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?
Data Flows Through the BI System and is Consumed as Information
Firstly, in the Business Intelligence arena, the customer is king; and who is this customer? The customer is the end user in the business community, often referred to as the information consumer. The end game is to make information available to the information consumers. So the first component is the understanding of the end user requirements and the business processes in which they exist. This may sound simple but is so often poorly done because the requirements must be interpreted in such a format as to be translated into dimensional models in the data warehouse and/or SAP BEx Query design. This translation is a critical step in true End to End BI practice. Refer to Ralph Kimball’s methods for more understanding of this subject. Secondly, ascertain if you even have the data that will meet the end user requirements, especially if some requirements are aspiration? Do you have an input system that captures the data?
Enterprise Data Warehouse (EDW)
The third component is the data warehouse. The data warehouse can be built on a relational database platform such as MS SQLServer or a best practice OLAP system such as SAP Business Information Warehouse. The optimum design of the data warehouse and the models within it are absolutely critical. For this reason the data warehouse and its business content can be considered the Cornerstone of the Business Intelligence architecture. A well designed data warehouse will have database tables known as atomic level tables; these are very low level detail tables. There usually co-exists another ‘layer’ of tables known as aggregate tables. These tables usually hold summary level data and are designed for performance. You may also choose to implement an Operational Data Store (ODS) or data staging tables to assist with your ETL work. A data warehouse that joins up data from source systems across your organisation is known as an Enterprise Data Warehouse (EDW). You may want to start small, in which case you can implement a single star join schema. In the diagram we illustrate a Star Join Schema by the symbol shown here.
If you are starting small the important thing is build a scalable solution; a solution that you can grow over time and eventually transform into an EDW. The failure to do this will result in so called BI silos.
The fourth component is the data loading and this requires a well thought through ETL Strategy. The strategy will involve the use of an ETL BI program, for SAP BusinessObjects the program is known as Data Integrator. This is the program that will extract the data form your source systems, transform it (clean it etc.), and then load it into your data warehouse tables. It is a very important component in ensuring your Single Version of the Truth.
Business Intelligence Platform
The fifth component is your Business Intelligence Platform and analysis and reporting suite. BI System Builders design and develop with the SAP BusinessObjects BI platform. When using the SAP BusinessObjects suite it is usual for a series of SAP BusinessObjects Universes to be created with SAP BusinessObjects Universe Designer . These universes are responsible for generating the code (SQL or MDX) that is the agent for returning data to the end user via the reporting tools. The end users do not need to see the code themselves; they simply drag and drop objects that contain business data such as ‘Customer Name’ and ‘Revenue’ into their report. Dragging and dropping these two objects into a report would yield a list of revenue by customer name. The universe is interdependent with the data warehouse and reporting tools.
The use of the SAP BusinessObjects universe makes it possible to combine data from different areas. For example if you have SAP Netweaver and a data warehouse built on MS SQLServer it is possible to combine the data from both systems in to a single report via two universes as long as you have common keys in both systems. You can also choose to federate your SAP and relational data via a virtual data warehouse. If you use SAP systems you can also connect directly to R3 via Crystal Reports. In fact there are numerous options available in this area.
So that was a real whistle stop tour through the big bucket areas that constitute Business Intelligence architecture. Of course the description above is very simplistic and the reality can be detailed and complex. For more information on risks and dependencies within Business Intelligence architecture view our End to End BI page.