Big Data & Data: What Makes The Difference ?

April 29, 2019

We’ve been capturing data for years, which means data has always been here. So what’s the difference between data and Big Data? The answer is scale. In order to qualify as “Big Data”, the amount of data has to be big enough that it requires computing capabilities to analyze it.

The sources of data significantly increase and vary in type and timeliness. There are now six characteristics of Big Data, as is said by some, becoming known as the 6 V’s of Big Data. To dive down that rabbit hole, click that link.

Here we’ll focus on the primary three: volume, velocity and variety, but we’ll touch upon the other three characteristics, a.k.a. the sizzle, as well.

Volume: How much?

To give you a glimpse of the amount of data we’re generating, Google receives more than three billion queries every day and Facebook has more than 10 million new photos uploaded every hour. The amount of data we generate is astronomical and it is growing exponentially. That’s BIG.

Constant technological advancement has enabled real-time data collection in large volumes. Location, voice and text queries, the burger you bought for lunch via a payment app, are all data points that result in you becoming analyzed and segmentized.

Velocity: How fast?

Velocity refers to how fast the data is processed. The flow of data is massive and continuous. We upload hundreds of hours of video on YouTube and send over 200 million emails through Gmail in a single minute.

Data flows through every aspect of businesses. One form of tech playing a very important role in this is the Internet of Things (IoT). IoT devices are all around us -- mobile phones, light bulbs, refrigerators, cars, industrial machines, and so much more. Thanks to these devices, our digital trails are enormous and, of course, happening at high velocity.

Variety: How many?

The variety of Big Data refers to the various sources and types of data.
Sources of Big Data are everywhere. They can be either computer-generated or human generated. Computer generated sources include web log data, point-of-sale data, sensor data (RFID tags or GPS data), etc. Human-generated sources include click-stream data, input data, and gaming-related data.

Types of data refer to emails, text messages, video, audio and image files. Your blog post, social media feeds and even store visits are all data. Demographic information, interests and personal preferences are what data collectors want.

By combining various data sources and going after different data types, variety is perhaps the most important Big Data characteristic. Without variety, volume and velocity are out of reach.

The Sizzles to The Three Vs

On top of the three core Vs, a simple question can be asked to understand the importance of the additional three Vs of Bid Data:


Are there any biases, noise, and/or abnormalities in the data?


How long is data valid and how long should it be stored?


How correct is the collected data; is it 100% relevant?

That’s the general scoop on Big Data today, 6 Vs to rule them all.
As data valume’s grow, high velocities are reached and variety stays prevalent, Big Data will live forever.

Understanding the fundamental characteristics of big data is a BIG leap forward to leveraging its comparative advantages for better consumer experience and more efficient business practices.

Let us know in the comments below if you want to know more about the Sizzling Vs of Big Data!

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