In this week’s episode, Katie and Chris walk through what big data analytics are. What criteria separates regular data and big data? What are the four Vs of big data? How do big data analytics play a role in marketing analytics? Why don’t more marketers use big data and big data analytics to improve marketing? Tune in to find out!

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In this week’s In-Ear Insights, we’re talking big data analytics, what is big data analytics? Why do we care about it? And how do we get started with so Katie, let’s start off with just a simple what is big data analytics.

My understanding of big data analytics is it is the analyzing of big data, big data being large, like the term Big Data returns, it refers to volume.

And so it’s large quantities of complex data.

So it’s not just having, you know, five years of Twitter likes, it would be sort of the five years of Twitter likes and comments and sentiment, and all of the different elements that go into it.

And that is what comprises Big Data, essentially.

And so it’s basically data that is larger than you yourself, the human can handle.

So it’s more data than you can just put together and analyze into a pie chart in a spreadsheet, is the basic definition.

And so the analytics part of it, is, you need to find more sophisticated ways to analyze and do something with the data.

And that’s where machine learning and artificial intelligence and coding and all that stuff, Chris, that you do comes in?

Yeah, the tongue in cheek definition I’ve heard is big data is anything that doesn’t fit into spreadsheet.

The more formal definition is exactly as you said, IBM did a bunch of this years and years ago, and came up with sort of this four v framework that defines big data.

It’s volume, velocity, variety, and veracity.

So how much data is obviously a big part? How fast are you acquiring the data is important, right? If it’s just a static database, okay, you can work with that and take samples.

But if it’s like that, the Twitter firehose, and there’s millions and millions of new rows appearing every second, that’s definitely a big data.

Variety is the different types of data within your database.

So again, using social media, as an example, you have text, you have audio, you have video, you have maybe even interactive stuff.

And then the last one, which is always the biggest challenge in data science is veracity, how truthful how good is your data, right? If your data is filled with garbage and errors, then you’ve got a problem.

So big data ana