Understanding Data: Mining Vs. Visualization

[This article was first published on R – Vertabelo Academy Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Here’s a reality check: Big Data has hit us like a speeding truck on the highway of business intelligence. In today’s digital age, we’re generating data about ourselves that were once considered private, and we’re doing it willingly!

From what we eat and wear to where we are at all times, nearly everything is now public knowledge. The data generated is a potential diamond mine for everyone in business, from one-person companies to Fortune 500 A-Listers alike, all thanks to the Internet.

But how do we capitalize on this enormous opportunity? How much data is good data, and how do we make sense of data? BI experts have the answer—and they use big words to explain what the masses are already struggling to understand.

Well, here’s to simplifying two of those big terms. We’re talking about the two that matter the most in making sense of this entire circus: data mining and data visualization.

Data Mining: Diamonds in the Rough

If data were diamonds, wouldn’t you want to mine them? To put it simply, data mining is the process of collecting, filtering, sorting, and classifying big data into usable data. Mining through veins of data helps uncover hidden connections and predict future trends for your business.

Let’s consider the most basic form of data mining. We all love our local food trucks, right? A food truck vendor is well attuned to his regular customers’ whims. He pays close attention to what they order, how they like their food, and when they’re most likely to place orders.

When serving a new customer, the vendor takes note of who the customer is above anything else. He ‘mines’ data about the person by engaging them in a conversation. A well-accomplished vendor can get the customer to talk about themselves and will later remember the details about that particular customer upon their next visit. To retain customers, the vendor offers complimentary condiments, fries, and sometimes a free meal on the house for special occasions.

Each customer fits into various patterns of purchase—some come to him for a single bite, some order in groups, and some promise to pay at a later time. He remembers each customer and treats them differently and consistently, based on his experiences with each of them. Thus, he uses data gathered from his experience to improve his customer service.

In general, data mining is based on three intertwined sciences: statistics, artificial intelligence, and machine learning. The e-commerce giant Amazon collects data based on a user’s purchase and browsing profile to promote upsells with their famous ‘People who viewed this also liked’ functionality.

However, as data mining technology evolves to keep up with the limitless potential of big data and affordable computing power, you get to bypass all of the technical jargon and cut straight to cracking the proverbial nut. With our current advances in tech, the more complex your data sets, the more potential you have to uncover relevant insights. You can use data mining to discover relationships among everything—from demand, advertising trends, and customer demographics to how the economy, innovation, competition, and social media will affect your business models, revenues, operations and customer relationships.

Data Visualization: Polishing Your Diamonds

Now that you’ve mined the raw diamonds, how do you make them shine? Data visualization is the answer to making clear sense of your data. Data in its raw form is just a truckload of numbers and words that are too complex to comprehend. Time is of the essence—we need to process all of this data faster. And to that end, we embrace our inner artist!

To quote dear Stephen Hawking, we’re just an advanced breed of monkeys. For all our big and graceful words, our brain still processes visuals 90% faster than text! Data visualization is the practice of communicating information by displaying it in pictorial form, using points, lines, bars, and colors. Data visualization helps you see your data clearly by giving life to plain old numbers.

Say you’ve collected data on leads generated during a digital ad campaign. You’ve invested resources in four major channels for lead generation, and these are the results:

It’s clear from a single glance at this pie-chart that resources need to be reallocated to Adwords for better lead generation results.

Data visualization is a beautiful blend of art and science. It’s as simple as using pictures to understand a bunch of numbers. From simple pie charts in the 1800s to today’s complex wind charts that depict the speed and direction of wind currents in real time stats, this scientific art form has come a long way.

Data visualization brings out the best in business intelligence. Understanding data becomes a piece of cake (or pie, in our case), which helps you see patterns in your business both internally and externally. For example, you can easily see where your business is struggling and opportunities that can be leveraged to boost your business exponentially. It’s just a matter of seeing the patterns clearly—and good data visualization will help you do just that.

What’s the big, obvious difference?

When you consider diamonds, do you think of them as compressed carbon molecules or glamorous jewels? Data mining involves generating relevant data, and data visualization makes the data easy to understand and evaluate.

Data visualization is the key to unlocking the hidden potential in your business. All the data that you collect just need to be clearly visualized so you can spot the patterns that you’d normally miss. And with a little bit of creativity, simple math, and an eye for detail, you can learn data visualization online. You’ll not only gain a clearer vision of what the data have to say about  various aspects of your business—from finances to marketing and customer relations—but you’ll also have a clear direction for what to do next to expand your business.

The post Understanding Data: Mining Vs. Visualization appeared first on Vertabelo Academy Blog.

To leave a comment for the author, please follow the link and comment on their blog: R – Vertabelo Academy Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)