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Friday, October 19, 2007

The Opportunity for Business Intelligence: Is it Evolution or Revolution?

Posted by John Trigg

Some recent news on improvements and changes in approaches to BI architectures caught my eye. New technologies suggest that there maybe alternatives to traditional BI architectures (see the recent posting by Curt Monash on in-memory BI and Philip Howard of the Bloor Group on data warehouse appliances).  Though I am not intimately familiar with these new approaches, they seem to suggest the kind of blazing speed and application to some areas, (for instance in-memory analytics and activity monitoring) that overlap with the capabilities of CEP applications.

Maybe a new turf war is on the horizon.

In an article in DM Review earlier this year, Larry Goldman of AmberLeaf took on the daunting task of whether a new event processing technology is required to support a more responsive BI architecture. Larry posed a series of questions for determining whether you should go the CEP route or can make do with existing technology. In light of the new commentary referenced above, I’d like to augment/question some of the thoughts in the Goldman article to show that there are other criteria that argue for going the CEP platform route and that, as we are fond of saying, it’s not just about ‘feeds and speeds.’

(Excerpted from DM Review January 2007, Customer Intelligence: Event Processing Alphabet Soup) with comments interspersed:

1. Do I already have competencies in real-time messaging and streaming? If you do, you may not need an application [specifically designed for CEP}. If you don't, these products may decrease the learning curve.

Agreed that one may have competencies in real time messaging and streaming in terms of accepting the data and storing it, but are you processing it as it arrives?  You must also consider what benefit you can draw from handling this data ‘in flight’ vs. persist, query and analyze?

2. Can my reporting infrastructure handle operational BI, scaling to hundreds or thousands of users? If it cannot, these tools may be able to scale without forcing you to be a performance guru.

Can my infrastructure handle operational BI?  What is operational BI? I believe it’s the notion that traditional BI tools do great at mining vast quantities of captured, processed and transformed data to produce graphs, charts and metrics.  But how do you transform those graphs and charts and metrics into actions – this is what operational BI is looking at.  And this is where the intersection with BAM, CEP, and EDA comes into play.

3. Can users easily identify or specify events to track? If they can't, these tools may help you identify and monitor events without IT involvement.

Can users easily identify or specify events to track?  One of the things that I think is on the forefront in CEP is technology that can determine or detect meaningful patterns, rather than be programmed or setup to react to known/defined patterns.  We see this as a major wave for CEP evolution.

4. What does real time mean to me? How fast do I need to make decisions? Do I have the people or the processes to react in real time?

I don’t disagree with that.  This was central to the recent Roy Schulte presentation on BAM at the Gartner CEP conference in Orlando (September 2007).  Roy has created strata to show that there are different applications and verticals that have different perceptions of real-time, ranging from those measured in milliseconds (e.g. trading) to those measured in minutes and hours (e.g. supply chain management).

5. Perhaps there is a 5th question here and that is one that presents the unique capabilities of CEP to the audience.  Do I need to monitor event data across time windows (A and B happen within X of one another [or not])?  Do I need to monitor large numbers of permutations of each rule simultaneously?  Do I need to derive or infer activity from my event flows?  Traditional query based approaches struggle with these issues especially if the demand or query refresh rate is high.

As the world of traditional BI architecture evolves and users look to determine whether CEP based architectures are appropriate, it is important to note that there may be additional benefits to the use of CEP rather than just ‘trading up’. Why not look at the two technologies as two parts to a greater solution? Augmenting an existing BI infrastructure with CEP is one approach (in which one applies event processing logic to the streams before they are passed into the data warehouse/analysis layer) as is augmenting a CEP solution with analytics/KPI from an existing BI infrastructure. There are opportunities for both sets of technology and collaboration in this instance may help to clarify rather than obfuscate for the target user.

 

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