I have been attending BI and SOA conferences for years and found that the language used at each was different.  Lately though, there has been a convergence of the language used because of the realization that both start from the same requirements – the ‘business architecture’.
Business intelligence enlightens an organization about Information but it has to be relative to the business process à Statistics (why things are happening), Trends and Forecasting / Predictive Modeling (what will happen next and will it continue) and finally Business process optimization (what’s the best that can occur) all require an understanding of the data in context.  Most BI solutions or data warehouses are information integration solutions that bring together disparate information sources into a single well documented solution (with metadata) and are often updated daily. A BI solution requires a managed information architecture / environment which includes:

  • Basic Metadata – reporting and operational
  • Common Communications – semantic consistency, dictionary
  • Data Architecture – data models, taxonomies, ontology
  • Trusted Data (data quality) & Usage (data governance)
  • Information Delivery - reporting and I even included data services

Not all BI solutions require or use a single integrated information source. An example of this is an organization that utilizes an ERP (like SAP, Peoplesoft, etc.) – although, they may still wish to develop customized reports using a BI package.  Go figure…
Services based architectures (including web services) required that we break the solution or application into small business chunks [UoW] that support the processing of these services.  Information about the processing becomes a natural output of this and this information occurs and is collected in real-time. Building Services Oriented Architectures [SOA] also required managed information architecture environment which similarly included:

  • Metadata and Meta-process information (enhanced beyond reporting)
  • Common communications – processes (business rules, choreography, orchestration, event-correlation), messaging (mechanism – MOM, delivery)
  • Enterprise Architecture – component or flexible implementations,, defined layers of abstractions
  • Data layer abstraction
  • Governance – architecture, security, SLA’s, applications, portfolio, etc.

Next came a common integration point known as Master Data Management – something that required both disciplines. I think that this was the impetus for the convergence of SOA and Business Intelligence.  It required the real-time integration of multiple applications (services based) but also the trusted data foundation (information architecture). It was a given that both solutions were developed using the business architecture as the source of requirements, and that both required structured communications (metadata) and governance (data at a minimum).
The IT community has sensed that there is a need for an overall integration architecture or method that we employ to the integration of systems and data and these terms we use should be consistent.  Just as the builder, electrician and plumber can all communicate, we should learn from them.
The need for this language, though, should not be isolated to or developed by one vendor but used by all vendors. I proposed that we start such a process to keep us all sane!  I will volunteer to head the IEEE, ANSI or other committee – hopefully all will bless!
Next, I will write about why IT should be an enabler to the business…”