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Oracle Database Online Documentation 12c Release 1 (12.1)

Data Warehousing and Business Intelligence

Data Warehousing involves large volumes of data used primarily for analysis. This category covers applications such as Business Intelligence and Decision Support Systems.

Supporting Documentation

Supporting documentation treats advanced topics related to Data Warehousing and Business Intelligence. In general, the 2 Day + books refer you to these topics when needed.

Provides conceptual, reference, and implementation material for using Oracle Database in data warehousing. It covers the full range of data warehousing activities, from physical database design to advanced calculation techniques.
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Provides information about how to tune the performance of Oracle Database using Oracle performance tools.
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Describes how to perform SQL tuning, which is the iterative process of improving SQL statement performance to meet specific, measurable, and achievable goals.
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Contains an overview of very large database (VLDB) topics, with emphasis on partitioning and parallel execution as a key component of the VLDB strategy.
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Describes how to use Oracle Database utilities to load data into a database, transfer data between databases, and maintain data. The topics discussed include Data Pump Export, Data Pump Import, SQL*Loader, external tables and associated access drivers, the Automatic Diagnostic Repository Command Interpreter (ADRCI), DBVERIFY, DBNEWID, LogMiner, the Metadata API, original Export, and original Import.
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Online Analytical Processing (OLAP)

Online Analytical Processing (OLAP) analyzes data from a data warehouse, for business processes such as forecasting, planning, and what-if analysis.

Explains how SQL applications can extend their analytic processing capabilities and manage summary data by using the OLAP option of Oracle Database.
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Describes the Analytic Workspace Manager XML and Java plug-in interfaces and provides simple examples of implementations of them.
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Contains a complete description of the OLAP Data Manipulation Language (OLAP DML) used to define and manipulate analytic workspace objects.
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Describes the Oracle OLAP expression syntax used to generate information-rich content from the data stored in dimensional database objects such as cubes and cube dimensions.
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Provides guidance for developing client applications using the Oracle OLAP Java API.
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Provides reference information for the Oracle OLAP Java API.
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Oracle Advanced Analytics

Oracle Advanced Analytics extends the database into a comprehensive advanced analytics platform, including predictive analytics, data mining and text mining, statistical analysis, and advanced analytics. Advanced Analytics has two components, Oracle Data Mining and Oracle R Enterprise.

Discusses the basic concepts underlying Oracle Data Mining. Includes an overview of the features of Oracle Data Mining and information about mining functions and algorithms.
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Explains how to use the SQL interface to Oracle Data Mining to create models and score data. This Guide also addresses administrative issues such as security, import/export, and upgrade for Oracle Data Mining.
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Contains important information that was not included in the documentation for Oracle R Enterprise 1.2.
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Describes how to install and use Oracle R Enterprise which provides an environment for statistical computing.
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