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Oracle by Example (OBE)

http://www.oracle.com/technology/obe

Documentatie:

http://www.oracle.com/pls/db112/homepage

A data warehouse is a strategic collection of all types of data in support of the decision-making

process at all levels of an enterprise.

Business intelligence is the process of transforming data into

information and through discovery transforming that information

into knowledge. Gartner Group

The dimensional model is essentially made up of measures and dimensions.

Measures contain or calculate data, and dimensions organize data

The multidimensional model has the following elements:

Measures

Dimensions:

Hierarchies

Levels

Attributes

Dimensions may contain the following elements:

Dimensions optionally have hierarchies, whichare logical structures that group like

members of a dimension together for the purposes of analysis, aggregation, or allocation.


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Hierarchies may or may not have levels because some hierarchies are not level based.

Dimensions may also have attributes, which are used to provide more information about

members of the dimension. Attributes are useful when filtering that dimension for analysis.

Physical Layers of a Data Warehouse

Staging Area

You need to clean and process your operational data before putting it into the warehouse. Most

data warehouses use a staging area to perform this operation. This is especially important when

data is being extracted from multiple source systems

Atomic Data Layer

The atomic data layer is the enterprise data model, which stores data in the third normal form.

This is the most detail level of data; it does not hold any aggregate data. The atomic data layer is

used as the source for dependent data marts and summary data.

Performance Data Layer

The performance data layer is also known as the data exploration layer of the warehouse. It is

built from the base data warehouse schema, containing summary data that allows for fast access

for reporting and analytic applications. This summary layer is often implemented as a star or

snowflake schema with materialized views and cubes.

Oracle OLAPis an option to Oracle Database 11g Enterprise Edition

Oracle OLAP offers:

Multidimensional OLAP (MOLAP), array-based storage, and retrieval model

SQL and dimensional access to multidimensional cubes

Sophisticated calculationsExcellent aggregation performance

Embedded BI metadata

ROLAP Versus MOLAP


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Entirely in the relational database. Data is stored entirely in relational tables in a data

warehouse and made available to applications by OLAP metadata. During user sessions,

data is selected and manipulated in the relational database. This method is typically called

Relational OLAP or ROLAP.

Entirely in the multidimensional analytical workspace. As a routine maintenance task,

data is loaded into dimensions and variables in the workspace from one or more sources(including the relational database and flat files) and saved for use by all sessions. During

user sessions, data is selected and manipulated in the analytical workspace. This method

is typically called Multidimensional OLAP or MOLAP.

A data warehouse is a subject-oriented, integrated, nonvolatile, andtime-variant collection of data in support of managementsdecisions.W.H. Inmon

An enterprise-structured repository of subject-oriented, timevariant,historical data used for information retrieval and decision support.The data warehouse stores atomic and summary data.Oracles definition of a data warehouse

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