Big Data: Velocity vs. Variety vs. Volume

Here we are again talking about Big Data. It’s no secret that Big Data is making waves across the business landscape as companies large and small take on the challenge of implementing Big Data type analytics databases, software, and infrastructure. While Big Data is generally understood, what many don’t realize is Big Data is not just about the word “Big”. There is a whole lot more that needs to go into your data analytics strategy.

For those who may be unfamiliar Big Data in simple terms is a large amount of data, often unstructured, that can be mined for information. Essentially it’s all about gathering large amounts of data from a bevy of different sources. These sources may include your website, social media, customer reviews, customer support, sales, marketing, and more. This data is compiled and combined to see a larger picture. How is social media affecting customer support or sales? How is our brand perceived online and how is that impacting our sales? These are just some basic examples. In the end, what you’re trying to accomplish with Big Data is gaining insight from a lot of data sources in one platform. Sounds simple, right? Well…

If it were as easy as it sounds everyone would be doing it and doing it well. Unfortunately that isn’t necessarily the case. There are certainly success stories, while others are making their way there. However, in order to better understand how to implement a Big Data strategy we must fully understand the important, often overlooked, pieces to the puzzle. They are volume, velocity, and variety.

Volume

This is one is pretty easy to understand. You are going to have a lot of data, I mean, more than you can possibly imagine. It will take significant storage capacity to house all of the data that you’re bringing in any given hour, day, week, or month. This is basically the reason for the name “Big Data”. The data is certainly that, Big.

Velocity

Ok. Another term we are familiar with, but how does it fit in with Big Data? Well, not only are you going to have a lot of data coming in, that data is going to be collected at a high rate of speed. One of the main reasons organizations are procuring Big Data type analytics is because you can gather your information and visualize it in real-time. Let’s pretend your company just launched a new product and people are coming in droves to purchase, use, and review your product. Obtaining and analyzing data in real-time from your sales team, social media, customer support, and so on will give you way more insight into how your product is being received than simple sales or accounting metrics.

There is more to this part of the story, too. How will you handle this influx of data and be assured the data you are seeing is relevant at that very moment? It takes a properly built infrastructure and capacity to do this. Of course, the cloud is a great way to solve this problem. You can provision more computing power when you need it most (a product launch) and scale it down during normal business operation. This not only offers flexibility in computing but costs as well.

Variety

What may be the most important aspect of Big Data is variety. Big Data is not just about the amount of data that you will be collecting but the amount of data from a number of vastly different sources. Think about it this way. Quantifying your sales statistics is a fairly simple endeavor. For a call center with a large volume of calls you can count leads to sales, close rates, conversion rates, number of sales and so forth. This is pretty straightforward.

Now, think about trying to figure out how social media or Amazon reviews impact sales? How your content marketing channels drive blog or digital content subscriptions? In the past we would have to dig through tons of data and figure this out on our own. An endeavor that is not only time consuming, but may often be irrelevant by the time it’s complete. The bottom line is there is a wide variety of data being pulled in from a variety of sources. It’s important to know what these sources are and how they tie together when creating a Big Data strategy.

In the end, Big Data may scare some people off. It’s not necessarily an easy thing to implement. Then again, when it comes to new technology there are always a few growing pains. However, a solid strategy can go a long way towards gaining success. Learning all you can about how Big Data can influence your company, what tools are available, and how others have successfully implemented will lead you down your own successful path. Don’t be scared to take on Big Data, see it as a challenge that will have lasting positive effects for your business.