As more companies begin to get to grips with the growing amount of information available to them, one of the key challenges is how they move beyond simply gathering this data to how they can evaluate it effectively.

Getting speedy results has long been a challenge for traditional business intelligence (BI) tools, it was noted by Olivier Rafal, director at Pierre Audoin Consultants (PAC). He told Information Age that solutions need to be agile if they are to provide real-world value for a business and this is often an area where older applications struggle.

If chief information officers fail to provide tools to meet these needs, users will keep buying personal or departmental solutions to work around the problem, which Mr Rafal noted creates potential headaches for data administrators as they lose control of their environment, while reports are likely to be produced that use inconsistent information.

Such demands are only increasing as new technologies such as social media and the Internet of Things greatly increase the variety and volume of data available to organizations. All digital events can now be recorded as data points and this is resulting in a great deal of unstructured information from sources including machine-to-machine interactions, logs, transactions and social postings.

"Unstructured content, whether internal or external to the organization, is a rich source of information that requires new analysis techniques," Mr Rafal said. This could pose problems for legacy solutions if they are unable to quickly extract the most relevant information from this noise and provide users with the answers they need before any opportunities have passed.

Many companies may not even consider this when they first start to implement big data analytics tools, as how the velocity of information creates value is often an under-discussed aspect of the technology, Mr Rafal said. However, problems in this area will quickly become apparent if the chosen solutions are not up to the task.

As a result, speed is set to become a top priority for technology buyers in the coming years. It will no longer be enough for big data solutions to produce accurate results, but they must also be delivering in real-time to have an impact on today's always-moving environment.

Therefore, PAC forecast that 'fast data' technologies and services are likely to make up a major part of the €20 billion ($26.75 billion) that is expected to be spent on big data around the world in 2016.

Mr Rafal stated: "The vertical applications of what we call 'fast data' are many and varied. In manufacturing, it can improve quality, reduce waste, make production and replenishment more effective by analyzing shop floor data in real time."

For banks and other financial services firms, he added it can help prevent fraud by analyzing transactions in real time, while retailers can benefit from improved personalization, offering customers tailored offers while they are still in-store on on their website.

In-memory computing platforms were identified by the expert as one of the key technologies that businesses will turn to in order to achieve this advanced, real-time analytics capability. Companies that have adopted these tools have typically reported they were able to create significant value for their business by boosting the speed of analysis and information delivery, Mr Rafal said.