It’s all about the CONTEXT!

Publish date:

## FADE IN ##   A: “I finished first.” B (curios): “First in what?”   A: “I finished first in a competition.” B (irritated): “What kind of competition?”   A: “I finished first in a running race.” B (curious): “How many people ran that race?”   A: “I finished first in a running race that […]

## FADE IN ##
 
A: “I finished first.”
B (curios): “First in what?”
 
A: “I finished first in a competition.”
B (irritated): “What kind of competition?”
 
A: “I finished first in a running race.”
B (curious): “How many people ran that race?”
 
A: “I finished first in a running race that comprised of 2 people.”
B (ridicule): “So you simply out-ran 1 person, duh!”
 
A: “I finished first in a running race comprising of myself & Usain Bolt.”
B (disbelief): WHA…

## FADE OUT ##
 
Each answer in the above dialogue leads to understandability that facilitates the next interaction that eventually ends in awe (or disbelief, whichever way you choose to view it). Each question in the dialogue is answered with context that finally helps in arriving to a conclusion.
 
Understandability comes from context; context determines & defines the meaning of the subject at hand. In the data world, this context is known as metadata.
 
Literally defined, metadata is data about data but upon closer observation, it’s simply data that provides context for other data.
 
For instance, let’s say you have a number in front of you. That number could be anything but then assuming it’s a 10 digit number, you narrow down the possibility of it being a phone number. Why? Simply because of the context of a phone number being 10 digits long. This is the power of metadata. Of course, upon dialing the said number for verification, you could realize that it isn’t a phone number at all; it probably could turn out to be a winning lottery ticket number for all you know; but then you get the point.
 
Metadata comes in different flavors, different types. From a data management standpoint, it could be business (functional), technical or operational. 
 
Let’s explore these types through a library books analogy.
 
A library book has various associated details such as its title, its author, its genre, its ISBN code/tag, its page count, its font, hardback/paperback status, its check-out count, its library location, currently checked out to, probable return-date, etc.
 
Given these details, here’s how the classification will happen:
– Business Metadata: Title, Author, Genre
– Technical Metadata: ISBN code/tag, page count, font, hardback/paperback status
– Operational Metadata: check-out count, library location, currently checked out to, probable return-date
 
In the past few years, especially due to easy internet, smart phones and social media availability, data has grown and how! With data being available 24 x 7, to be able to truly derive value out of it, we need to have the context. And metadata is what provides that context. 
 
Without metadata, this data explosion becomes meaningless and remains simply reduced to a number game.

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