Four Ways to Look at Big Data

Four Ways to Look at Big Data

January 30

I mentioned in a previous post that according to a Gartner report, 4.4 million IT jobs are expected to be created globally by 2015, with 1.9 billion residing in the US alone. One of the biggest driving forces fueling this growth is “Big Data.”

Gartner also reported in a recent Info World article that not only is Big Data providing billions of Americans with jobs, it’s also expected to drive IT spending to $3.8 trillion in 2014. As Big Data gets, well, bigger, so does the need for Big Data management skills.

But let’s back up a bit. What exactly is all of this Big Data?

Basically, Big Data is just lots of data (surprise). According to IBM, Big Data consists of the 2.5 quintillion bytes of data we create every single day. As the information technology industry grows and as more information is digitized, more data is created. When a data set becomes too large and complex to be processed using traditional data processing applications, it becomes Big Data.

Big Data can provide organizations with useful information, which can be extremely beneficial assuming they can sort and analyze it properly. But, the bigger the data, the more advanced tools must be to capture, store, search, share, and analyze it.

In order to process queries and manage vast quantities of data, you’ll likely need specialized software and hardware with capable processing power, along with expert employees specially trained in Big Data management.

In addition to thinking about what tools you’ll need as your data grows, you’ll want think about the various facets of Big Data. IBM recommends you look at it in terms of the four V’s of Big Data:


Volume refers to the amount of data. Every day more data accumulates: emails, tweets, documents and so forth. Are you working with gigabytes, terabytes, or even petabytes?


Velocity refers to speed. The latest information is the most useful, but you can’t obtain that information if you can’t analyze the large quantities of data quickly enough. A marketing survey you sent out three month ago contains outdated information if you finally finish analyzing it today.


It’s important to take note of the different types of data; there can be dozens. How do you analyze a growing database of emails, sift through thousands of relationships, and target specific groups for various email campaigns? How can you find where your company’s name has been mentioned in various social media outlets? How do you keep track of all of your various backup images?


IBM asserts that one in three business leaders don’t trust information they use to make decisions. What good is information you can’t trust, and why are you acting on it at all? Trusting Big Data becomes more difficult as it grows larger. The difficulty also heightens the need for reliable analysis tools.

This growth and expansion of IT spending and data processing is great for the IT industry, but education and training in Big Data analytics and management isn’t keeping up with the growing need employers have for these skills. In many cases, the data has grown beyond traditional IT skill sets which means that those with Big Data management and analysis expertise will be in high demand.