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Oracle® Business Intelligence Disconnected Analytics Administration and Configuration Guide > Preparing Applications for Oracle BI Disconnected Analytics > Working with Data Set Definitions >

Defining Multiple Data Sets

This section describes multiple data sets by using an example of a customer interaction application that tracks the following types of customer interactions:

  • Service requests submitted by customers. Service requests have an owner, a status and a submission date and time.
  • Activities in which customers participate such as phone conversations, on-site visits, and product demonstrations. Activities have a priority, a type and a scheduled date and time.

Figure 5 illustrates the database schema for the application. It shows a schema with two main fact tables (Activity and SR) and their associated dimension tables. The two fact tables share the Customer and Time dimension tables.

Figure 5. Database Schema for the Application with Multiple Data Sets

CAUTION:  As the Oracle BI Administrator, you must verify data consistency and integrity. For example, if you create a new data set that contains new dimensional records and you do not update the corresponding facts data set, then the disconnected database might provide incorrect results.

Static Dimensions

Static dimensions are dimension tables that do not change for long periods of time, if at all. For example, a dimension table of United States zip (postal) codes could be a static dimension for most applications. Because static dimensions do not change often, disconnected users typically need to download them only once. Therefore, you should put all static dimension tables for a disconnected application into a separate data set.

The Customer Interaction application example in Defining Multiple Data Sets has one static dimension (Time). Database administrators typically preallocate many years worth of time data. As a result, the table does not change for years at a time. For example, in the Customer Interaction application, the Time dimension contains static data through the year 2010.

Example of a Data Set for a Time Dimension

The following is an example of the data set definition for the Time dimension.

 

<dataset

name="Static"

 

 

incremental="true"

 

 

syncmode="preprocessed"

 

 

forcesync="true"

 

 

subjectarea="CustomerInteraction">

 

<displayname lang="en" value="Data Set for Static Dimensions"/>

 

<displayname lang="es" value="Colección de Datos para Dimensiones Constante"/>

 

<table name="Time">

 

<sourcingreport name="Time" file="Time.csv"/>

 

<tablesql name="Time.sql"/>

 

</table>

 

 

</dataset>

 

NOTE:  A download occurs by default only during the first synchronization on a disconnected machine. The user cannot override this attribute (forcesync = "true").

Common Dimensions

Common dimensions are dimension tables that join with more than one fact table. Because common dimensions join with multiple fact tables, they must always be synchronized. Therefore, put all common dimension tables for a disconnected application into a separate data set.

The Customer Interaction application example in Defining Multiple Data Sets contains two common dimensions (Customer and Time). Because the Time dimension already qualifies as a static dimension, we need only put the Customer table in the data set for common dimensions.

Example of a Data Set for a Common Dimension

The following is an example of the data set definition for the common Customer dimension.

 

<dataset

name="Common"

 

 

incremental="true"

 

 

syncmode="preprocessed"

 

 

forcesync="true"

 

 

subjectarea="CustomerInteraction">

 

<displayname lang="en" value="Data Set for Common Dimensions"/>

 

<displayname lang="es" value="Colección de Datos para Dimensiones Comunes"/>

 

<table name="Customer">

 

<sourcingreport name="Customer" file="Customer.csv"/>

 

<tablesql name="Customer.sql"/>

 

</table>

 

</dataset>

 

A download occurs by default for the first synchronization and all subsequent synchronizations on a disconnected machine. The user cannot override this attribute (forcesync = "true").

Fact Tables and Private Dimensions

Private dimensions are dimensions that only join to one fact table. Because fact tables typically change independently of one another, you should put each fact table and its associated private dimensions into a separate data set.

The Customer Interaction application has two fact tables (Activity and SR), so each fact table and its associated private dimensions should have a separate data set.

Example of a Data Set for Fact Tables with Private Dimensions

The following is an example of the data sets for fact tables and their private dimensions.

 

<dataset

name="SR_Fact"

 

 

incremental="true"

 

 

syncmode="preprocessed"

 

 

subjectarea="CustomerInteraction">

 

<displayname lang="en" value="Service Request Data Set"/>

<displayname lang="es" value="Colección de Datos de los Pedidos del Servicio"/>

 

 

<table name="Owner">

 

<sourcingreport name="Owner" file="Owner.csv"/>

 

<tablesql name="Owner.sql"/>

 

</table>

 

<table name="Status">

 

<sourcingreport name="Status" file="Status.csv"/>

 

<tablesql name="Status.sql"/>

 

</table>

 

<table name="SR_Fact">

 

<sourcingreport name="SR_Fact" file="SR_Fact.csv"/>

 

<tablesql name="SR_Fact.sql"/>

 

</table>

 

</dataset>

 

 

<dataset

name="Activity_Fact"

 

 

incremental="true"

 

 

syncmode="preprocessed"

 

 

subjectarea="CustomerInteraction">

 

<displayname lang="en" value="Activity Data Set"/>

 

<displayname lang="es" value="Colección de Datos de la Actividad"/>

 

<table name="Priority">

 

<sourcingreport name="Priority" file="Priority.csv"/>

 

<tablesql name="Priority.sql"/>

 

</table>

 

 

<table name="Type">

 

<sourcingreport name="Type" file="Type.csv"/>

 

<tablesql name="Type.sql"/>

 

</table>

 

<table name="Activity_Fact">

 

<sourcingreport name="Activity_Fact" file="Activity_Fact.csv"/>

 

<tablesql name="Activity_Fact.sql"/>

 

</table>

 

 

</dataset>

 
  
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