Oracle 11g数据库与数据仓库指南：2天实战教程

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Oracle Database 2 Day + Data Warehousing Guide 11g -130 是一本关于Oracle数据库的权威指南，专为Oracle 11g Release 2 (11.2)设计，出版日期为2012年2月。这本书旨在提供用户在短短两天内快速理解和掌握Oracle数据库管理和数据仓库设计的全面教程。内容覆盖了Oracle数据库的关键概念、安装、配置、优化以及与数据仓库相关的高级特性。书中可能包括以下知识点： 1. **Oracle数据库基础知识**：介绍Oracle数据库体系结构、数据模型、SQL语言和基本操作，帮助读者理解如何创建、管理和维护数据库。 2. **安装与配置**：涵盖了Oracle 11g的安装过程，包括安装选项、网络配置、安全性设置等，确保读者能够顺利部署数据库环境。 3. **性能优化**：讨论如何调整数据库参数、索引策略、存储管理以及使用SQL Tuning Advisor来提高查询性能。 4. **数据仓库技术**：深入讲解如何设计和实施数据仓库，包括星型、雪花型和事实表的设计，以及如何使用Oracle Essbase或Oracle RAC进行并行处理和高可用性。 5. **OLAP（联机分析处理）和数据挖掘**：介绍如何利用Oracle的分析功能，如Oracle Business Intelligence Suite，进行数据分析和决策支持。 6. **大数据和云集成**：如果涉及11g版本，可能包含对Oracle Database在云计算环境中的部署和与Hadoop等大数据平台的集成。 7. **安全性和备份恢复**：强调数据库安全措施，包括用户管理、权限分配，以及数据备份和恢复的最佳实践。 8. **许可证和法律条款**：提醒读者软件使用许可协议的重要性和限制，包括反逆向工程的规定，以及如果该书被美国政府或代表其使用时适用的法律通知。由于本书是版权作品，用户需遵守版权协议，不得随意复制、传播或修改软件，除非在许可协议或法律规定下可以执行。任何发现的问题或错误都应通过书面形式报告给Oracle。这本指南是一份实用的资源，适合DBA、数据分析师和IT专业人员在实际工作中提升技能，了解和应对Oracle数据库在11g Release 2中的新特性和需求。

What Is a Data Warehouse?

1-2 Oracle Database 2 Day + Data Warehousing Guide

What This Guide Is Not

Oracle Database 2 Day + Data Warehousing Guide is not an exhaustive discussion of

implementing a data warehouse on Oracle. The objective for this guide is to describe

why and when tasks must be performed in a task-oriented way. Where appropriate, it

describes the concepts necessary for understanding and completing the current task.

For complete conceptual information about these features and detailed instructions for

using them, see the appropriate Oracle documentation as follows:

■ Oracle Database Data Warehousing Guide

■ Oracle Warehouse Builder Sources and Targets Guide

■ Oracle Database Administrator's Guide for a discussion of administrative tasks

■ Oracle Data Mining Concepts for a discussion of data mining

What Is a Data Warehouse?

A data warehouse is a relational or multidimensional database that is designed for

query and analysis. Data warehouses are not optimized for transaction processing,

which is the domain of OLTP systems. Data warehouses usually consolidate historical

and analytic data derived from multiple sources. Data warehouses separate analysis

workload from transaction workload and enable an organization to consolidate data

from several sources.

A data warehouse usually stores many months or years of data to support historical

analysis. The data in a data warehouse is typically loaded through an extraction,

transformation, and loading (ETL) process from one or more data sources such as

OLTP applications, mainframe applications, or external data providers.

Users of the data warehouse perform data analyses that are often time-related.

Examples include consolidation of last year's sales figures, inventory analysis, and

profit by product and by customer. More sophisticated analyses include trend analyses

and data mining, which use existing data to forecast trends or predict futures. The data

warehouse typically provides the foundation for a business intelligence environment.

This guide covers relational implementations, including star schemas.

The Key Characteristics of a Data Warehouse

The key characteristics of a data warehouse are as follows:

■ Some data is denormalized for simplification and to improve performance

■ Large amounts of historical data are used

■ Queries often retrieve large amounts of data

■ Both planned and ad hoc queries are common

■ The data load is controlled

In general, fast query performance with high data throughput is the key to a successful

data warehouse.

