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The End to End BI Concept

Considering the Full Landscape

Cornerstone Solutions® use an End to End BI approach and here’s why. When thinking about Business Intelligence architecture we need to consider the entirety of the component parts as a whole and not simply individually. In other words consideration is made of the full BI system as a whole and the individual components are not treated in exclusivity of each other. This is because the components will need to act interdependently regardless of whether they have been procured from a single or multiple software vendors.

In this respect the BI system is similar to the human body i.e. everything is so closely related that a felt symptom in one area (a pain in the arm) may be caused by an unseen symptom in another part of the body (a problem with an internal organ). To relieve the pain felt in the arm we treat the unseen causal effect in the internal organ. The same concept of unseen relationship and causal effect applies to the Business Intelligence system. Data flows from end to end through the Business Intelligence system in a similar way to blood circulating in the body and must not be blocked, lost or corrupted at any stage. The BI Architect must ensure this.

End to End BI
The components in the BI system are akin to a linked interdependent chain

Interdependency of the BI system

The early phases of a BI implementation can be usefully considered as akin to those of the Rational Unification Process (RUP) stages of Strategy, Inception, Elaboration, and Construction. A well defined BI strategy is very important. However, perhaps paradoxically the Construction phase is often delivered using an Agile delivery method.

Construction frequently commences with source system analysis, end user requirement gathering and the installation and configuration of the software components. If using SAP Business Information Warehouse, cubes and queries will be developed, or if a relational platform is used a dimensional modelling exercise is undertaken and then the physical tables are developed. The ETL system is designed and developed and reports and dashboards are built.

The relationship between these things is one of interdependency. It’s like a linked interdependent chain. This is why in the implementation methodology of BI System Builders we practice our philosophy of End to End BI. End to End BI takes the view that as each component in the BI system has interaction with and therefore dependency on its related components, BI Breakpoints can occur. BI System Builders take full consideration of the interdependencies in the landscape to ensure prevention rather than cure in their End to End BI project delivery method.

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Death Of The Cube – Long Live The Cube!

OLAP Cubes

OLAP Cubes

The acquisition of BusinessObjects by SAP paved the way for a very welcome tighter integration between the two softwares. One of the challenges coming out of that tighter integration was the performance of Web Intelligence against an OLAP universe generated on SAP cubes and BEx Queries. The reality of SAP project implementations was that SAP Netweaver experts designed large cubes and large queries. And why not; after all this was the OLAP world?! Large SAP cubes and large BEx Queries make sense for OLAP.

However, Web Intelligence is not an OLAP tool, it builds a cache of data referred to as a ‘microcube’. Note the word ‘microcube’. Attempting to pass large volumes of data from an OLAP query to the microcube could cause the Web Intelligence engine to perform poorly or crash. BISB have observed this on numerous occasions when undergoing performance testing at client site. Problems with the version of Explorer dependent up on the Web Intelligence engine have also been observed for the same reason.

But failing to process large volumes of data was not a weakness of Web Intelligence. On the contrary, Web Intelligence was designed for smaller, fast, ad hoc queries. Users experiencing problems with large volumes of data and Web Intelligence could consider the use of Crystal Reports. Crystal Reports uses a different cache infrastructure to Web Intelligence.

The above mentioned data volume issues have made the SAP BI 4.0 road map very welcome. Using the new Data Federator connectivity through the SAP BusinessObjects BI 4.0 universe means that the SAP MDX engine (OLAP) is bypassed. This removes one of the big issues of the SAP OLAP data volumes, namely MDX crossjoins. Other development means that the BI 4.0 universe now has connectivity to SAP HANA. If you have the budget available this makes SAP HANA highly desirable for Big Data and Analytics.

Finally, ardent OLAP users that cannot live without a cube have not been left out in the cold. BI 4.0 ushered in the end of the Voyager OLAP tool, replacing it with the new Advanced Analysis for OLAP tool.

The view expressed in this article is from BISB and not necessarily SAP. Russell Beech was Senior Analyst in the BusinessObjects Analytic Applications Division for almost six years. Check out Web Intelligence In Under Three Minutes here.

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Business Intelligence Architecture

Creating BI Architecture That Stands Out

In essence Business Intelligence is about taking raw data and turning it into information and then using that information to do intelligent business. The process of both transforming the data and consuming it as intelligence occurs in the BI system. The effectiveness of the BI system is dependent upon the quality of the overall BI architecture. Planning the BI system architecture occurs very early on and there is an art to getting it right. BI System Builders recognise that it takes wide and in-depth knowledge and experience to effectively make consideration of the full BI system in the early design stage of the Business Intelligence architecture. At this very early stage thinking may be embryonic and the components do not yet physically co-exist in the system. The skill set to visualise at this level can be sparse on the ground but the failure to do so can lead to consequent sub-optimal BI systems being developed. At their worse these BI systems run the risk of becoming expensive white elephants. They have taken a lot of effort and budget to implement but in the final analysis the end user community cannot access the critical information that it requires.

So what are the key areas at the macro level that constitute the Business Intelligence architecture and hold interdependencies?

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