One of the big IT catch phrases over the last several years has been the term “Big Data”. As in BIG data. REALLY BIG data. So, what is meant by “Big Data”? According to Google, “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.” If you’re like me, this conjures up images of voluminous spreadsheets, covered over by vague word clouds. And if you’ve ever seen the old Tracy and Hepburn movie “Desk Set”, you know the hazards of overloading complex systems with never-ending data. That’s right, lots of explosions and blown fuses.
An infographic from this week’s readings, prepared by IBM, aims to make Big Data a little less elusive by breaking it into 4 dimensions: Volume, Velocity, Variety and Veracity. First, Volume. Volume is what puts the BIG in data. Put plainly, there is a ton of data being created and stored every instant. Second, Velocity. Think of velocity as the speed of data and how it is being processed. Third, Variety. All this data that is being created and stored is coming from a plethora of sources. From Social Media, to Protected Health Information, to GPS, data about we the people, along with our habits and patterns, is being recorded and sent. Finally, Veracity. This is what puts the DATA in Big. This is how the data is analyzed and determined if it is fit for use.
So – what does any of this have to do with EA? In a word, plenty. Enterprise Data Architecture is the development of models and processes which manage the volume of data, the speed at which it is processed, and the variety of sources from which it is coming, so that folks who enjoy statistics and analysis can make sense of it all. A poorly conceived EDA can lead to redundancy, inconsistency, and a lack of understanding of where an organization is and where they want to get to.
Source:
Edjlali, R. (2011, January 28). Data Modeling and Data Architecture; A Required Strategy for Enterprise Information Architecture.
Tracie,
I can’t tell you how many times someone has uttered the phrase “we need big data” at my organization. It shows that we a.) don’t have it and b.) no one really understands it. Especially if they utter that phrase. I think the first step is to understanding what it is and what it can do for an organization. Until then, I am sure that those will still get caught up in the buzz terms.
Matt