One of the biggest buzzwords ever, it seems, is “Big Data”. But what EXACTLY is big data? It might seem a little condescending, but for those who aren’t in the industry, explaining big data requires some “dumbing down.” If you’re in the position to explain this to someone with zero experience in it, who isn’t tech savvy, or who comes from an entirely different field, leave the jargon out and instead focus on explanations and similes they’ll understand.
A perfect example is when the CEO asks for a quick rundown—and her background is in corporate leadership, she uses an old smartphone, and simply isn’t on the same page as you. Don’t get frustrated. This is your time to shine.
Big Data is Exactly What it Sounds Like
Here’s an idea of how the explanation will go for a five year old, but feel free to pepper in your own ideas, too. Just make sure it stays simple, to the point and you don’t go off track.
“Big data is exactly what it sounds like—a collection of data that’s so big it’s tough to process. It’s like the US Census Bureau information. That’s way too much information (since millions of people are surveyed) to look at at once.
The biggest problems with this much information is being able to store it, share it with other people, or figure out just what the heck those numbers mean. Usually with data, there are technology tools that can do all this work easily, but too much data is too big of a job for them. Big Data is actually better, smarter use of the data.”
Why We Use Big Data
“What do we want with all this information, anyway?” It’s a great way to spot trends, such as figuring out how many people in your town prefer chocolate ice cream over vanilla.
This information can be very useful to an ice cream company that can’t decide whether to advertise for their chocolate ice cream cake or vanilla one. After all, why spend one hundred dollars on a vanilla ice cream ad and just $50 on the chocolate one when the data says most people prefer chocolate?
I actually prefer the vanilla/chocolate twist… why wasn’t that an option? Oh no! Our data is already skewed!
Data Tells Us All Kinds of Things
Data can tell us all kinds of things, like what type of people are doing what, where the most puppy adoptions take place in each state, and what types of clothes, food or toys people prefer. This is really important for businesses who can use that information to make more money. Otherwise, they might be trying to sell a tricycle for little kids to a bunch of middle schoolers who want dirt or mountain bikes—no training wheels, please.
How do You Collect Big Data?
Big Data Sounds Easy
Using big data might sound like a piece of cake, but whenever you have a lot of something it can be really hard to manage.
Think of it this way: It’s pretty easy to clean your room when there’s just your crayons to put back in the box and a couple of shirts to toss in the hamper. But if you just had a huge party and there are dirty cups, leftover pizza and balloons everywhere, suddenly it seems like it will never get done—even though ‘cleaning up’ is basically the same chore no matter how big it is.
You Need to Manage Big Data Correctly
Size makes a huge difference. Just look at Godzilla—it can easily get out of control. That’s why big data can be such a tough problem to solve. You need to manage it right or it can make things much worse.
After all, you wouldn’t clean your room by trying to vacuum up those dirty clothes on the floor, would you? Vacuums do a great job for some things, but when not used right they just don’t make sense. The same goes for managing big data.
Originally written by Travis Wright on LinkedIn Pulse.
About Travis Wright
Travis Wright is a Venture Catalyst, Digital Disrupter, Marketing Technology Entrepreneur, Interactive Awesomeizer, Technology Journalist, Stand-up Comic & Marketing Consultant.
As a journalism major in college and sports editor on his high school newspaper staff, he has always loved writing and sharing resources, “strategery”, opinions & random hilarity along with the occasional sport or political rant.
Follow him on Twitter:@teedubya or follow him here on LinkedIn: Travis Wright.