TRIFACTA is bringing a visual approach to BIG data management

TRIFACTA is bringing a visual approach to BIG data management

 

Certainly it’s true that people tend to learn more from visual sources than from those which require internal computations. As the saying goes, “a picture is worth a thousand words”, right?  Maybe a better question is, how will a more visual approach to BIG data management help overall?

Let’s imagine that you work in BIG data for a second here. You spend most of your time doing coding duties as opposed to actually performing any analysis on data. Then of course (once you finally reach the analysis phase), it’s something that’s done very quickly. To say that this is somewhat backward is an understatement; after all, the whole point of a job in BIG data is to perform various types of analysis in order to extract useful / important information which adds extra value to what’s already there, of course.

This is the situation that most people involved in BIG data find themselves in – spending most of their time “processing resources” so that they can be hastily examined.

As you know, solutions in computing are always “just around the corner”. TRIFACTA seems to be an organization with some answers to some of the more continually challenging conundrums; they also have some amiable perspectives on the value of the so-called “human element” in data analysis.

What is TRIFACTA doing in the realm of BIG data that’s such a departure? Well, there’s been talk of applying (perhaps) specific software that might make visual analysis much faster.

What’s driving TRIFACTA from a longer-term perspective is also interesting. They are supporting the notion that the costs associated with software and hardware (not to mention, large, scalable computing resources) will continue to become more affordable. The idea is, once this occurs, the value of the work being performed by human beings will only increase in value.  At the same time, this company’s goal is to improve our ability to execute BIG data management. So, perhaps the solution is simply one of numbers? After all, why not just widen the participation level and overall appeal of BIG data; wouldn’t that bring a significant amount of power and immediacy to the situation?

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This sparks an interesting notion though; for projects involving extremely large sets of data, would it not be easier to simply use a greater number of human sorters / analysts in tandem with digital forms of cataloging? Although this is far from a perfect analogy, the image of a horse-drawn carriage piloted by a sole human being comes to mind. In other words, create a platform where more people can actively participate in this relatively new area. The idea would be to effectively create a new class of careers based in BIG data management. Outside of more skilled professionals who work in the fields of software development or perhaps IT, this new group of BIG data analysts wouldn’t necessarily have to have intimate knowledge of those (aforementioned) fields. Through more visual means, the idea is that the computer does all the tedious work and the creative and decision-making elements are perhaps diverted to human employees.

A more visual approach to BIG data would be a great thing in any case, regardless of how it was applied. As previously mentioned, you can’t help but think it is a little bit underdeveloped to spend a smaller portion of time exploring the potential uses and approaches of data analysis vs. a larger time spent doing tasks where the goal is to simply “process the raw materials”.

Once there is a more fully-functional, stream-lined, and overall intelligent way to carry out BIG data analysis, more businesses and firms will be on board as well. This translates into a great deal more opportunities for additional solutions to develop. Likewise, the more diverse the application for the technology, the higher its overall value might climb as well.

The bottom line is that we need more obvious and easy-to-implement approaches to some of the larger issues and hurdles facing BIG data management as a whole. It only makes sense to take a visual approach to organization and taxonomy if you think about it (after all, the visual cortex is one of the largest parts of the brain, right?). Moreover, anything that might be able to spur growth or hiring in the so-called tech industries should be considered constructive, don’t you agree?

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