A Big Data conversation between a rapper and a cashier

3 min readOct 1, 2018

Part 1

A rapper enters a fast food restaurant*
Rapper: I want a burger yo!
Cashier: Which one would you like?
Rapper: Chicken. Cashier: Alright.
Would you like to have any drinks?
Rapper: Yeah. Get me a coke without ice cubes. Also could you add 1 big chicken burger, 1 small beef burger, 2 mini fries….
Cashier: Wait a minute! I’m out of RAM!
Rapper: What do you mean?
Cashier: When you go too fast and say a lot of things, I cannot process it. It’s just too much data to process. Computers also face the same problem.
Rapper: What, really?
Cashier: Yes. That’s why we have the term ‘big data’.
Rapper: I just know about big burgers man. Can you tell me more?
Cashier: Sure. Big data is characterized by 3Vs. Volume, Velocity and Variety. When you said chicken burger, it was low volume but when you added a lot more items, it became high volume. Also, when you started speaking, you were just speaking one or two words per second. But when you added more items, man, you were fast. That’s velocity.
Rapper: I sorta get the idea, man. What’s the last one? Varie what?
Cashier: Variety. Now if you give another order and if you rap, you’ve used 2 different ways, normal order and rap.
Rapper: Yo thanks for the lesson, I’m hungry now, so you better run.
Cashier: Haha sure!

*Rapper enters the same fast food restaurant*
Rapper: Hey! Do you remember me?
Cashier: Of course, we had a great chat last time!
Rapper: Haha yeah! You know what, after going back, I did some reading.
Cashier: Really?
Rapper: Yeah. I found out there are 6Vs of big data, not 3, like you explained the other day.
Cashier:Really? When I studied it was 3! Anyway what are the other 3?
Rapper: I don’t know if I’ll do as good a job as you man!
Cashier: Come on, give it a try.
Rapper: Okay! So the other 3Vs are Variability, Veracity and Value. So your restaurant is open in the morning, its open in the evening and late in the night, even when others shut down. If you’re data is regular and dependable even in unpredictable conditions, your data is exhibiting variability. When there are too many cashiers taking one order, it’s too distracting. When no one takes, it’s no fun as well. Veracity refers to the noises, biases and abnormalities in your data. You check for your data to check if it’s cleaned and relevant. And finally comes Value. You provide me with great burgers, you’re valuable to me. In data terms, you check if your stored data is contributing to the required business outcomes.
Cashier: Wow, you did great!
Rapper: Thanks, now on towards the burgers!

These posts were first written on my LinkedIn profile. For more such posts and other Data Science related ideas, connect with me on LinkedIn here:
https://www.linkedin.com/in/imaad-mohamed-khan-218b3999/