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Data is now the most important resource.


The first transatlantic data transfer happened over 150 years ago, and since then, it has become the most valuable resource in the world. More money is involved in the multinational transfer of data that the cross border delivery of physical goods.

And as data becomes more important, the acquisition, control and manipulation of it are vital in determining the success or failure of businesses. However, because it is so vital, large companies have been frequently accused of being careless with the mountains of data at their disposal, as well as lobbying for looser and looser restrictions on the regulations surrounding data flow. This may be a concern for some, especially at a time where concerns about privacy are very high.

Data acquisition in itself is not sufficient, what is done with that data is crucial.

Companies in America have been switched on to this trend for a while, but for those outside the US, it has taken some time to get onboard. And the reason it is so important is because so much data is no longer just personal. Financial, industrial and commercial data is vital in terms of many profit making activities. The concern is that, as we see in China, the regulation of data can be used as a tool to aid a ruling regime, and thus people are understandably worried about how theirs is used, and who has control.

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How new data protection laws are impacting businesses across the globe.


Thanks to a new piece of European law, EU citizens will, in 2018, have more control than ever when it comes to how their data is stored and used. The new legislation, known as the General Data Protection Act, will be the biggest legal overhaul in the data gathering sphere for 20 years. The new rules allow customers to more easily remove their data from databases, as well as provide their data to competitor services with greater ease, and require companies to provide a notification to customers within three days if there is a hack.

Any country that has companies that may wish to trade with the EU must comply or face a fine of 20 million euros, or 4% of total global income, depending on which is more. GDPR affects any company that processes data in Europe. So, if an customer of an American Mobile company visits the UK, and that company monitors, or acquires any data, then they are governed by GDPR.

Given that for many, losing out on billions worth of trade with the largest trading bloc in the world is unthinkable, EU citizens will soon find themselves with more control over their data than ever before and companies having to be more and more careful with what to do with the data they acquire.

A lot of data acquisition deals with technical information, monitoring of systems. Where that data can be directly, or indirectly related to an individual, then it potentially becomes problomatic. Imagine a situation where a device is measuring the brake performance on a test vehicle – where the data is collected and processed, alongside the details of the driver, or tester – then that data could be covered by GDPR, and organisations collecting or processing it could face huge fines if they don’t process it properly.

Now for some countries like Japan, Israel and New Zealand, who already have data privacy standards judged to be on par with Europe, then the transition process that businesses must undertake will be a reasonably smooth one. But for emerging markets, the high cost involved with administering the changes may result in them being left out in the cold.

Europe has been at the forefront of data privacy laws for a while now, but with the vast swathes of data American companies like Amazon and Facebook can collect, EU lawmakers are creating new legislation to increase protection.

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Make the most of your data to improve the customer experience


In today’s connected world, data is becoming incredibly valuable. The key is to take mountains of information, and turn that into a tailored, customer centric experience that will continue to bring in new clients. Generally, the customer need to be purchasing an outcome, rather than a product, and having excellent customer service is the way to get there.

In an increasingly commoditised market, great customer service really should be at the centre of a business because after all, customers are what keeps businesses running. At each point of contact, you need to tap in to your customers emotions, and the correct interpretation of data is the way to do it. Now this is a step above simply having good service. To do this the entire business model needs to be built with the analysis of big data in mind, so that a tight relationship between you and your customers develops.

Authenticity is also key to creating a successful customer experience, and being able to analyse data, and therefore customer needs and desires in real time is a great way to go about achieving it. The combination of data with machine learning technology and AI allows for the customer to be well and truly at the centre of the business model. Doing this will not only benefit your clients, but drive the financial success of your business. And in today’s technological climate, there are more ways than ever before to go about collecting the data. Customers give it away on a whole host of different platforms and in varied formats, which is why the incorporation of technology is vital to make data analysis more feasible.

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The dilemmas of data gathering


The rise of virtual assistants, amongst other gadgets, undoubtedly has the potential to make our daily lives better and easier. But after the initial excitement, some doubts have slowly arisen about the technology, especially when it comes to data gathering.

The ability to gather vast swathes of data has its benefits, but also raises questions about our right to privacy. Slowly, laws are being put into place that will provide us with more control over our own data.

There are three specific ethical concerns that arise over big data. One is, how far can one go when it comes to buying data? One example is companies that allow you to install trackers on your car, so that safer drivers pay less insurance. On the one hand this seems very fair, but on the flipside, it could mean that people who cannot afford the premiums are compelled to give up their data because they have no other way to pay the insurance.

