all bits considered data to information to knowledge


Who mines the miners?

Organizations like to keep their cards close to the chest.  For a long time BI/analytics was all in-house affair: tools, skills and - especially! - data. The shift towards distributed computing models such SaaS and PaaS change everything.

The data needed for analysis might not be owned by the company; it might live - virtually - anywhere: public domain, subscription service, social networks such as Facebook, geographical data from Google Maps or Microsoft Earth. This is the secret ingredient for the analysis, and just as every true secret it hides in plain sight.

SAP has announced that its flagship analytics BI - Business Objects 4.1 - will have even tighter integration with Google Maps API, going beyond location services…

One can’t help but wonder  what data Google gets to keep for its own analytic endeavors as it tracks each call to its services.  Could it be that the corporate secrets are leaking out through usage patterns?


Extensible Architecture

Q: How to prove to a client that the system is extensible? (an actual question...)

Nail down the client’s definition of extensibility first; it might be possible that her ideas are quite different from yours. Once you are on the same page, make sure she understands the limitations of extensibility and ramifications of thereof; for example, she might want a Cadillac but only has a Yugo budget.  

Designing an infinitely extensible system requires both time and budget of corresponding proportions…

 In a single sentence: an extensible architecture would have a modular structure as well as defined set of API(s) for integration; current paradigm leans towards loose coupling, usually via Web Services (latency, concurrency and other inherent limitations need to be carefully considered).