Meeting the key big data security challenges

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2016
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As more businesses embrace big data analytics solutions, the amount of information held in databases all around the world is growing at an extremely fast rate. However, while this presents many new opportunities to gain insights, it also creates challenges.

One of the biggest issues is security. These applications present a tempting target for criminals as data volumes rise, offering them personal and financial details that can be used for fraud.

In previous years, internal applications that make use of this data have been regarded as low risk. However, it was noted by Data Center Knowledge that as adoption of web, mobile and cloud-based applications increases, sensitive data becomes accessible via more platforms, some of which are particularly vulnerable to hackers.

"The more data is stored, the more vital it is to ensure its security," stated contributor Aleksandr Panchenko, head of A1QA's complex web QA department. "A lack of data security can lead to great financial losses and reputational damage for a company. As far as big data is concerned, losses due to poor IT security can exceed even the worst expectations."

There are a range of particular challenges when it comes to big data security that were identified by Mr Panchenko. For example, he noted that the pace of change of the sector creates difficulties.

Because tools such as NoSQL databases are constantly evolving, it is very difficult for security solutions to keep up with demand. Most distributed systems' computations also have only a single level of protection, which is not recommended.

The sheer scale of the data involved also poses challenges. For instance, validation processes to ensure incoming data is trustworthy are often not performed, while detailed audits are not routinely performed on big data due to the huge amount of information involved.

Meanwhile, some companies are unwilling or unable to institute access controls to ensure only approved personnel have access to applications. And even among those businesses that do put solutions in place, access control encryption and connections security can quickly become dated and inaccessible to the IT specialists who rely on it.

To overcome these obstacles and ensure that big data analytics applications are as secure as possible, Mr Panchenko offered several recommendations. For starters, he advised companies to focus on applications security as opposed to device security, as well as isolate servers that contain critical data,

Companies should also look to implement real-time security information and event management solutions that can give early warnings of any unusual behaviour that may be an indicator of a data breach. Being able to react quickly to any alerts could make the difference between a successful defence or sensitive data being compromised.

"Malicious attacks on IT systems are becoming more complex and new malware is constantly being developed," Mr Panchenko said. "Unfortunately, companies that work with big data face these issues on a daily basis. Nevertheless, every problem has a solution and finding an effective and suitable answer for your organisation is indeed possible."

How can retailers avoid key big data mistakes?

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Jan
2016
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How can retailers avoid key big data mistakes?
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While big data has been making its presence felt across many sectors in the last couple of years, one area where it has great potential is in the retail space. With these businesses able to gather a large amount of information on their customers, such as their buying preferences, they can use this to ensure they are offering the products their customers want, at the most competitive prices.

However, there are several pitfalls that retailers need to avoid if they are to make big data analytics a success. In a recent piece for Internet Retailing, vice-president of EMEA sales at point-of-sale software supplier Vend John Coulston said it is easy to make simple errors that can lead to important information being ignored, or customer trust being lost.

Among the most common problems is ignoring the data that retailers already have. Many companies promote loyalty schemes that can be a great source of data on their customers' activities, yet do not make the most of it.

"Data should be collected with the chief intention of benefiting the customer – which in turn will benefit your business," Mr Coulston said. "For example, high street bakery Greggs does this well through its loyalty scheme, which collects customer data and then provides instant, targeted offers and rewards to shoppers through their mobile phones."

Retailers also need to ensure their employees are able to tap into these resources. This means not only training them on how to use big data analytics software, but educating them on what they can do to turn this insight into action.

For instance, Mr Coulston stated that training staff members in all areas to spot trends, such as what items are popular and often sold together, and empowering employees to look deeper at customer data can help create a more personal experience for shoppers. So if a regular customer walks into a shore, associates should be trained to check that customer’s purchase history or loyalty status so they can interact with them in the most relevant way.

Keeping this human touch will be vital if analytics programmes are to be a success. While technology can provide a wealth of information on individual customers, it shouldn't be used to replace the specialised knowledge and skills of retailers' best staff.

