Cloud computing and big data analytics are two “terms” that few would have imagined being used in the same sentence. Yet, placed together, the two concepts can offer businesses the ability to engage in big data at a reasonable price tag.

This is the sentiment of PBT Group, who believes that big data is not only a trend, but should be deemed as a key resource that must be protected and exploited to create value for an organisation.

Says Willem Conradie, BI Consultant at PBT Group; “A few years ago, for many of the Internet ‘giants’ it was a do or die period in terms of technology investment, which forced them to invest in alternative technologies to stay ahead of competitors. Today companies are not so much ‘forced’ to but are exploring different technologies. In the search for technologies that can actually add value to the business environment, big data and big data analytics are among these – because it can be exploited in many different ways for an organisation.”

Continues Conradie; “To give some context, in retail, big data analytics can be used to improve customer recommendations – while in telecommunications, network call behaviour can be deeper analysed to develop new, more personalised products and services for consumers – so you can see the value it can bring for organisations looking to really define their competitive ‘edge’.

However, starting a big data analytics project or ‘proof of concept’ can be a daunting and rather expensive task. A company needs the right hardware, software and resources, with the applicable skill set from a technical as well as an analytical perspective, to get it right.

“However, this is where the cloud changes the game and becomes a big data analytics enabler. Cloud resources, in theory, are available immediately, with no lead time required as well as allowing for on-demand analysis. Additionally, data of any type can be loaded into the cloud, analysed as and when needed, and when complete, the cluster can be stopped and discarded – or additional data and capacity can be added – depending on the outcome of the analysis.”

Cloud architecture also alleviates the highly specific technical skills required to keep a big data system up and running. “These types of skills are rare and have a high price tag, where procuring them can be a time consuming process. Therefore, making use of cloud computing lowers the cost of entry significantly, especially when it comes to big data analytics”; continues Conradie.

Of course, cloud computing does comes with certain risks. A few aspects that need to be considered are the privacy and service level agreements, as well as the security and data protection, location of data and legislation and regulation. These factors are also very much dependant on whether the business is making use of a public or private cloud.

Continues Conradie; “Data privacy and personal information protection today is always a slight challenge that companies need to be mindful of. However, there are possible solutions to this. Some examples include masking data when loading it into a cloud, or using a cloud encryption gateway to encrypt the data.”

“Challenging as it may seem to be, a big data analytics project doesn’t have to be all about the technology – especially given that cloud computing alleviates a lot of the upfront costs and barriers in this regard. As no hardware procurement is necessary, computing capacity is dynamic and can be adjusted on a per analysis basis, which means that performance is on par with physical hardware and any type of data can be loaded as required.”

“Cloud computing supports the iterative nature of big data analytics and allows data practitioners to focus on the data itself and how to really derive value from it – to ensure a business remains competitive – isn’t that what we all want?”