Data has gotten BIG for every industry, but it's really apparent in marketing. It's not just that you have hundreds of data sources to review before making decisions. Those sources also capture a huge range of data types. Depending on your role, you might encounter quantitative (measurable information represented by numbers) and qualitative (descriptions usually represented by words) data about conversions, customer service interactions, social media impressions, or A/B testing. It goes on and on.

What is "big data," exactly? Data scientists use velocity, variety, and volume (they call them "the 3 V's") to determine whether a dataset counts as "big data." There isn't a concrete definition, but the term certainly pertains to marketing campaigns that collect millions of rows of data. When you pull data points from a dozen social media profiles, your e-commerce platform, your sales team, customer service representatives, and who even knows how many Google Ads campaigns... there's no doubt that you work with big data.

The obvious problem here is that the human brain can't process that much information in a lifetime. That's why data analysts and developers have built tools that simplify everything from collecting information to spotting trends. Even with data analysis on your side, though, it's often challenging to determine how you can use big data to your advantage.

Data visualization for big data has become essential for marketers and other professionals who rely on data points.

If you're completely new to big data visualization, even the tools people call "user-friendly" can seem impossibly complicated. Don't worry too much. We're going to break down the basics and introduce you to some big data visualization tools to get you started.