"Your analytics software may be able to tell you what’s selling and what’s not, but gathering insights first-hand about how your customers feel about your merchandise can only be done through qualitative data-gathering and communicating with shoppers," Mr Coulston said.

He also emphasised the importance of ensuring businesses are ethical in how they use data. "Getting customers to trust you with their information – from email addresses and birthdays, to purchase histories – is a significant responsibility, so be careful with it," the columnist said. "The last thing your business wants is to come off as untrustworthy, or have to deal with stolen data."

EU set to analyse big data use in mergers

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Jan
2016
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EU set to analyse big data use in mergers
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The European Union (EU) is planning to take a more detailed look at whether the large amounts of consumer data carried by large internet companies violates competition rules as part of its analysis of proposed mergers.

After taking over as Europe's leading antitrust enforcer in 2014, Margrethe Vestager has enhanced the investigations into US web giants including Google and Amazon in order to determine whether this information should be regulated more strictly.

Ms Vestager noted that protecting consumer privacy transcends her agency's remit, adding that the power large internet companies wield should not make it too challenging for other companies to compete.

This move comes after the European Commission suggested that Google favoured its own shopping services in search results ahead of rivals and is considering potential sanctions against the search engine.

Speaking to a conference of top European and US entrepreneurs and investors, Ms Vestager explained: "If just a few companies control the data you need to satisfy customers and cut costs, then you can give them the power to just drive rivals out of the market.

"If we analyse a merger, if we have a suspicion or concern when it comes to antitrust, if it comes to data, of course we will look at it. If a company's use of data is so bad for competition that it outweighs the benefit, then you may have to step in to restore the level playing field."

Ms Vestager embraced efforts by businesses to develop standards for internet data protection and emphasised the advantages noticed in businesses analysing big data to identify consumer demand to offer personalised shopping and organise better transportation.

She noted that the EU is planning to publish a wide-ranging policy paper on online services by the middle of the year.

Large companies increasingly turning to big data tools

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Jan
2016
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Large companies increasingly turning to big data tools
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The popularity of big data analytics continued to grow last year, with more large companies adopting the technology to assist with the decision making

According to a NewVantage study, 65 per cent of Fortune 1000 firms report that they now have at least one example of Big Data in production, almost double the 31.4 per cent recorded in 2013. Some 26.8 per cent of companies stated that they will invest more than $50 million in Big Data by 2017, marking a significant rise from the 5.4 per cent recorded in 2014.

The chief data officer position has also become more established, with 54 per cent of companies now having one on their team. Some 20 per cent of companies also reported that the chief data officer is the executive with primary ownership responsibility for big data.

Some 33.9 per cent of companies said that business and technology cooperation was the most critical factor in business adoption, putting it ahead of all other factors by a wide margin.

Strong business sponsorship was viewed as the most critical factor by 23.2 per cent of companies, while technology leadership (5.4 per cent) and technology selection (0 per cent) were viewed less favourably.

The study found that business insights and speed are the key drivers of big data investment, with businesses now citing the ability to develop better insights into their business and customers (37 per cent) as the largest driver of Big Data investment,

Second in this list is the advantages gained from faster speeds, including faster-time-to-answer, faster-time-to-decision and faster speed-to-market (29.7 per cent). Companies also require greater analytics capabilities (9.3 per cent) and the chance to develop a data-driven culture.

With more information now available for businesses, it is vital that specialists protect their data and make sure workers are aware of how to use it properly, or they could leave themselves vulnerable to cyber criminals. 

Can the insurance sector get consumers on board with data gathering?

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Jan
2016
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Can the insurance sector get consumers on board with data gathering?
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Over the last few years, many businesses have been tempted by the idea of using big data to gain a much more detailed picture of their customers, which they can in turn use to provide more personalised offers and even discounts.

But the catch with this is that in many cases, consumers will be wary of technology solutions that delve deep into their personal information. In some situations, they will need to give their express permission for a company to collect and use their data – and this can prove tricky to obtain, despite the benefits on offer.

This is a problem currently being experienced by the car insurance sector. It was noted by the Wall Street Journal that the advent of big data analytics, combined with Internet of Things technology, has provided great opportunities for the sector. 

