The big data problem: using AI to manage and leverage it for insights success

Big data has been a buzzword for so long that it’s almost lost its meaning; for many of us, it’s a term we casually throw around without understanding its full definition or the myriad ways we can leverage it to make smarter, faster business decisions.

But it’s no wonder there’s confusion; we create 2.5 quintillion bytes of data every single day, a nearly incomprehensible number that reflects one of the key issues with the concept of big data — that it is, by its nature, overwhelming.

In this article, we’ll explore exactly what big data is and break down why artificial intelligence is your secret weapon in transforming it into insights.

Businesses leverage big data at every level of their operations, from optimizing customer experience and building advertising campaigns to driving strategy and improving their bottom lines.

It’s defined by three primary characteristics, also known as the three Vs: variety, velocity, and volume.

Variety refers to the many different sources big data can stem from and the many forms it comes in, including structured and unstructured. The vast majority of big data is unstructured, which means it’s typically text-heavy (rather than numerical) and difficult to process and analyze. Unstructured (also called open-ended) data comes from places like social media comments, call center transcripts, in-depth interviews, employee feedback, and product reviews.

Velocity refers to the speed with which we generate data — in other words, the rate at which data is processed, analyzed, and stored within our digital ecosystem. Social media is an easy way to understand this; each day, for instance, Facebook users upload 900 million photos to the platform.

Volume refers to the amount of data generated each day (2.5 quintillion bytes, as we mentioned earlier), and it’s this piece of the three Vs in particular that means it’s humanly impossible to manually stay on top of all the data a given business receives on a daily basis.

Together, the three Vs make big data so complex that conventional data processing techniques — aka manual coding and analyzing — are inadequate to break it down into manageable chunks of data that businesses can mine for insights.

This unmanageability with traditional methods is a key aspect of working with big data — but luckily, there’s an easy solution.

Your big data (aka the information you have about your customers — their habits, wants, needs, purchasing patterns, buying behavior, etc.) should be the primary driver behind both the short-term and long-term decisions you make for your business.

This means that the data your business collects on a daily basis is the most important capital you have, so you should treat it like you’d treat any other source of capital — by ensuring not only that you’re collecting all relevant data, but that you’re also maximizing its potential value by making use of it.

But how do you tackle such mammoth amounts of data, especially on an ongoing basis?

If you’re using the right tools to properly leverage big data, it can completely transform the way you interact with your customers, make decisions, and build and implement strategy. As for the right tools: more and more, we’re seeing the benefits of using AI to manage the big data problem.

“Our main challenge was the fact that making sense of and processing unstructured data is time-consuming. When we conduct a survey with open-ended questions, sometimes we get thousands of responses, and coding takes time. Yabble does this for us.”

Paul Di Marzio, Head of Research, SenateSHJ

Even the fastest and most proficient human coders can’t keep up with the tsunami of data businesses receive each day. Instead, we need to take advantage of one of our most powerful innovations: artificial intelligence.

Look at it this way: an unstructured dataset of one million comments is to an AI what a dataset of 50 comments is to a human coder: quick and easy to process and analyze for actionable, profitable insights.

AI-powered insights tools use sophisticated techniques like deep learning, machine learning, and natural language processing to quickly boil down huge sets of unstructured big data into bite-size pieces of information you can use to make accurate decisions either immediately or in the longer-term.

That analytical power makes handling the “volume” piece of the three Vs a walk in the park — and because these tools are also capable of aggregating and analyzing datasets from multiple sources, they’ve got the “variety” aspect covered as well. With Yabble’s best-in-class AI-powered insights generator Hey Yabble, for instance, you can feed in unstructured datasets of any size and from different sources and get richly detailed customer insights in minutes flat.

As for “velocity”? These kinds of tools save businesses considerable amounts of time and money by automating tedious manual research tasks, so they’re cost-effective to use on an ongoing basis — meaning the speed with which your business generates big data is no longer an issue.

AI can help you make sense of and derive insights from the mountains of data you already have, yes, but it’s also an incredibly useful tool to generate targeted data for analysis and insight at pace and cost-effectively.

Need to find out how your customers feel about a new product you’d like to offer? Or what they’re thinking about changes you’ve made to your in-store shopping experience? Send out a survey, collect the responses, and then use an AI-powered insights generator like the Yabble platform to quickly and accurately analyze your new set of big data with surprising speed and accuracy.

Want to learn more about how Yabble can help you manage your big data? Tap the button to book a personalized demo with one of our expert team.