See Also: Oracle Database Data Warehousing Guide for more details

regarding multidimensional data warehouses

Tasks Illustrated in This Guide

Introduction to Data Warehousing 1-3

Common Oracle Data Warehousing Tasks

As an Oracle data warehousing administrator or designer, you can expect to be

involved in the following tasks:

■ Configuring an Oracle database for use as a data warehouse

■ Designing data warehouses

■ Performing upgrades of the database and data warehousing software to new

releases

■ Managing schema objects, such as tables, indexes, and materialized views

■ Managing users and security

■ Developing routines used for the extraction, transformation, and loading (ETL)

processes

■ Creating reports based on the data in the data warehouse

■ Backing up the data warehouse and performing recovery when necessary

■ Monitoring the data warehouse's performance and taking preventive or corrective

action as required

In a small-to-midsize data warehouse environment, you might be the sole person

performing these tasks. In large, enterprise environments, the job is often divided

among several DBAs and designers, each with their own specialty, such as database

security or database tuning.

Tasks Illustrated in This Guide

This guide illustrates the following tasks:

1. Configure an Oracle database for use as a data warehouse.

See Chapter 2, "Setting Up Your Data Warehouse System". This section also

includes instructions on how to access a demonstration that is referenced in

exercises throughout this guide.

2. Take the initial steps in consolidating data.

Follow the instructions in Chapter 3, "Identifying Data Sources and Importing

Metadata".

3. Begin to define the target objects in the warehouse.

Chapter 4, "Defining Warehouses in Oracle Warehouse Builder" describes how to

define external tables, dimensions, and cubes for the target warehouse.

4. Define strategies for extracting, transforming, and loading data into the target.

Chapter 5, "Defining ETL Logic" describes how to define ETL logic to extract data

from the source you identified in step 2, transform the data, and then load it into

the target you designed in step 3.

5. Deploy to target schemas and execute ETL logic.

Chapter 6, "Deploying to Target Schemas and Executing ETL Logic" describes how

to prepare a target schema with code from mappings and also describes how to

subsequently execute that code.

6. Write efficient SQL.

Tools for Administering the Data Warehouse

1-4 Oracle Database 2 Day + Data Warehousing Guide

Read and complete the tasks in Chapter 7, "SQL for Reporting and Analysis". This

section describes how to write efficient SQL.

7. Refresh the data warehouse.

Read and complete the tasks in Chapter 8, "Refreshing a Data Warehouse".

8. Optimize operations.

Read and complete the tasks in Chapter 9, "Optimizing Data Warehouse

Operations".

9. Eliminate performance bottlenecks.

Read and complete the tasks in Chapter 10, "Eliminating Performance

Bottlenecks".

10. Review some basics of data warehouse backup and recovery.

Chapter 11, "Backing up and Recovering a Data Warehouse" describes some

considerations for how to back up and recover a data warehouse.

11. Review some basics of data warehouse security.

Chapter 12, "Securing a Data Warehouse" describes some considerations for how

to create a secure data warehouse.

Tools for Administering the Data Warehouse

The procedures in this guide refer to and sometimes require the following products,

tools, and utilities to achieve your goals with your data warehouse:

■ Oracle Universal Installer

Oracle Universal Installer (OUI) installs your Oracle software and options. It can

automatically start the Database Configuration Assistant (DBCA) to install a

database. OUI and DBCA are included with Oracle Database. See Oracle Universal

Installer User's Guide for Windows and UNIX for optional information.

■ Oracle Enterprise Manager

The primary tool for managing your database is

Oracle Enterprise Manager, a

Web-based interface. After you have installed the Oracle software, created or

upgraded a database, and configured the network, you can use

Oracle Enterprise

Manager for managing your database. In addition, Oracle Enterprise Manager

also provides an interface for performance advisors and for Oracle utilities such as

SQL*Loader and Recovery Manager. See Oracle Enterprise Manager Administrator's

Guide if you want more detailed information than what is discussed in this guide.

■ Oracle Warehouse Builder

The primary product for populating and maintaining a data warehouse, Oracle

Warehouse Builder provides ETL, data quality management, and metadata

management in a single product.

Warehouse Builder includes a unified repository hosted on Oracle Database.

Warehouse Builder leverages Oracle Database functionality to generate code that

is optimized for loading into and maintaining Oracle Database targets. See Oracle

Warehouse Builder Data Modeling, ETL, and Data Quality Guide for more details and

comprehensive procedures.

■ Oracle Tuning Pack

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