Whereas in the past, insurers had to rely on broad categories such as age, occupation and car type to determine risk levels, by using sensors in their customers' vehicles, they can track behaviour much more accurately to deliver personalised quotes. 

For instance, among the metrics tracked by US insurer Allstate is hard braking – defined by the company as a speed reduction of more than eight miles per hour in less than one second. Analysis of this data reveals that drivers who do this more than eight times for every 500 miles driven are 73 per cent more likely to be involved in an accident in any given year.

However, despite the impact this may have on premiums – with large discounts on offer for the safest drivers – consumer trust in the technology remains low.

According to US insurer Progressive, almost 80 per cent of its customers would qualify for a discount through the use of driver trackers and big data analytics, with savings of up to 30 per cent available.

But just a quarter of the company's new customers use the technology, while a survey by the company found around 40 per cent of people stated they would never consent to the use of such sensors.

Chief executive of Progressive Glenn Renwick noted this is a challenge that's particularly prevalent in his industry. "Insurance is not something where people say, 'I trust you,'" he said.

Therefore, companies in the sector are having to create even more incentives in order to persuade people to use the technology. Allstate, for example, offers drivers the chance to earn points through safe-driving challenges, such as driving below 80 miles an hour and avoiding hard braking for three straight days, which can be redeemed for  deals on merchandise, gift cards and local offers.

In years to come however, some experts are predicting that resistance to the use of data-gathering for use in analytics-based businesses will fade. Paul Saffo, a Stanford University professor and specialist in technological change, told the Journal that  usage-based pricing will be inevitable for the insurance sector in the long term.

He added that in the US at least, consumers have already shown increasing willingness in recent decades to sacrifice privacy for convenience, and they will continue to do so – even as they complain about the technology.

What will the big data challenges for 2016 be?

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Jan
2016
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What will the big data challenges for 2016 be?
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Big data is in a state of constant evolution, with new technologies and software regularly emerging in the field.

There are increasing numbers of companies that are turning to big data in order to control the vast amounts of information controlled on a variety of devices, ranging from laptops and tablets to mobile phones and even smartwatches.

It was noted by Information Age that the result of this is that big data can no longer be considered a passing trend. Enterprises need to accept that the technology is here to stay – as when internal communications, cloud computing and social media interactions are considered, organisations are having to handle more information than ever before.

With so much data now readily available to companies, organising it is harder than ever before. Information Age noted  it is increasingly challenging to put big data into a unified format, especially when it comes to governing information and making sure it does not fall into the wrong hands.

As well as this, big data remains a relatively new technology and companies that have just begun using it will be more likely to encounter difficulties. Accessing logs and audit trails could also be challenging for businesses that are looking to check harder-to-reach information.

Big data has become such a phenomenon in the IT industry that likely that some companies will feel they have to investigate the technology, even though it may not necessarily be suited to them.

Prior to investing any time or money into big data, companies should fully consider what they are hoping to get out of big data. It may be that workers need to complete more training on data mining and machine learning, or they could struggle to interpret data properly.

FTC warns against big data ‘discrimination’

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Jan
2016
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FTC warns against big data 'discrimination'
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The US Federal Trade Commission (FTC) has released a new report advising businesses what considerations they need to take into account when working with big data, with the regulator particularly urging firms to avoid strategies that produce exclusionary or discriminatory outcomes.

In the document released last week (January 6th), the body looked specifically at the end of the big data lifecycle – how information is used after it has been collected and analysed. It noted that while the technology has a wide range of benefits, it can also lead to reduced opportunities for certain groups and the targeting of vulnerable consumers for fraud and higher prices.

FTC chairwoman Edith Ramirez said: "Big data's role is growing in nearly every area of business, affecting millions of consumers in concrete ways. The potential benefits to consumers are significant, but businesses must ensure that their big data use does not lead to harmful exclusion or discrimination."

The report observed that positive outcomes of big data are not only limited to improved results at enterprises. There are also a number of wider societal benefits that can be seen, such as improved healthcare, education and equality. 

