Understanding the three V’s of big data

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Big data is now big business for many companies. Organisations that are able to harness the power of this technology can gain much greater insight into all aspects of their activities and use it to guide their decision-making.

Whether it is delivering more personalised marketing campaigns to retailers, helping healthcare providers analyse patient data to provide more effective treatments, or enabling manufacturers to speed to the process of new product development, effective use of business information now plays a key role in giving firms the insight they need to succeed in a digitally-focusing environment.

With this in mind, it’s no wonder that International Data Corporation has estimated that the big data market will see a compound annual growth rate of 27 per cent between now and 2017 – to reach a total of $32.4 billion by the end of the forecast period. This will be six times the growth rate of the IT industry as a whole. But despite this, many companies still lack maturity when it comes to understanding the topic and what it can do for them.

A lot of talk about big data evolves around the so-called ‘three Vs’ that many of the technologies can be divided into. Knowing what these are and how they can be applied to your business can be the first step on the road to big data success. Read on to discover these Vs and¬†find out more¬†about how they can be applied to your business.

Volume

The first V, volume, is perhaps the easiest to understand and refers to the huge growth in the amount of data businesses now have available to them. Where once, firms may have only been dealing in gigabytes or terabytes of information, now large enterprises will have to handle up to petabytes of data.

Companies can take advantage of this to get a much fuller picture of both their operations and the wider market – enabling them to spot trends and understand the impact any changes may have on the market.

But this can pose major problems to those firms that still run outdated analytics solutions, as they simply will not be able to cope with the vast amounts of details. As a result, evaluating this information will be a highly time-consuming process and much of it may not be adequately analysed due to these constraints.

Velocity

This leads into the next V – velocity. The need to gain insight quickly will be essential to the success of any big data project. It’s no good gathering information on a prospect if the opportunity will have already passed by the time the results are in. Gartner recently noted that many digital firms will be dependent on spotting crucial ‘business moments’ to guide their strategy – and some of these may only last a few seconds.

Therefore, real-time or near real-time solutions will be a must for any firm looking to outpace its competitors. And if they can use predictive analytics to identify opportunities before they even arise, they will put businesses in a much stronger position.

Variety

The final V relates to the huge increase in the number of sources and types of data firms will be able to mine for information with the right big data analytics tools. This might include everything from social media posts to photos and videos – as well as a growing amount of data collected from sensors and other equipment. Much of this is likely to be unstructured, so traditional methods of storing this in data warehouses will not be suitable for easy analysis of these assets.

But with billions of devices set to become connected to the internet in the coming years – from smartwatches to cars to energy meters – firms will need to find effective ways of extracting this data and turning it into actionable insight.

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