As BI professionals we would have to have our heads buried in the sand to miss the storm building on the horizon. That storm is one of events. Lots of them. Think about RFIDs, credit cards transactions, telephone call data records (CDRs) or even partial CDRs for pre-paid customers. Also click streams, business process messages, and SOA where the whole thing runs on event messaging. Where is this taking us? We are headed right into event driven automatic analysis, and volumes of data like we haven't seen the like of before.

In my hotel room recently I was watching CNN and a discussion about how Hong Kong Airport is starting roll out RFID baggage tagging added to our luggage labels. In a year or two it will just be part of the norm in every airport. Retail supply chains and logistics operations are all heading down the RFID road and have been for some time. Anti-money laundering (AML) and Risk Management in banks are applications that demand automated action. Customer level risk management is starting to require credit reduction or 'close off' across all credit risk products as soon as one goes delinquent. Fraud is already a real-time automatic analysis application in banking.

In my opinion it is time we started to think about preparation for event-driven BI. Many of us are already doing event-driven data integration but that is just the beginning. The consequences of event driven are significant. With the demand for lower and lower latency of data we may not have time to move data into a warehouse and out to a data mart before analysis. We may have to analyse as soon as the data arrives in a warehouse (this capability is already supported in Teradata and IBM DB2 for example). This puts pressure on DBMS scalability. In some cases we may have to analyse before data reaches a warehouse (i.e. Business Activity Monitoring). This can be done by invoking scoring or predictive analytics services from a data integration flow or even from scoring model workflows that are event driven.

In my opinion this means we are heading for an era where automatic analysis will start to come into its own. Cognos has recently acquired Celequest in this area. Other large BI vendors will no doubt follow the Cognos lead and head into this market. Well before the Celequest acquisition this market has been growing and is vibrant today with vendors like Actimize, Fair Isaac, SAS, SeeWhy, SPSS, ThinkAnalytics and Tibco , to name a few, all competing for business.

In the hype of BI 2.0 there is a new lease of life to data mining. Back in the '90s the image of data mining was seen as only for the few and we had visions power users with double PHDs in statistical analysis. Today we are way beyond that. Now the bright power users are still there but the real value is once these models are deployed to be the 'look-outs' for patterns in data and for specific events occurring all over the enterprise. Event-driven in-place real-time scoring in the database is already happening in several of my clients and is growing, especially as SOA takes hold in organisations. The implication is lots instances of atomated analyses running concurrently in the BI system alongside 'classic' reporting and analysis. Workload management in DBMS products and BI servers will become even more critical to allow this new workload to run alonglside increasing numbers of concurrent users. This storm is coming. Time to get ready and re-visit your BI architecture to see if you can support it.