Big data, business intelligence, and HR analytics are three buzzwords that are discussed frequently. You don’t know very well what they mean? And what added value do big data and business intelligence to bring to the field of HR? This article will explain everything you need to know to answer these questions using different examples. What’s big data? Big data is seen as a four elements traditionally, also called the four V’s.

1. Volume: Big Data must be big. And we indicate really big. We’re not talking about gigabytes, we are talking about petabytes and terabytes. The ‘big’ in big data represents untold thousands of cells in your Excel sheet. In fact, it’s often so large it wouldn’t even easily fit into Excel to begin with.

2. Velocity: Big data is not static, it has a certain momentum. It really is collecting new data constantly. Take twitter data as an example: huge amounts of data represent a huge selection of tweets and retweets another. 3. Variety: Big data has a certain variety. We are not only talking about nicely organized data (data that’s purchased in nice columns and rows). We are also discussing unstructured data (like the info in your average email).

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4. Veracity: Big data is messy and can’t always be trusted. Quality and accuracy are not always present in a large data. Data cleaning is part of the procedure for analyzing big data. However, because of the large quantity of data a few of these little errors can be nullified. The large quantity of data thus makes up for the reduction in reliability of specific data points.

Bernard Marr provides a fifth V: Value. Access big data is no good unless it could be changed by you into value! There will vary opinions about whether big data really pertains to HR. The simple answer is: it does. However, the more nuanced answer is: this will depend. There’re why HR experts aren’t really data-savvy: the quantity of data they use is bound. 1. HR has access to a huge variety of data. Systems containing worker data, pay information, engagement ratings etc. are all examples of organized data. Things like performance email and reviews content can contain interesting information for evaluation – and they are often unstructured.

2. In conditions of veracity, HR data is often quite untidy and unreliable. Data like someone’s career history within the business is often missing: the old date is merely overwritten. Furthermore, numerous reorganizations and restructuring efforts make it hard to keep an eye on how long someone remained in a function.

An example: How do you know that someone has kept the same duties when his job’s function name has changed two times in the last 3 years? 3. Overall, the volume of data in HR is low quite. I haven’t seen a large database with employee records exceed a few gigabytes. This isn’t a negative thing, but it makes HR data the exception always. Usually big data is… bigger. However, for the common HR professional, a few gigabytes of data is already quite something! 4. The speed of data in HR is also quite low. HR data is quite static generally.

Records are just transformed when someone switches functions or when different departments are shuffled. Other than that, the data remains static mainly. 5. HR data most surely retains value. When leveraging the right way it can be used to uncover workforce risks, make smarter people’s decisions and assist in building a competitive advantage for the firm. Does big data apply to HR? Again, It is thought by me does.

HR analytics are ways to create valuable insights into the workforce. This is done through the use of datasets that are bigger than most HR professionals have ever worked with. This is the essence of big data in HR. Let’s take Natural Language Processing and combine this with HR. Most HR departments are seated on large hemorrhoids of unanalyzed, written performance reviews.