Characteristics of Big Data: Understanding the Five V’s

Characteristics of Big Data – A lot has been said and written about Big Data over the past ten years, but it raises questions about how much people know about it. Too often, we just accept the latest buzzword or phrase into our lexicon and use it without fully understanding what it means.

And although there are plenty of resources available out there that go into detail about Big Data, we’re going to focus on the concept by paying more in-depth attention to the often-cited “five v’s of Big Data.” We will review the fundamentals, such as the characteristics of Big Data, its definition, and the Five Vs of Big Data themselves.

So, buckle up, and let’s tackle the basics.

What is Big Data?

Big Data is the collective term describing massive datasets of structured, unstructured, and semi-structured information. This data is collected from a variety of sources and is never-ending. Unfortunately, the data has little to no practical use due to its size and must be collected, analyzed, and processed into useful, actionable information.

Additionally, the nature of Big Data makes it too difficult for traditional data processing software to deal with. Consequently, new tools and disciplines have been developed to deal with Big Data’s challenges.

Big Data is mined to acquire insights and is found in predictive modeling, machine learning projects, and other complex analytics applications. Organizations can monetize Big Data by using it to improve operations, offer their customers better service, and develop targeted, personalized marketing campaigns.


Now it’s time to look closely at each of the 5 V’s of Big Data.

The Characteristics of Big Data: Five V’s Explained

Big Data is characterized by the following traits:

1. Volume

Big Data refers to extremely large data sets that are beyond the capacity of traditional data storage and processing systems. This data can come from various sources such as social media, IoT devices, sensors, and more.

2. Velocity

Big Data is generated at a high velocity and in real-time. This requires systems that can process and analyze data quickly to extract insights and make decisions in real-time.

3. Variety

Big Data comes in various formats and types, such as structured, unstructured, and semi-structured data. This includes data from text, images, videos, audio, and more.

4. Veracity

Big Data is often noisy, incomplete, and inconsistent, which poses challenges in processing and analyzing the data. Therefore, data quality and data cleaning are critical components of working with Big Data.

5. Value

Big Data has the potential to provide valuable insights and benefits for organizations, such as improving decision-making, creating new products, and enhancing customer experience. However, extracting value from Big Data requires sophisticated data analytics tools and techniques.

What’s This About a 6th and 7th V?

Yes, some schools of thought add a sixth and even a seventh V entry to the characteristics of Big Data.


Variability

This characteristic shouldn’t be confused with Variety. If you go to a bakery and order the same doughnut every day and every day it tastes slightly different, that’s a measure of variability. The same situation apples to Big Data. If you constantly get different meanings from the same dataset, it can noticeably impact your data homogenization.

Variability considers the idea that a single word can have multiple meanings. For instance, the word “fold” can be used as a verb that describes bending a sheet of paper (but it also is an action word in cooking, so there’s even more variability!). But it could mean a crease, a bend in rocks, or a group of people united in a common interest or belief.

Since Natural Language Processing (NLP) often uses Big Data resources, it’s easy to see how the variability of language could affect AI and ML algorithms.

Terms keep changing, and the variability characteristic reflects this. Old words and meanings get discarded, and new definitions and words emerge. For example, remember that once upon a time, the term “awful” meant “worthy of respect or fear,” not as a description of how you feel after drinking that milk that was way past its expiration date.

Visualization

Humans are a visually oriented species. A picture is worth a thousand words, and charts and graphs can help readers understand huge amounts of complex better than reports riddled with formulae and numbers or endless spreadsheets.

So, the visualization characteristic deals with changing the immense scale of Big Data into something a resource that’s easy to understand and act on.
Visualization has been called Video on a few rare occasions.

And as if this wasn’t enough, you can Google “the 10 Vs of Big Data” and find even more V’s, such as Venue, Vocabulary, and Vagueness. However, this runs the risk of getting things out of hand, so let’s just stop at the five. Still, consider yourself warned!

How Would You Like to Become a Data Engineer?

Whether we’re talking about the characteristics of Big Data — five V’s, six V’s, or even ten V’s — it’s safe to say that the demand for Big Data-related professionals will remain strong. So, if you’re interested in having a career in a Big Data profession, such as a Data Engineer, Simplilearn has the resources you need.

The Caltech Post Graduate Program in Data Science, held in collaboration with IBM, offers masterclasses that impart job-critical skills like Big Data and Hadoop frameworks, and leverage Amazon Web Services’ functionality (AWS). In addition, you will learn how to use database management tools and MongoDB through industry projects and interactive sessions. Finally, you will benefit from “Ask Me Anything” sessions conducted by IBM experts.

Glassdoor reports that Big Data Engineers in the United States earn an annual average of $125,531. Additionally, Glassdoor shows that Big Data Engineers in India make a yearly average of ₹754,830.

If the prospect of becoming a Big Data Engineer doesn’t interest you, Simplilearn offers other Big Data career options such as Big Data and Hadoop Training.


Big Data is here to stay and will keep presenting fantastic career opportunities for ambitious candidates who want to go far in today’s information-driven world. So visit Simplilearn and get your start on a new, exciting career that offers new challenges, career stability, and excellent compensation and benefits.