Business Intelligence and the Semantic Web

Analytics strategist Seth Grimes was in town last week speaking in Covent Garden on the subject of Web 3.0. For those still catching up with what this means then the evolution of the web is generally thought of as;

Web 1.0		Retronym which refers to the web as largely a publishing paradigm
Web 2.0		The interactive web characterised by the rise of social networking
Web 3.0		The semantic web. Functionally rich and understandable to machines as well as people
Die Hard 4.0		Fourth instalment of the Bruce Willis franchise released in the US as Live Free or Die Hard

Whilst web 3.0 is some way off there are some early glimpses into the world of possibilities with search engine innovations from Google and Wolfram Alpha. Fellow BI blogger, Peter Thomas who also writes about this subject in his blog Literary Calculus uses the example http://www.google.co.uk/search?&q=age+of+the+pope.

What interests me about the semantic web though, has much less to do with what might be described as contextually aware searching and more to do with the impact on Business Intelligence.

BI, since the 1970's, has been almost entirely focused on numbers. This is understandable given that these tend to be highly structured, organised and available in databases. Arguably though, this wasn't the original vision. In his 1958 (yes, 1958) article "A Business Intelligence System", IBM visionary, Hans Peter Luhn describes the objective as "to supply suitable information to support specific activities carried out by individuals, groups, departments, divisions.." and what Luhn goes on to describe is statistical analysis of text and documents as information sources.

Seth Grimes, in his Intelligent Enterprises article BI at 50 Turns Back to the Future makes the point that BI has more latterly revisited this original vision on the analysis of text and document sources which, after all, reflects the vast bulk of corporate data.

Early innovators, including my own company Artesian, are already making progress in the field of analysing documents for the purpose of business intelligence. This new breed of semantically aware business intelligence technology can "supply suitable information" to "support activity" by answering questions like;

• 'which of my competitors are growing and which are declining?'
  
• 'are my customers launching initiatives that could be supported by our products or services?'
  
• 'do market behaviours indicate a declining need for our products?'
  
• 'how did customers respond to our competitors when they changed their business in a way that we are also considering?'
  

This isn't to suggest that semantically aware BI should function like search engines. Indeed, I would strongly argue that it should not. Search engines deliver a single set of answers to a single ad-hoc question. Business processes are much more frequent, diverse, repeatable and involve wider audiences. Further, businesses require scalability and high degrees of automation. Here, the business questions need to be regularly monitored, visualised, distributed, shared and collaborated around. Interestingly this has more in common with today's best practice BI systems. So there it is. The shape of semantically aware BI is emerging through the fog of future developments and it is unsurprisingly an evolution of what is best about business intelligence as we know it today with some breakthrough thinking that will unlock meaning from the colossal volume of corporate and online documents.