Although big data analytics are now finding a place in businesses across all verticals, there remain a few key sectors where the technology has proven to be especially useful in tackling problems that have persisted for many years.

One example where big data analytics are making a difference is in the telecoms sector. In particular, these tools are being used to help reduce customer churn, which can be one of the most costly challenges for these companies.

In an interview with Tech Republic, co-founder and chief strategy officer at Cloudera Mike Olsen explained that telcos can expect to spend more than $300 on every new customer they acquire. Therefore, being able to improve their retention of existing customers even fractionally can have a major impact on a company's profitability.

In the past, one of the challenges with managing churn from a data point of view was the complexity of the landscape and the variety of information available.

"Here we're talking about all of the domains that cross user profile and usage data (account info, transactions, things like that), mobile and devices (GPS/location, set-top box logs), network logs, marketing, and CRM systems, and then data in the public domain," Mr Olsen explained.

Historically, all this information will have been carefully siloed, with telcos having a variety of disparate systems for running networks, customer support, marketing, billing and more. These will all have been spread out throughout the business and walled off, with no easy way to transfer data between them.

This often meant that it was hard to detect problems that may lead to customer churn until it was too late to do anything about it.

However, effective big data solutions can break down these barriers and make it easy to integrate data, so that businesses can build a complete picture of their customers, all in one location.

Mr Olsen observed that churn is typically the result of dissatisfied customers, so anything businesses can do to identify the root causes of this unhappiness will greatly help with retention. 

"What telcos want is to understand data across silos and to enrich it with external data, like social media," he said. "The objective is to understand customers' behavior and figure out what their experience is, without even talking to them."

To achieve this, companies in the telecommunications sector want to build predictive analytics solutions that create models of what their users are likely to do, based on the data available. Mr Olsen said: "We see this creating leading indicators of customer churn, which is really much more actionable data."

Looking forward, the expert predicted that finding affordable solutions for real-world business problems will be the driving force behind many big data deployments.

"Business users today need to attack important problems without hiring armies of data scientists or radically retooling their IT and analyst teams," he continued. "I think that the telco example is a great template of the kind of integrated solutions that large enterprises need."