information strategy

Archive for the ‘Architecture’ Category

In his article Analytic Databases Power BI Boom, James Kobielus notes that analytic databases have been largely ignored in the BI industry merger spree of the past few years. He predicts that analytic database vendors will develop or partner to offer BI appliances with built-in analytic applications, and that these BI appliances will be particularly attractive to mid-market customers. I think he’s right - DW vendors will need to do something to differentiate.

This begs the question, though, if it’s the applications that mid-market customers will buy, why will they care what database is powering the application, and doesn’t this still sound a lot like plumbing? Furthermore, if database vendors or partners begin offering DW SaaS, customers should not need to know or care what powers the service. Isn’t that one of the main ideas behind SOA?

So, I say, let the best BI apps win. I think that BI applications or SaaS are most likely to succeed where the data sources are themselves packaged suites or SaaS. That’s because, having built my share of successful business intelligence systems, I can confirm that it’s the “gezintgas and gezoutgas” (inputs and outputs) where the lion’s share of the development and maintenance cost is consumed. Only when the sources and uses of the data are reasonably standardized, can we get enough repeatability.

Not to say that more granular SaaS can’t work. In Persistent Storage for Amazon EC2, Werner Vogel from my alma mater, Amazon.com, announced that beta EC2 customers can stand up raw storage in sizes ranging from 1 GB to 1 TB. EC2 also provides the capability to copy a snapshot of the data into their S3 distributed store. It would be interesting to see how this would work for building OLAP cubes or other specialized analytic data structures using these capabilities.

So database vendors may try to differentiate by building analytic appliances, but if cloud computing services like EC2 keep advancing, cloud computing may eventually give traditional vendors a run for their money.

Information architecture should be founded on basic principles. These principles can also be used to evaluate the “goodness” of a given architecture. A good discussion of the characteristics and components of architecture principles can be found in the TOGAF chapter on Architecture Principles.

I think that principles, in turn, should be founded on a set of core values. I’ve distilled some some of the core architecture values that I’ve used in the following table:

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In the article The origins of today’s OLAP products, Nigel Pendse chronicles the history of OLAP (On-line Analytical Processing), tracing the ancestry of the technology as far back as 1962.

Personally, my introduction to BI (Business Intelligence) technologies doesn’t go back quite as far. In the late 1980’s, I worked for a systems integrator, developing and supporting COBOL applications software. Around this time, we noticed that our customers were increasingly spending time and money on reporting tools and report development.

At the time, we used report writer (designer/generator) tools. Sophisticated users generated report specifications using the designer; the generator tools translated the report specifications into COBOL that could be compiled and executed to produce reports. These tools seemed to work pretty well, and they certainly were a big improvement over hand coding. The main problem, as we soon learned, was that report writers generated reports - and lots of them. So it wasn’t long before I found myself standing before an customer’s executive committee to explain why they had four “green bar” sales reports for February in hand, none of them matching, and all of them “wrong”!

Upon investigation, I came to suspect that the reports didn’t jive because:

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