Category: Big Data

The high cost of distrust

A lack of trust in data is going to cost the world’s economy over a trillion dollars forecast a Cisco panel

A lack of trust in technology’s security could be costing the global economy over a trillion dollars a panel at the Australian Cisco Live in Melbourne heard yesterday.

The panel “how do we create trust?” featured some of Cisco’s executives including John Stewart, the company’s Security and Trust lead, along with Mike Burgess, Telstra’s Chief Information Security Officer and Gary Blair, the CEO of the Australian Cyber Security Research Institute.

Blair sees trust in technology being split into two aspects; “do I as an individual trust an organisation to keep my data secure; safe from harm, safe from breaches and so forth?” He asks, “the second is will they be transparent in using my data and will I have control of my data.”

In turn Stewart sees security as being a big data problem rather than rules, patches and security software; “data driven security is the way forward.” He states, “we are constantly studying data to find out what our current risk profile is, what situations are we facing and what hacks we are facing.”

This was the thrust of last year’s Splunk conference where the CISO of NASDAQ, Mark Graff, described how data analytics were now the front line of information security as threats are so diverse and systems so complex that it’s necessary to watch for abnormal activity rather than try to build fortresses.

The stakes are high for both individual businesses and the economy as technology is now embedded in almost every activity.

“If you suddenly lack confidence in going to online sites, what would happen?” Asks Stewart. “You start using the phone, you go into the bank branch to check your account.”

“We have to get many of these things correct, because going backwards takes us to a place where we don’t know how to get back to.”

Gary Blair described how the Boston Consulting Group forecast digital economy would be worth between 1.5 and 2.5 trillion dollars across the G20 economies by 2016.

“The difference between the two numbers was trust. That’s how large a problem is in economic terms.”

As we move into the internet of things, that trust is going to extend to the integrity of the sensors telling us the state of our crops, transport and energy systems.

The stakes are only going to get higher and the issues more complex which in turn is going to demand well designed robust systems to retain the trust of businesses and users.

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Video and the internet of things

High resolution video coupled with the IoT are part of the Big Data explosion

A few days ago we discussed how 4k video cameras are going to change the sports broadcasting industry.

Yesterday executives from modular data center supplier VCE held a media lunch where they discussed some of their industrial applications. One of the areas they discussed was the monitoring of power stations with large resolution cameras.

The 4k cameras are trained on machine rooms with software watching for irregular conditions such as excessive vibrations, leaks or smoke. Should something out of the ordinary be detected, warnings can be triggered and potentially affected equipment spun down.

With the 4k resolution the cameras are able to watch large areas and like the sports coverage can zoom in for a detailed view of an affected area.

The use of 4k video cameras shows how the internet of things won’t just be about the data gathered from smart devices but also matching the information coming from IoT equipment with that of other environmental factors.

For companies like VCE these sort of applications are an opportunity as they need large amounts of data storage and processing power in local centres.

In many respects these small scale data centers are a large scale example of the fog computing being touted by companies like Cisco where most of the operational tasks are carried out by local equipment with only reports and exceptions being transmitted to the cloud.

This sort of application also shows the demands different industries are going to have for local data processing and storage with the VCE executives suggesting hospitals, mines and sports stadiums are also going to need these facilities.

For VCE – a troubled joint venture between Cisco, storage company EMC and computer virtualisation firm VM Ware – these are the sort of clients they are hoping to find to keep their business running.

Regardless of VCE’s prospects, the need for equipment to manage the data being collected by devices on the Internet of Things and 4k video is going to grow. That could give us one of the clues of where the jobs of the future are going to come from.

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Data driven lending

Square enters the small business lending space, will be they successful in a very competitive field?

Banking has always been a data driven business, understanding borrowers and the risks they present is one of the essential skills in making money from lending.

The new wave of payment startups present a new way for lenders to analyse risks; with real time data aggregated across businesses and regions, lenders can quickly decide wether a borrower is likely to able to pay the money back with the conditions asked for.

Payments company Square in its latest pivot has partnered with Victory Park Capital and claims to have extended more than $100 million in capital to more than 20,000 merchants writes the New York Times.

