YOGA FOR DATA


“Now that I know that, I want to know this.” Now that I know we’re obligating the funds too early, why don’t we have better insight into the contractor burn rate? Each one of these ques- tions would require a change to the structure of a database. A slightly different question may require changing how data are collected, stored or queried.


Te Army’s ability to sustain its information systems is depen- dent upon the flexibility of those systems. If those systems cannot adapt to changing information needs, we will see a quick transition to obsolescence followed by another expensive investment in the next generation, or even another overlapping system, maintained alongside the first one. Information-seeking behavior on its own isn’t expensive, but what if you have spent thousands of dollars building an infrastructure to collect the data to provide the information? In other words, we can’t afford to change our minds about what we want to know.


YOGA FOR DATA Our traditional data warehouses are highly structured and so rigid that they have become brittle. We need yoga for our data structures to increase their flexibility, to adapt to


Because both our tactical and enterprise information needs change so rapidly in contrast with our requirements development and system procurement, rarely will we field a system that answers the needs of today’s Army, and never will we field one that will answer the needs of tomorrow’s Army.


information-seeking behavior. Te body of a data warehouse is its schema, a set of constraints that tells what the data must look like. Data must fit the schema to be entered into a database. If we want to add data that don’t fit the schema (for example, if we want to add a contractor burn rate not previously captured), then we must change the schema. While modifying the schema is marginally easier than forcing a human body into a new and difficult yoga position for which it has not prepared, it is still a costly and time-consuming exercise.


One of the underlying assumptions of a modern data warehouse is that the data must follow a common schema—if data is not consistent in description, in how it is measured, then we can’t rely on it to allow us to make that leap from data to information. Tis is a good assumption, but we’re applying it too early. We’re applying it to data collection rather than data analysis.


ADAPT OR FADE AWAY Army readiness depends in part on the flexibility of its information sys- tems to provide information when it’s needed. Sustaining those informa- tion systems is dependent upon their flexibility, and those systems that cannot adapt to changing information needs will soon become obsolete.


Forcing data into a common format complicates the process of pulling in data from other information systems. Imagine if we took the water piped into our houses and immediately separated it based on need. We’d have one tank of hot water with soap for showers, one tank for water with toothpaste for brushing our teeth, one for washing dishes, one for drinking, and so on. If we run out of drinking water, we can’t use the dishwater, because it isn’t suitable. Tis is what we’re doing with our data when we force it into a schema—we’re assuming a particular use, but if we have a different question, it may not be suitable.


NAMASTE, DATA LAKE A more efficient method is what we already do: Transform the water at the point of need, and add toothpaste when we’re ready


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Army AL&T Magazine October-December 2016


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