Big data analytics: confidence in the cloud

Many have invested heavily in cloud based analytics platforms only to discover their data is missing the necessary depth to deliver valuable business insight. As a process, that’s clearly the wrong way round.

It’s only once a business has confidence in its data quality that the time is right to move ahead with cloud-based analytics. Even then, the approach is not to throw analytics at the entire big data resource.

Companies will be successful only if they determine business objectives and then use analytics-as-a-service to quickly test hypotheses and deliver immediate business wins.

>See also: The sky’s not the limit: analytics in the cloud

Data can clearly drive business transformation but a new, bite-size attitude is required if organisations are to effectively embrace the potential of cloud-based analytics.

Cloud confidence

Why are organisations struggling to make the most of the cloud for analytics?

Certainly the increasing maturity of the cloud in recent years is a result of organisations’ confidence to migrate key business applications. But when it comes to big data, concerns persist.

Are cloud services as scalable as the vendors insist? Is it really possible to move vast quantities of data into the cloud – even with today’s huge bandwidth? And, critically, how can organisations retain control over the analytics process – from the tools used to analyse the data to the timing and visibility of the data from the analytics systems?

The financial model adopted by cloud providers means that while it is easy and relatively cheap to put data into the cloud, it is difficult and extremely expensive to get it out again.

What’s more, while many companies may have vast quantities of data – both structured and unstructured – there is no guarantee that data can actually deliver business value.

>See also: Cloud data management: data protection

Data collection, categorisation and storage processes are inherently complex, meaning organisations can spend thousands of pounds only to discover the data is simply not available to answer the key business questions.

A bite-size approach

The new realm of cloud analytics providers now offer the capability and technology to undertake the essential step of data discovery incredibly quickly. Within a matter of weeks, a cloud-based service can look at a company’s data to determine the business value, if any, and whether that data can be used to meet key objectives.

Once the data quality has been confirmed, organisations can then embark upon an analytics project to identify clear business outcomes. The power of this cloud service-based approach is that it enables businesses to try out analytics, both to gain confidence and to respond to a specific business objective.

A tactical, bite-size approach with a tangible business outcome based on real data not only delivers immediate value – and confidence – but also provides a platform for far broader analytics activity.


Companies need confidence in their data projects – but to build this, attitudes towards analytics must change. Organisations need a business case to drive their analytics activity, but this is simply unachievable if the initial data evaluation step has not been undertaken first.

Cloud services and Managed Service Providers must show they are actively providing analytics services on the data already held within their organisation, and provide access to affordable, effective data evaluation processes and options for quick, business-focused activity.

>See also: Why not all clouds are created equal

With the flexibility to promote a bite-size approach, an analytics-as-a-service model can eradicate all the issues currently acting as a barrier to the adoption of cloud-based analytics.

Only once an organisation has had the chance to exploit analytics in the cloud to meet its specific business objectives quickly and at a low cost, has it truly taken the first step towards data-driven innovation.


Sourced by Peter Ruffley, chairman, Zizo

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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...

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