The 7 Vs of Big Data in HR Analytics

The 7 Vs of Big Data In HR Analytics

Big Data in HR analytics is transforming human resource management into a new avatar. This is because , HR with the help of big Data, analytics tools and technologies is evolving new, real-life, implementable methods ,to improve and predict the performance of organisations.

Keeping the above in view, it will be quite prudent to discuss what is Big Data and what are its 7 distinct characteristics.

The author suggests that for a better understanding of this blog, the readers should go through the following blogs, which, CHRMP has published earlier:

HR Analytics: Meaning & Importance

How to Get Started with HR Analytics in Your Organisation

5 Best Books on HR Analytics

7 Tips for Effective Utilisation of HR Analytics

1.0 Big Data in HR Analytics: Contents of Blog

The author proposes to discuss the following in this blog:

  • Definitions
  • The 3 distinct characteristics of Big HR Data
  • Additional characteristics of Big HR Data
  • 7 Vs of Big HR Data

2.0 Definitions of Big Data

2.1. Definition as per Wikipedia

Wikipedia defines Big Data as follows: Big data is a field that treats ways to analyse, systematically extract information from, or otherwise deal with data sets, that are too large or complex to be dealt with, by traditional data-processing application software.

2.2. As per the Oxford Dictionary

The Oxford Dictionary defines big data as: Extremely large data sets ,that may be analysed computationally, to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

2.3. As per Gartner

As per Gartner, Big Data may be defined as: Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.

2.4. As per the author

We may define Big Data as following: The use of advanced analytics tools and programs, beyond the ability of commonly used software tools, to look at immense amount of data across numerous systems, within a defined time.

In the context of Big Data in HR Analytics, it means use of multiple data sources to assess and improve HR practices, including Training and Development, Performance Management, Compensation and Benefits Management, Recruitment and Overall Business Performance.

3.0 The 3 distinct characteristics of Big Data in HR Analytics

The 3 distinct characteristics of big data are the following:

  • Volume
  • Velocity
  • Variety

3.1. Volume

The volume of big data must be very huge. Please note that we are not talking about giga-bytes, rather, we are talking about tera-bytes and peta-bytes.

It contains millions and millions of cells in the familiar sheet.

However, this would not fit in an excel sheet.

To understand this further, let us look at the maximum number of rows in an excel sheet. It used to be 65,000 earlier. However, now we have more than a million rows in an excel sheet (1,048,576 to be exact). These increased number of rows are still not sufficient to accommodate Big Data.

3.2. Velocity

Another thing ,we must keep in mind in Big Data, is the velocity of data coming in. It is really very fast.

In the conventional methods, the time taken in gathering, analyzing and coming to a conclusion used to take months and years. Moreover, the data which was being gathered, was static in nature. This was because of the fact that once the data was generated, it did not change. However, in the case of Big Data, it is no more static – rather constantly dynamic. For example, in social media – tweets, retweets, mentions, likes on twitter are constantly changing. There is a constant influx of streaming data. This is posing a great challenge before us.

We may illustrate the hyper-velocity of data on the internet in the best possible way , by the below infographic . It indicates what happens in one minute on the internet in 2020.

Velocity of Big Data in HR Analytics
What happens in an internet minute by @LorilLewis / @OfficiallyChadd

3.3. Variety

Big Data contains variety. Tendai describes variety as follows:

Variety is the quality or state of being different or diverse; the absence of uniformity or monotony.

Variety in Big Data refers to all the structured and unstructured data that has the possibility of getting generated either by humans or by machines. However, unstructured data like e-mails, voice mails, handwritten texts, audio recordings etc. are also important elements of variety in Big Data.

There is huge variety in Big Data in HR Analytics
Variety is the spice of Big Data in HR Analytics

4.0 Additional characteristics of Big Data in HR Analytics: Veracity, Viability, Visibility and Value

Four additional characteristics of Big Data, that have emerged over the years ,are Veracity, Viability,Visibility and Value, along with Volume, Velocity and Variety – which we have described above.

4.1. Veracity

We must bear in mind that Big Data may be quite messy. We may not be in a position to have full trust in it. Further, it may happen that quality and accuracy are not there in Big Data. Thus, cleansing Big Data is a most important pre-requisite before analyzing it. Veracity in Big Data refers to biases, noise and abnormality . Veracity in Big Data also means whether the data , which we are mining for a specific problem analysis, is suited to it or not.

As per reference Gutcheckit , Veracity is the most important V of Big Data. As per them, it is much more important than the other 3 Vs (Volume, Velocity & Variety). Veracity is the biggest challenge before Big Data. Data being relevant and of high quality is ,thus, very significant. Veracity helps to filter through what is important and what is not.

The general dictionary meaning of veracity is : Conformity to facts, accuracy. The Cambridge Dictionary defines the veracity as the quality of being true, honest , or accurate.

In that way, veracity of Big Data means: It must be true , honest or accurate.

4.2 Viability

The general meaning of viability is to work successfully.

Datafloq, describes viability, as carefully selecting those attributes in the data, that are most likely to predict outcomes, that matter most to the organisations.

The scientists believe that 5 percent of attributes in the data are responsible for 95 percent of the benefits.

Keeping the above in view, paying attention to the most important attributes in big data may prove to be extremely rewarding.

4.3 Visibility

The dictionary meaning of visibility is the state of being able to see. We may also define it as the degree to which ,something has attracted general attention, prominence.

Data visibility is basically the clarity of data, so as to perform analytic operations on it. If we cannot see it , we cannot analyse it.

As per reference , rob-livingstone.com, the state of being able to see or be seen implies visibility. They further elaborate that data from disparate sources need to be stitched together, where they are visible to the technology stack, making up Big Data.

We must bear in mind that critical data, even if it is available, but not visible , may prove to be a difficult paradigm in Big Data. Also , unauthorized visibility may prove to be a big risk. Hence, we must be alert all the time.

4.4 Value

Bernard Marr, the author of the book “Data Driven HR: How to use Analytics and Metrics to drive performance”, adds a seventh V: Value. Having access to Big Data is totally insignificant, if we can’t derive value out of it.

5.0 7 Vs of Big Data in HR Analytics

Based on the discussions in the preceding sections, we may clearly say the following.

7 Vs of Big Data in HR Analytic. Image by CHRMP
The 7 Vs of Big Data

To get a better understanding of what is Big Data in HR, we may describe it using the 7 Vs, which are:

  1. Volume
  2. Variety
  3. Velocity
  4. Veracity
  5. Viability
  6. Visibility
  7. Value

If you are looking to upgrade your skills in HR Analytics, you might want to consider a certification in HR Analytics by CHRMP. To learn more click here.


Category : HR Analytics July 25, 2020