The Data Dive

The Perfect System

I am continuing the Tron:Legacy metaphor.

In this movie the arch bad guy, an Artificial Intelligence (A.I), horribly misinterprets the requirements of his maker.

His maker said, “Go forth and build me the perfect system.  BTW could you also manage all the other AI’s too while you are at it. I am going away to contemplate my navel”.

The bad guy did not start out as bad. He had the best of intentions. In his mind the perfect system was efficient and orderly. He manifested his interpretation of his maker’s will precisely but it was at the expense of creativity and openness.

In the end there was a revolt and the bad guy was overthrown.

I have been thinking, “What lessons can we learn for our world?”

Apart from that we should be careful about our requirements, pick a decent project management team and for goodness sake monitor project progress, what else?

It’s an ever changing world.

The systems we build need to adapt. Now of course there is the factor of obsolescence in any technology we use. That’s life!

However we can allow for this in our Enterprise Architecture.

So how have we addressed this at Apurba?

At Apurba we work with data, lots of data, from the big to the small and almost anywhere in between. We work in financials and so we spend a lot of time with eXtensible Business Reporting Language (XBRL).

We work in construction, energy and transport (more XBRL).

We work in health care and HL7 & CDA.

We work with standard XML, RDBMS and other disparate sources of data.

It could make us quite desperate, but it doesn’t, because we have a dynamic system architecture. This week we talked about this architecture in BigDataScience, Stanford.

Realized by allowing new components to be added and old ones removed dynamically.

This principle  is in our flagship Lyticas family of analytics products.

Our clients can mix and match the services they need to meet their data analytics goals.

This can be an evolving processing and our clients don’t need to build their analytics capability with just Apurba products alone, our architecture allows products from other vendors to be added too.

So how do we do this specifically?

To get a bit more technical, we separate our data driven and event driven components. We then set up a mechanism for communication between components / services in our architecture.

The other principle we live by is to use the appropriate methodology for the scale of systems we have been entrusted to build.

There is no point going through an intense Enterprise Architecture methodology for developing a single web service.

We have Agile for the small, however it does help us to know the Enterprise Architecture landscape of our client’s environment to craft the most optimal solution.

Now I am going to stop here before I get too heavy. From my blogs you may gather I like methodology. I like it a lot. I like to learn from the experiences of others as well as my own screw ups & successes. However it must all be used in the right context and at the right time.

So what’s the thinking?

To seek perfect systems where every requirement is met perfectly for all time is folly.

To ensure our solutions can cope with change is smart.

To reach the two, one needs to accept that things will change and build the architecture to cope.

Thanks for reading.

Categories: Analytics, Big data, XBRL

Data interoperability » « Compliance and analytics – Two sides of the same coin

2 Comments

  1. Great quality of information. In the beginning, I thought your post was too long, however it needed the length.

  2. Was researching for some time before finding your post. Very helpful. Maintain the great writing.

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