For example, Google is among a number of businesses that are deploying big data solutions as part of their hiring processes, in order to create a more diverse workforce. "Through analytics, Google identified issues with its hiring process, which included an emphasis on academic grade point averages and 'brainteaser' questions during interviews," the report said. 

"Google then modified its interview practices and began asking more structured behavioural questions (e.g., how would you handle the following situation?). This new approach helped ensure that potential interviewer biases had less effect on hiring decisions."

However, while big data can be used to eliminate many personal biases from business' decision-making, the technology could introduce new types of discrimination that could affect opportunities for citizens if used incorrectly.

One example highlighted by the FTC's report is incidents where credit card providers have lowered certain customers' credit limits based not on their own payment history, but analysis of other consumers with a poor repayment history.

In one case, a provider settled with the FTC after it was alleged to have failed to disclose that it identified some customers as having a higher credit risk if they used their cards to pay for  marriage counseling, therapy, or tyre repair services, based on its experiences with other consumers and their repayment histories.

"Using this type of a statistical model might reduce the cost of credit for some individuals, but may also result in some creditworthy consumers being denied or charged more for credit than they might otherwise have been charged," the FTC said.

Other potential issues for big data included its ability to expose sensitive information. The FTC highlighted one study that combined data from Facebook 'Likes' and limited survey information, which was able to predict a user's ethnic origin with 95 per cent accuracy and male users' sexual orientation 88 per cent of the time.

The report offered several recommendations to ensure that the use of big data does not lead to discrimination. These include reviewing data sets and algorithms to ensure that hidden biases are not having an unintended impact on certain populations.

"Remember that just because big data found a correlation, it does not necessarily mean that the correlation is meaningful," it concluded. "As such, you should balance the risks of using those results, especially where your policies could negatively affect certain populations."

European businesses ‘lose £20m a year” through poor data management

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Dec
2015
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European businesses 'lose £20m a year" through poor data management
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Businesses in Europe could be missing out on sales worth up to £20 million a year because they do not have the ability to take full advantage of the data they collect.

This is according to research conducted by flash storage provider Pure Storage, which claimed more than half of companies (51 per cent) have missed out on an opportunity because they were not aware of it until it was too late.

Almost a third of respondents (31 per cent) stated they had experienced this at least once a year, while 19 per cent see such an occurrence multiple times a week. 

In many cases, businesses had access to the right data that would have given them an insight into the opportunity, but were unable process it in time to take advantage.

Vice-president for Europe, the Middle East and Africa at Pure Storage James Petter commented: "The reason we're seeing these trends emerge is because it is now cheaper for businesses to retain the data they are collecting than to destroy it, so the volume of data a business holds is growing rapidly."

At the same time, he added it is becoming increasingly complicated and costly to access usable information fast enough to make a difference.

Nearly three-quarters of businesses (72 per cent) said they collect information that is never used, with almost half of these firms (48 per cent) putting this down to the fact that data processing is too time consuming. One in five also highlighted the expense of these activities as a challenge.

However, as the amount of information available grows, companies that are better able to process this and turn it into usable information that can influence decision-making will be in a much better position that those without these capabilities. This will be particularly true as in many cases, competitors will all have access to the same raw data from publicly-available sources.

Mr Petter said: "As companies gather more and more granular data on what they do, the potential to gain understanding and plan accordingly is not just a profitable undertaking, it is a necessity. Transformation is being forced on organisations at an ever-increasing pace. They must adapt to new ways of doing business, new markets and new practice, or die."

Among the concerns raised by businesses when it comes to making the most of their data is the regulatory burden placed upon them. Overall, one in ten respondents said their data processing efforts are held back by data protection worries.

Organisations in the UK were found to be particularly affected by such issues. Some 39 per cent of respondents in the country agreed that well-meaning regulations often have unforeseen negative consequences for their business.

However, this was not a view reflected elsewhere in Europe. In France, for example, 42 per cent of respondents stated data protection rules have actually helped their ability to do business, while German firms were also positive. 

