Data Analysis

This might sound too much like software engineering but for any software application’s life cycle, data collection, metrics and analysis should be part of an ongoing process and different aspects of application data should be continuously harvested to understand which business rules have been really effective and which rules are not so effective. Requirements are typically written at a very initial stage of the application development and lot of business rules are perceived to be really effective and hence directly translated into technology requirements without having any solid metrics backing the requirements up.

A continuous loop back cycle (by doing data analysis) enables the application support team to come up with metrics and relevant data which they can present it back to business owners of the application and highlight what aspects of the application need to be improved and what aspects of the application can be sunsetted. This data can also be leverage for future generations of application or can also be used as input to organization’s multi generation plan.

Certainly this is not a very “cool” exercise from a developer perspective as it involves too much “SQL” but my definition of “cool” is : the system in context adds value to the business it supports. If an application uses state of art technology but does not do any good to the business partners, I think it is a waste of company’s limited/precious resources.

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