Big data analytics is becoming more popular among companies that are keen to boost theirRead More
How can big data risks be minimized?
Big data analytics is becoming more popular among companies that are keen to boost their market agility and forward-thinking strategies. However, maintaining an ever-growing quantity of data to drive these processes can come with considerable risks.
An increasing number of businesses are reporting data-security breaches, with some of the world's biggest organizations falling victim to cyber criminal activity.
JPMorgan Chase, Ebay, Adobe and Target are just some of the household names that have announced the personal information of customers had fallen into the wrong hands in recent months.
Earlier this year, the UK's Department for Business Innovation and Skills released a report that showed 55 per cent of the country's large organizations experienced an unauthorized data attack in the last 12 months.
The 2014 Information Security Breaches Survey also revealed 16 per cent of companies were aware that intellectual property had been stolen from their network over the same time period.
Understanding the risks
One of the best ways to protect against big data security threats is to understand the risks and implement measures to reduce potential incidents.
Writing for CNBC, chief security officer at Trexin Consulting Glenn Kapetansky said companies will never be able to eradicate the dangers of a breach, but preparation can mitigate the chance of devastating outcomes.
He identified a number of key areas where businesses should concentrate in order to optimize big data processes:
Eliminate unneeded data: Many companies stockpile all of their data, but some of this can be jettisoned once the organization identifies which information is the most useful.
Holding onto unnecessary data increases risk, so businesses should isolate what is required to draw new insights and remove the rest.
Strengthen back-door security: Similar to home security, the back door of technology systems is rarely as well guarded as front access areas.
In businesses, this means locations where data is stored but is not part of a 'live' system. For example, information could be replicated in test environments or disaster recovery platforms, which are less likely to have comprehensive protection.
Utilize business acumen: Mr Kapetansky claimed senior managers do not need to be data scientists in order to make important big data decisions.
Choosing between a gold-plated security solution and one that covers the bases will largely come down to an organization's specific circumstances and risks. Business leaders should therefore approach the matter with the same rigor they would with any other strategic issue.
Recognize risks from every angle: Cyber criminals are becoming increasingly sophisticated with how they use business data for nefarious purposes.
"Just because it's your company's data, about your customers, you're not necessarily the expert on what inferences can be drawn from it and what crimes can be cooked up from it," Mr Kapetansky stated.
"Today's most advanced cyber criminals are looking not just for commodities like credit card information, but for high-value inferences or other intellectual property that they can use for more sophisticated purposes."
Ultimately, he urged companies to tackle big data analytics projects with a common-sense approach, addressing the largest risks first and whittling them down gradually.