Some 40 per cent of businesses in the country stated that there were no new regulations in their industry that affected their performance, and over a quarter (26 per cent) said that regulations aimed at a different industry had a positive impact on their activities.

What do CIOs want from big data in 2016?

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Dec
2015
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What do CIOs want from big data in 2016?
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With the new year almost upon us, many experts have been offering their thoughts on what the big data market will hold in 2016. And while top tips for the technology include greater use of developments such as the Internet of Things and machine learning, will these be the innovations that the people actually using the tools want to see?

CBR noted that for many chief information officers (CIOs), the main thing they will be hoping to get out of the next 12 months will be clarity. this includes better messaging about the technology itself, and clearer information on issues such as privacy and data sharing.

Top of the wish list for Hortonworks founder Arun Murthy will be an end to the hype and overuse of buzzwords that has defined much of the big data sector in previous years. He told the publication: "I just wish the term went away and [we can] just call it data and be done with it."

CBR noted that this is indicative of a growing feeling that simply referring to 'big data' is too broad, particularly now that the initial hype stage is coming to an end and businesses are starting to ask more about what they can actually do with the technology in order to drive real-world value from their applications. 

Improved standardisation and clearer guidelines from regulators about how large volumes of sensitive data need to be protected will also be highly important to CIOs in 2016, as more production deployments of such solutions go live.

CBR stated that the EU, for instance, should be creating a set of laws that make it clear exactly how data can legally be shared across the continent. There have been steps taken towards this recently, with a draft text of the upcoming European General Data Protection Regulation agreed upon by MEPs earlier this month.

However, the publication observed that one of the biggest problems with previous pan-European data protection laws is that they have been constantly updated and revised, while individual member states have often interpreted EU directives differently. This has caused a great deal of stress for CIOs as they struggle to keep up. 

A more consistent set of rules that do not change from country to country will give CIOs much greater peace of mind as they go about building systems for the collection, storage and processing of large volumes of data in 2016, CBR continued.

Efforts to develop universal processes for data collecting and ensure that all applications are able to integrate with each other more easily will also assist with this.

CBR said: "Platform providers have taken steps in standardising and making it easy to connect different data sources, but plenty more can be done."

Among the other CIO big data wishes that the publication highlighted for 2016 was the implementation of more focused data collection policies that offer more detail about the type of information organisations need to collect. The ability to make migrating data between different parts of a network easier was also named as a priority for the year ahead.

Big data investments ‘to double’ by 2021

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Dec
2015
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Big data investments 'to double' by 2021
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Global investment in big data analytics technology is set to double between 2015 and 2021, with innovations such as the Internet of Things driving business interest in the technology.

This is according to a report from Strategy Analytics, which estimated that global revenues from big data analytics solutions will reach $73.77 billion by 2021, up from £36.2 billion in 2015. By 2022, the market will have reached $80 billion, for a compound annual growth rate of 12 per cent over the next seven years.

Key sectors for the technology include the healthcare, financial services, industrial and manufacturing markets. Companies in these markets will particularly benefit from solutions that can interpret the vast amounts of data they generate, allowing them to respond to evolving market dynamics in ways that benefit them and their customers.

Andrew Brown, executive director of the Enterprise and IoT Research team at Strategy Analytics, said that big data analytics will make the difference between reactive and proactive businesses.

He added: "Predictive analytics software can help businesses respond in a proactive way by dealing with issues before they occur. Prescriptive analytics on data sources can suggest decision options that take advantage of the predictive elements and provide real differentiation and competitive advantage for companies leveraging these technologies."

The report also noted that many investments in big data analytics technology will go towards open-source tools. As well as being less expensive than proprietary alternatives, these solutions will also have the advantage of being able to run on commodity hardware, which OEM vendors are hoping will help broaden the technology's appeal to small and medium-sized enterprises.

The healthcare vertical segment will remain the largest market for big data analytics solutions, with this set to grow from $7.96 billion in software revenue in 2015 to $17.03 billion in 2022. This will be followed by the financial services market, which Strategy Analytics forecast is set to double in size by 2022.

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