Select Page

The Five Vs Of Big Data

The Five Vs Of Big DataScore 86%Score 86%
Understanding The Five Vs of Big Data

Understanding The Five Vs of Big Data

The five Vs of big data

The five Vs of big data (volume, velocity, variety, veracity and value) are like the five Ws of Journalism (who, what, why, where and when). They’re the characteristics that define big data and what data analysts, engineers and executives need to understand when considering their organisation’s approach to data.

Volume

Volume refers to the size (per unit, i.e., one terabyte) and quantity (number of units, i.e., one million records) of data. How big and how much will vary widely depending on industry, organisation and technological advances over time.

For example, a dataset that is considered big data today may not be considered big data in 5 years, as computing power and what constitutes ‘large data volumes’ is evolving at a rapid pace. In the past couple of decades, there has been an exponential increase in the volume of data that organisations are able to capture. This is the foundation of why big data exists and leads us to the remaining four Vs.

Examples

  • A standard financial services enterprise handles more than 1.5 million transactions every hour, which imports over 2.5 petabytes into their database. For comparison, that’s like having over 40 million filing cabinets filled with text.
  • Thanks to advances in technology such as smartphones and wearable digital devices like watches, it’s estimated that over 30% of the world’s data is generated by healthcare companies and will reach nearly 5,000 device interactions per day by 2025.
  • On a national level, educational institutions collect and store data of millions of students, including grades, test scores, expulsion records, extracurricular activities and more to share with universities for admissions considerations.

Velocity

Velocity is the speed that companies receive, store and manage the data coming in from its various data sources. It’s important because some data will be far more valuable the closer it is to instantaneous.

Consider the world of retail. It’s way better to know which products are out-of-stock in terms of seconds or minutes rather than days or weeks. Telling a customer to come back tomorrow to find out whether you have a particular shoe in stock isn’t exactly a great sales tactic.

Examples

  • In the finance sector, an investment company uses big data to pull trends from multiple sources fast enough to provide real-time stock market insights to help investors make informed decisions with their money.
  • A medical device company receives heart rate data from a pacemaker and needs to process it and produce rapid analysis to provide a reactive shock to restore heart rhythm, preventing serious injury or death.
  • A large university opens enrolment for the semester for tens of thousands of students. The university must process this information instantaneously to provide accurate information as students continue to register for classes until capacity is reached.

Variety

One of the challenges that accompanies the creation of big data infrastructure is all the different sources upstream that are flowing into the data lake. Variety of big data refers to the diversity and range of different data types, including unstructured data, semi-structured data and structured data, along with their disparate sources.

Examples

  • A national bank collects structured data from forms on their website and mobile app, where each field maps directly to a table in their database. However, they also collect unstructured data from customer service phone calls and emails.
  • About 80% of healthcare data is unstructured, including handwritten practitioner notes, imaging data, video and audio files and many more. Many healthcare companies are adopting EHRs (electronic healthcare records) that help structure some incoming data, but the challenge of transforming unstructured big data still exists.
  • A university collects semi-structured data on individuals in a student profile through academic transcripts, purchases made with linked credit cards and admissions to different facilities used with their student ID card.

Veracity

How trustworthy is the data? Veracity in big data can be thought of as its credibility or reliability. If users don’t believe in the data or have too many doubts about its validity or quality, the data loses value and becomes irrelevant, misleading or dangerous. Given the movement of organisations toward data-driven decision-making, weaknesses in data veracity will ultimately impact the choices that executives make.

One of the biggest obstacles to organisations becoming data-driven is their lack of best practices around data governance. Fortunately, ensuring the quality of data at your organisation is something relatively simple, and really just comes down to following a few steps.

Examples

  • A financial firm that allows customers to enter their address without verifying that the address actually exists is more likely to have human errors as people could lie or enter typos, lowering veracity.
  • A healthcare company has discovered that multiple patients have the same Patient ID due to historic sources being consolidated into a new, modern data platform.
  • An educational institution wishes to analyse academic performance amongst all primary school aged children, but different grading scales and standards are used at different schools, making the data unreliable.

Value

From a business perspective, value is the most important characteristic of big data. Value is derived from the analysis, insights, discoveries, and ultimately business decisions and consumer outcomes that result from the data collected.

Determining the value of data requires working backwards to determine what decisions are now viable as a result of the new information, and the expected economic utility of those decisions.

A good way to ensure that useful data is being collected comes from identifying areas where you are lacking information and using that as a basis for exploratory analysis.

Big data analytics

Big data analytics revolves around extracting insights from large bodies of information. Thanks to Big Data analytics, Google Maps can give you the optimal route to any destination, taking into account traffic, weather conditions, road closures and a multitude of other factors that Google collects in its vast datasets.

Organisations that leverage big data will be leaders in the global economy in years to come, regardless of industry. Research shows that companies can save billions of dollars by cutting costs and implementing more efficient processes. By capitalising on consumer insights that big data can provide, the sky’s the limit on how profitable organisations can become. There are philanthropic impacts that big data will have on the world, too.