Like other payment companies that have entered this market, Square uses their own deep understanding of their customers’ incomes to be able to make a data based decision on the creditworthiness of applicants.

Square also offers ancillary data-driven products created for small businesses. The new instant deposit product, which is still in testing and will be fully available in the spring, will give businesses faster access to money they put into a debit account. And the company’s new charge-back protection service will cover some disputes between consumers and merchants.

Those products also rely on data that Square has collected. They will be available only to small businesses that have a solid financial track record, based on a history of accepting payments with Square.

Square is by no means the first business to do this, last year we wrote of PayPal’s move into small business lending and Point of Sale hardware manufacturer Verifone retreated from the market two years ago calling it ‘fundamentally unprofitable.’

The competition in the space and the fact assessing financial risks isn’t exactly a core competence of Silicon Valley start ups indicate Square’s and other companies may find small business lending a tough business as well.

Despite that, small business lending is a field that is overdue for disruption. With companies like Apple, Google and Amazon all offering payment services, the logical expansion is into evaluating risk and profit.

It may not be Square, Verifone or PayPal who ultimately redefines the sector, but it will be one of today’s tech businesses that does.

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Clawing back our data – Telstra makes metadata available to customers

Australia’s Telstra responds to government data legislation by opening metadata to users

Today Australian incumbent telco announced a scheme to give customers access to their personal metadata being stored by the company.

In a post on the company’s Telstra Exchange blog the company’s Chief Risk Officer, Kate Hughes described how the service will work with a standard enquiry being free through the web portal with more complex queries attracting of fee of $25 or more.

The program is a response to the Australian Parliament’s controversial intention to introduce a mandatory data retention regime which will force telcos and ISPs to retain a record of customer’s connection information.

We believe that if the police can ask for information relating to you, you should be able to as well.

At present the scheme is quite labor intensive, a request for information involves a great deal of manual processing under the company’s current systems however Hughes is optimistic they will be able to deal with the workload.

“We haven’t yet built the system that will enable us to quickly get that data,” Hughes told this website in an interview after the announcement. “If you came to us today and asked for that dataset it wouldn’t be a simple request.”

The metadata opportunity

In some respects the metadata proposal is an opportunity for the company to comply with the requirement of the Australian Privacy Principles that were introduced last year where companies are obliged to disclose to their customers any personally identifiable information they hold.

For large organisations like Telstra this presents a problem as it’s difficult to know exactly what information every arm of the business has been collecting. Putting the data into a centralised web portal makes it easier to manage the requirements of various acts.

That Telstra is struggling with this task illustrates the problems the data retention proposals present to smaller companies with far fewer resources to gather, store and manage the information.

Unclear requirements

Another problem facing Hughes, Telstra and the entire Australian communications industry is no-one is quite clear exactly what data will be required under the act, the legislation proposed the minister can declare what information should be retained while the industry believes this should be hard coded into the act which will make it harder for governments to expand their powers.

What is clear is that regardless of what’s passed into law, technology is going to stay ahead of the legislators, “I do think though this will be very much a ‘point in time’ debate,” Hughes said. “Metadata will evolve more quickly than this legislation can probably keep pace with so I think we will find ourselves back here in two years.”

In many ways Australia’s metadata proposals illustrates the problems facing governments and businesses in managing data during an era where its growing exponentially, it may well turn out for telcos, consumers and government agencies that ultimately less is more.

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Reducing big data risks by collecting less

Just because you can collect data doesn’t mean you should

“To my knowledge we have had no data breaches,” stated Tim Morris at the Tech Leaders conference in the Blue Mountains west of Sydney on Sunday.

Morris, the Australian Federal Police force’s Assistant Commissioner for High Tech Crime Operations, was explaining the controversial data retention bill currently before the nation’s Parliament which will require telecommunications companies to keep customers’  connection details – considered to be ‘metadata’ – for two years.

The bill is fiercely opposed by Australia’s tech community, including this writer, as it’s an expensive   and unnecessary invasion of privacy that will do little to protect the community but expose ordinary citizens to a wide range of risks.

