata
A Dimension Materialized View
CREATE Materialized View for a Dimension Hierarchy
Bitmap Indexes for a Dimension Hierarchy
Statistics for a Dimension Hierarchy
A Fact Materialized View
CREATE Fact Materialized View
Bitmap Indexes for Fact Materialized Views
Statistics for Fact Materialized Views
Using the DBMS_ODM Package
Procedure: Automatically Generate the Materialized Views
Procedure: Manually Generate the Materialized Views
Example: Automatically Generate the Materialized Views for a Price Cube
Example: Manually Generate the Materialized Views for a Sales Cube
A
Database Standard Form for Analytic Workspaces
Overview of Database Standard Form
Terminology: Using Role Names to Identify Objects
Querying a Standard Form Analytic Workspace
Querying the Standard Form Catalogs
Querying Properties
Standard Form Implementation of the Logical Model
Relationships Among Logical Objects
Classes of Workspace Objects
Object Naming Conventions
Logical Names
Simple Logical Names and Full Names
Name Space Organization
Workspace Object Properties
System Properties on All Workspace Objects
Properties Specific to Implementation Class Objects
Role Property Values for Implementation Class Objects
Role Property Values for Catalogs Class Objects
Role Property Values for Features Class Objects
Role Property Values for Extensions Class Objects
Implementation Class Objects
Cube Objects
Cubedef Dimension
Measure Objects
Measuredef Object
Dimension Objects
Dimdef Dimension
Hierlist Dimension
Levellist Dimension
Member_Levelrel Relation
Member_Parentrel Relation
Hier_Levels Valueset
Attrdef Object
Catalogs Class Objects
Lists of Objects
ALL_CUBES Dimension
ALL_MEASURES Dimension
ALL_DIMENSIONS Dimension
ALL_HIERARCHIES Dimension
ALL_LEVELS Dimension
ALL_ATTRIBUTES Dimension
ALL_OBJECTS Dimension
Lists of Types and Languages
ALL_DESCTYPES Dimension
ALL_ATTRTYPES Dimension
ALL_LANGUAGES Dimension
Lists of Cube and Dimension Objects
CUBE_MEASURES Relation
DIM_HIERARCHIES Relation
DIM_LEVELS Relation
DIM_ATTRIBUTES Relation
Supporting Object Information
AW_NAMES Variable
Features Class Objects
ALL_DESCRIPTIONS Variable
DEFAULT_HIER Relation
VISIBLE Variable
Member_Inhier Valueset
Member_Createdby Variable
Member_Familyrel Relation
Member_Gid Variable
OBJ_CREATEDBY Variable
VERSION Variable
Extensions Class Objects
B
Upgrading From Express Server
Administration
Management Tools
Authentication of Users
Data Transfer
Localization
Applications Support
Programming Environment
Communications
Metadata
Programming Language Changes
New Commands
Obsolete Commands
UPDATE and COMMIT
Transforming Oracle Express Databases to Standard Form
Who Should Use the Transformation Tool
What the Transformation Tool Does For You
What the Transformation Tool Does Not Do For You
Converting From Oracle Express Objects Metadata
Procedure: Converting From Oracle Express Objects to Standard Form
Populating Time Attributes
Sorting Time Dimension Members
Creating and Populating End Date and Time Span Attributes
Setting Properties on Time Objects
Revising the Load Programs
Example: Converting the XADEMO Database to Standard Form
Creating a Standard Form XADEMO Analytic Workspace
About the Time Dimension in XADEMO
Populating the XADEMO Time Attributes
Glossary
Index