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by Graham Cookson
in Big Data
on 06 June 2014

What is big data? Part 1: The meaning of big data

In this, the first in our blog post series about big data, we take a look at the meaning behind the term ‘big data’ and why it is important for companies to use it...

The Internet is a perpetually growing environment, and every minute it’s estimated that more than 570 new websites are created, over 277,000 tweets are made and there are nearly 2.5 million Facebook shares; that’s a huge amount of data in just 60 seconds.

With this growth comes an issue of data management for companies and, should the right data be found, just what to do with it and how a business should best handle it, so that they too can grow and improve to meet customers’ needs.

However, it should also be noted that big data isn’t necessarily new information created each day. That is part of it, but big data can also comprise of the billions of databases that businesses have been creating and using since the dawn of computing. Companies the world over have server rooms full of structured and unstructured data.

This is where the idea of big data management comes in to help. Rather than becoming overwhelmed by the sheer volume of information out there, or simply missing out on crucial pieces of data that could help a company, big data management tools can help to filter and organise information so that companies can utilise the data for their own needs.

What is ‘big data’?

The terminology ‘big data’ is ambiguous. It is generally a term used to describe the (very) high volume and exponential growth of structured and unstructured data that has been created, either by one source or multiple sources combined.

But big data, doesn’t refer to a specific type of data, or even the physical memory size of data per se, but rather refers to the collection of data sets that are either too large, complex, moving too quickly, or don’t fit the limits of standard database architectures. Because of this, big data needs to be handled in a different way to be able to process it efficiently.

Like the Internet, big data is a constantly moving element and can range from a few dozen terabytes to several petabytes of data in a single set. In 2012, it was estimated that 2.5 exabytes (approximately 2.5 billion gigabytes) of data were created on a daily basis and that number has been growing ever since.

Just to clarify, the basic model iPad has a storage capacity of 16 gigabytes – meaning that in 2012 the equivalent of more than 156 million iPads were filled daily - that equates to just over 383 double decker London buses filled with iPads every single day!

Why is big data important to you?

The proper handling of big data can have enormous benefits, especially to businesses. Primary goals for looking at and managing big data are to help discover repeatable business, find out current trends in markets, understand what consumers are interested in and help organise better communication with clients.

All of this leads to companies being able to make more accurate analyses of what is being said around the world, leading to better decision making, which in turn can lead to cost reductions, more profits and reduced risks on investments.

It’s almost impossible and most definitely impractical to look at every result from a normal search engine. Using big data management and analytics tools, is the only efficient and effective way forward.

Using big data analytics allows users to search for any subject matter or topic of conversation from any source on the Internet, be it a blog, news site, social media or even a forum post – making it wholly possible to look at all those sources and ensure that you are getting the bigger picture.

One key element of using a tool like Digital Contact’s Insights Engine, is that the data is not only filtered by words, but the system uses factors, such as: sentiment, volumes, influence, demographics or location, to determine whether the information is important to the user.

The search results are then filtered to the user’s requirements and delivered in a way that is easy to read and understand.

For example, if you wanted to only know negative comments from sources, to help determine which elements of your company/brand/product are seen in an undesirable light by consumers, then you can. From there, a company can look at ways to help resolve these issues and improve its customer relationships.

So, while a simple search for something like “Apple” can yield millions of results, using a big data analytics tool, you can condense those results into something more meaningful and direct that the user can employ to help gain the edge.


In our next post we explore why big data needs to be handled differently to ‘standard data’ and take a look at a couple of real-life examples of how big data has been used, but not for financial profit or gain, but rather in politics and helping to save lives in the world of medical science.

Click here to read Part 2: Why we need big data tools >>>

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