For example, in the financial services industry, leading organisations use big data analytics to crack down on fraud and money laundering as well as improve compliance with the many laws around conduct, reporting and corporate transparency. This will not only benefit financial institutions, but also society as a whole as dishonest behaviour will be caught and decrease over time.

In the healthcare sector, companies can gain profitability but also help save lives by analysing trends and threats in patterns of data. Big data will have a huge role in the future of genomic research, patient experience, claims and billing fraud and more.

Organisations need skilled people effectively utilising the latest data engineering technology to keep up with the rise of big data and benefit from the value analytics provide. We get it – data projects can be difficult to actualise within an organisation, especially when internal stakeholder approval is needed. Aginic hires and trains individuals who are experts in engineering and data, capable of creating complete end-to-end data solutions that help create lasting change.

Review

86%

Summary The five Vs of big data (volume, velocity, variety, veracity and value) are like the five Ws of Journalism (who, what, why, where and when). They’re the characteristics that define big data and what data analysts, engineers and executives need to understand when considering their organization's approach to data.

Focus on Topic
100%
Use of Multimedia
90%
Level of Research
100%
Academic Assessment
98%
Contemporary Need in Coming Years
100%
Language
100%
Authenticity
100%
0%

About The Author

admin

I am an electrical engineer with a Masters degree in computer sciences.

Leave a reply

Your email address will not be published. Required fields are marked *

RECENT VIDEOS

Loading...

Understanding The 5 Vs of Big Data

Exams Academy Shares Some Thoughts On Time Management

Take Care of Your Emotional Welbeing

Benefits Of Blockchain Technology

Differences Between AI & Machine Learning

Why Is 5G Technology Different Than 4G

Do Books Really Influence You?

RSS Exams Academy

  • AI (Artificial Intelligence) and ML (Machine Learning) Certifications
    Value of any certification depends not only on the name but also on the skills and knowledge you gain during the certification process. Be sure to choose certifications that align with your specific interests and career goals. Additionally, the AI and ML landscape is continually evolving, so staying up-to-date with the latest trends and technologies […]
    admin
  • Professional Certifications That Will Be In Demand In 2024 and Beyond
    Predicting the exact demand for professional certifications in 2024 and beyond is challenging, as it depends on various factors. However, based on the existing trends and emerging technologies. Also, the job market is constantly evolving, so it's essential to stay up-to-date with the latest trends and demands in your field. Additionally, consider your interests, career […]
    admin
  • How The GRE Exam Is Going To Change In September 2023
    Graduate Record Examination or GRE 2023 is a challenging, internationally valid, entrance test. It is a registered trademark of ETS (Educational Testing Service) which is headquartered at Princeton, N Jersey, United States. This exam is attempted every year by aspirants who wish to pursue a specialized Masters course or Doctoral degree at well-known B-Schools in […]
    admin
  • New Changes in TOEFL 2023 Exam Pattern
    TOEFL is a Test of English as a Foreign Language which assesses the English skills of non-native speakers as the Educational Testing Service administers it. This test is accepted by more than 11,000 universities and other institutions in over 190 countries and territories for students who want to enrol in any overseas university or college. […]
    admin
  • Most Popular Certifications
    It's difficult to determine the most popular certification across all industries, as different certifications hold different levels of importance and popularity in different fields. To conclude, we would say that determination of the most popular certification depends on various factors such as the industry, job role, and location. However, some of the most widely recognized […]
    Engr. Saeed Khtar PMP
  • Top 8 Accounting Certifications
    If you are a financial professional, an accounting certification can increase your earning potential and qualify you for more positions. If you are considering obtaining certification, exploring some of the more popular ones can help you determine which is the best fit for you. In this article, the indeed editorial team discusses eight top accounting […]
    admin
  • Can ChatGPT Pass Any Exam?
    GPT-4 is OpenAI’s “most-advanced” AI technology. It can comprehend and discuss pictures and generate eight times the text of its predecessor, ChatGPT (which is powered by GPT 3.5). Here’s a list of exams the new technology has passed… The post Can ChatGPT Pass Any Exam? appeared first on Exams Academy.
    admin
  • Merits and Demerits of Online Examinations
    We have so far seen many advancements in science and technology but the idea of online exams is innovative and challenging at the same time. We cannot be more sure if it should be applied by and large to all institutes. There are many preparations to be done beforehand. There are many systems suggested for […]
    admin
  • Amazing Uses of Calculus in Real Life
    Calculus is used in lots of fields, physics, engineering, medicine, economics, biology, engineering, space exploration, statistics, pharmacology and many more. Without calculus architects and engineers couldn’t build safe structures. It is used to calculate changes in quantities and systems. Calculus helps to analyze, find optimal solutions and predict the future. Calculus has given us incredible […]
    admin
  • How To Improve Reading Retention
    Have you ever found yourself at the end of a book you’ve just finished wondering, what did I just read? (And not in a Gone Girl "what the hell just happened" way.) If you have trouble remembering the finer points of your recent reads, don’t stress, because you’re not alone, and there are plenty of […]
    admin