One of those risks is that of the data stores being hacked, a threat that Morris downplayed with some qualifications.

As we’re seeing in the Snowden revelations, there are few organisations that are secure against determined criminals and the Australian Federal Police are no exception.

For all organisations, not just government agencies, the question about data should be ‘do we need this?’

In a time of ‘Big Data’ where it’s possible to collect and store massive amounts of information, it’s tempting to become a data hoarder which exposes managers to various risks, not the least that of it being stolen my hackers. It may well be that reducing those risks simply means collecting less data.

Certainly in Australia, the data retention act will only create more headaches and risks while doing little to help public safety agencies to do their job. Just because you can collect data doesn’t mean you should.

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Reading the golden records – can we avoid a digital dark age?

Changing computer formats mean we risk a ‘digital dark ages’ industry experts warn.

In 1977 NASA’s Voyager mission launched from Cape Canaveral to explore the outer solar system, included on the vessel in case it encountered other civilisations were a plaque and a golden record describing life on Earth.

The record was, is, “a 12-inch gold-plated copper disk containing sounds and images selected to portray the diversity of life and culture on Earth.” It containing images,  a variety of natural sounds, musical selections from different cultures and spoken greetings in fifty-five languages.

Most American households in 1977 could have listened to the sounds on Voyager’s golden disk but were the spaceship to return today it would be difficult to find the technology to read the record.

This is the concern of Google Fellow and internet pioneer Vint Cerf who told the American Association for the Advancement of Science’s annual meeting in San Jose this week we are “facing a forgotten century” as today’s technologies are superseded rendering documents unreadable.

A good example of ‘bit rot’ is the floppy disk – the icon used by most programs to illustrate saving files is long redundant and few organisations, let alone households, have the ability to read a floppy disk.

For corporations the problem of dealing with data stored on tape is an even greater problem as proprietary hardware and software from long vanished corporations becomes harder to find or engineer.

As the Internet of Things rolls out and data becomes more critical to business operations, the need for compatible and readable formats will become even more important for companies and historical information may well become a valuable asset.

With libraries, museums and government archives having digitised historic information, this issue of accessing data in superseded formats becomes even more pressing.

It may be that important documents need to be kept on paper – although there’s still the problem of paper deteriorating  – to make sure the 21st Century doesn’t become the digital dark ages and our golden records remain unread.

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At the mercy of machines

Automation and algorithms are changing business but they are not without risks

Automation is the greatest change we’re going to see in business over the next decade as companies increasingly rely upon computers to make day to day decisions.

Giving control to algorithms however comes with a set of risks which managers and business owners have to prepare for.

Earlier this week the risks in relying on algorithms were shown when car service Uber’s management was slow to react to a situation where its formulas risked a PR disaster.

Uber’s misstep in Sydney shows the weaknesses in the automated business model as its algorithm detected people clamouring for rides out of the city and applied ‘surge pricing’.

Surge pricing is applied when Uber’s system sees high demand – typically around events like New Year’s Eve – although the company has previously been criticised for alleged profiteering during emergencies like Hurricane Sandy in New York.

In the light of previous criticism, it’s surprising that Uber stumbled in Sydney during the hostage crisis. Shortly after criticism of the surge pricing arose on the internet, the company’s Sydney social media manager sent out a standard defence of surge pricing.

That message was consistent with both Uber’s business model and how the algorithm that determines the company’s fares works; however it was a potential disaster for the business’ already battered reputation.

An hour later the company’s management had realised their mistake and announced that rides out of Sydney’s Central Business District would be free.

User’s mistake is a classic example of the dangers of relying solely on an algorithm to determine business decisions; while things will work fine during the normal course of business, there will always be edge cases that create perverse results.

While machines are efficient; they lack context, judgement and compassion which exposes those who rely solely upon them to unforeseen risks.

As the Internet of Things rolls out, systems will be deployed where responses will be based upon the rules of predetermined formulas.

Businesses with overly strict rules and no provision for management intervention in extreme circumstances will find themselves, like Uber, at the mercy of their machines. Staking everything on those machines could turn out to be the riskiest strategy of all.

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