SAP BusinessObjects Enterprise XI3 Deployment Patterns

When deploying an SAP BusinessObjects Enterprise system there are a lot of choices for where you can deploy all the services that make up the system. It is then necessary to make sure that you choose the right deployment in order to meet your requirements, for example, is it easily maintained, is it resilient, is it secure, will it support my user base and can it be easily expanded to accomodate additional users.

This article looks at different deployment patterns for an SAP BusinessObjects Enterprise XI3 system and reviews their advantages and limitations of each. It is the intention then that this can help you make an informed decision about the deployment configuration of your system.

The article focuses on the core SAP BusinessObjects Enterprise servers and does not include Data Services or Performance Management.
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SAP Business Objects Data Services, SQL Server Express and Java 6

This articles looks at configuring the following components,

  • SAP Business Objects Data Services XI3.2
  • SQL Server Express 2005
  • Tomcat 5.5
  • JDK 1.6

The JDK 1.6 is not supported and indeed when trying to configure the Management Console to connect to a repository created in SQL Server Express 2005 we get the following error,

Java Runtime Environment (JRE) version 1.6 is not supported by this driver. Please use the JDBC 4 driver (sqljdbc4.jar) instead.

Solution

As the error suggests we need to upgrade the SQL Server JDBC driver to use a Type 4 JDBC driver.  The instructions below assume you have already setup a Data Integrator repository in SQL Server and also you are not using windows authentication to connect to this repository.
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Calculating Geometric Mean in Web Intelligence

A geometric mean is an average that is useful for sets of numbers that are interpreted according to their product and not their sum as is the case with the more commonly known arithmetic mean. An example of where you would use a geometric mean is in financial reporting when you want to calculate the compound annual growth rate.

Compound annual growth rate is an average growth rate over a period of several years. For example if you had growth rates of 4%, 6%, 5%, 8% each year what was the average rate over the four year period? You can then use this average to forecast growth for the next few years.

Web Intelligence doesn’t have a built in geometric mean formula however we can calculate it using logarithms. This article then looks at how to calculate a geometric mean in Web Intelligence.

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Filtering for Latest Data in a Universe

Summary

This article looks at a reporting requirement where we need to restrict data to the latest data, for example, to only show the latest account balance or the latest action item for work streams in a project.

Our solution is to implement a series of predefined conditions one for each dimension that we need to filter for latest data by.

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Date Objects Every Universe Should Have

A large amount of data analysis will use dates to filter or group results. This article looks at what objects and predefined conditions we should include in your universe that provide rich functionality to report authors that are querying with dates.

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