THAT’S SO META, DATA
So you go to the supermarket and pick up a tin of milk, then you throw it in your trolley. You pick up a tin of beverage, and in it goes. Sugar, in it goes. Soap, favorite cereal, bread, snacks, drink, toothpaste, same thing. You are on your way to checkout, but something keeps gnawing at the back of your mind, so you slow down as you try to let it come to you; what did I forget? You scan your trolley and mentally check the items off one-by-one, then it hits you, AHA!
You forgot the lotion. You search for the aisle with body lotions, locate it, and move. You get there, and search for your preferred product, but you don’t see it.
Hmm.
You walk up and down the aisle again, convinced it’s there; you just missed it. But you check again and find out you didn’t miss it; it’s just not there. You turn to locate the nearest salesperson and ask them about your product. They walk with you to check, and then they confirm your fears; they’re out of stock, but then they ask, would you like these other ones? They’re good too. In fact, he can swear this particular one here (he picks it up and hands it to you) is better than the one you are looking for, because his girlfriend’s aunty’s friend swears by it. You stamp down on the question that threatens to arise — how do you know what your girlfriend’s aunty’s friend uses? — and you take the product offered hesitantly, before your eyes go down for a second and back up to his face, but it is enough time for you to recognize that the logo on his shirt is the same as the one on the product in your hand. You chuckle to yourself and say to yourself “this one wan guy me sha”. But you don’t automatically throw it into your basket; you turn it around and begin to scan the words on the container, looking for something, anything familiar. You don’t necessarily recognize the words there — all the chemicals and vitamins are nothing but a jumble of words, but you look for similarities between what you are seeing, and what you think is on the back of your favourite product. Not convinced enough though, you drop that product and pick the one you used to use before you began to use the one that’s now out of stock. You don’t want to use it for too long though, so you pick the smallest one, toss it in your trolley, and wheel away, while the salesperson rearranges his products.
Now, assuming this is/was you, sit back and ask yourself a few questions:
a) How many times have you gone to the supermarket to pick up something, and turned it around to read the ingredients/content?
b) Why did you do so for this particular lotion?
c) Why’d you think it was important?
Get Raymond Elenwoke’s stories in your inbox
Join Medium for free to get updates from this writer.
d) What goods do you normally do this for?
e) How does this affect your purchasing behavior?
There are a few more questions I could ask, but I’ll leave it at these 5.
In our little illustration above, what you did was look for data about the product you were looking for. When we look through the perspective of data as a product, we could say that you were looking for data, about the data you wanted to use. In this case, you were looking for some form of standardization that could help draw similarities between the data you were used to, and the one you were being handed. However, because you found none, you dropped the data and picked one you were familiar with.
What you actually did, was look at Metadata.
Metadata is, well, data about data. It is information that explains the makeup, structure and content of the data you have extracted or have created, and it helps you or any user decide if, when and how to use it. Learning about this in the 3rd course gave me some flashbacks to my time in Audit. As an Auditor, I was trained to appropriately label and classify my working papers. The reason for this was so that if it had to be revisited by anyone other than myself, the user would have no trouble understanding what he/she was looking at, and could decide how best to use the information. So for every time I was called on the phone (rarely) to explain something I had done, this was an indication of my failure to create metadata.
On the other hand, Kaggle babble. Yeah, got a Kaggle account now, so you can say things are heating up.
Getting back to learning SQL again looks like fun. We’ll see how that goes.
On to the next one.