Another problem comes from the fact that a more transparent view of everyone’s specific data could lead to a situation where customers who understand an offer less well are exploited and charged more.

The third problem is how acceptable it is to use big data to actively influence and shape peoples buying habits. We regularly see advertisements that have been tailored or influenced by our buying history, and with more and more data, these adverts become more and more specific. Another example could be online video services such as Amazon or Netflix suggesting new TV shows or movies based on our viewing history.

Market forces may not allow for companies to even have this debate about the ethics of big data. Most now require some way to analyse big data to keep up, and businesses without such technology may find themselves losing out. If some regulation isn’t implemented, we may find ourselves in an undesirable situation where discussion of these dilemmas in a luxury only afforded to the very richest companies, and everyone else simply has no choice but to use big data in an unethical way.

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Big Data and the future of agriculture



A staggering one third of all produce that comes out of farms per year is wasted. And whilst the misconception is that this is down to consumers throwing it away, this couldn’t be further from the truth. Since farming began, it has been plagued with problems ranging from the wrong amount of fertiliser, to pests and adverse weather conditions. Big data, and careful analysis of it, could be the solution we need.

Sensors in the field can alert the farmers as to when the opportune moment to harvest is, tell them if more or less fertiliser is required. Drones can be used to keep track of pest populations, as well as any other potential problems. Using agricultural data can allow farmers to streamline their business plan, and invest in the plants which are best in terms of profitability and sustainability.

And it isn’t only the farmers who benefit. Household sensors can warn consumers when food hygiene standards are slipping, and when the food has gone off. This will hopefully lower the 8 million working days that are lost to food poisoning every year.

It is vital that both producers and consumers understand how this data is collected and how it is used. Sectors are getting smarter and more interconnected all the time, and it is only natural that our analysis and collection methods must adapt to survive. This is a burden all industries must bear, but the reward will be worth it in the end.

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Is implementing big data in healthcare worth the privacy risk?



There is a strong and convincing case to fully implement big data analysis into the healthcare profession. Departments that are able to communicate with each other are often better able to help their patients. In short, more interconnectivity often equates to a more efficient healthcare system. It won’t be long before various different companies have mapped far more genomes that they currently have. There will be a huge database of patient’s clinical and genetic data. This should help doctors diagnose and treat diseases, such as cystic fibrosis, and heart conditions.

But often, the privacy issue is one that is overlooked. In the quest to streamline the whole process, the advent of big data analysis has thrown up some interesting questions about just how private our medical information really is. The worry is that what was once sacrosanct private medical information becomes a commodity traded freely between the healthcare industry and large corporations. The NHS has been reprimanded for illegally handing patient information to Google, and with massive fines available to any company that breaches regulations, as we move forward into the age of big data analysis, privacy issues will be at the forefront of general consciousness.

Companies that manufacture drugs in the UK have been fervent advocates of the possibilities that big data provides. They claim that through proper analysis, the mountains of information available to the healthcare industry and not only improve overall patient health, but save the NHS money in the process.

The possibilities if the healthcare industry successfully integrates big data into their business model are obvious. But as are the potential risks. With stringent regulation, the lives of could be made a lot better, their treatment could be more effective, and save money. But without such regulations, the risk that certain private information could be distributed to data banks like Google is going to provide a stumbling block.



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Large and small-scale uses of data collection in cities

city-dataData collection on a large scale in developing, and its use in cities is increasing drastically. An American company is now providing businesses and cities with detailed, real-time data that aims to help cities get deeper insight into the patterns of stationary and moving objects, for both indoor and outdoor environments.

The way this works is through the utilisation of a supercomputer that runs advanced neural networks, with an extensive range of wireless radios and a HD stereo camera. Through this, near-instantaneous scene analysis can display critical event notifications in real-time.

This company can, however, ensure customer privacy, as video data streaming never happens outside the sensor itself – the video is analysed on-site and immediately removed from the embedded system. After this, the scene can be described but can never be reconstructed, as to guarantee the safety of the privacy of the public.

This data collection can perform a variety of tasks, as large scale as estimating traffic flow and patterns, and performing detailed and accurate pedestrian and object counts. The technology can monitor the precise trajectory of objects either moving or stationary, whatever speed. This can be used as self-contained analysis, such as in shops, or combined to create a citywide field of view.

In terms of small scale use, this product can be invaluable in shops, monitoring how long a customer dwells on an object, and whether they proceed to buy the object or not. It also monitors how many people come and go from the shop, and whether they enter after spotting something of interest in the window.

Other small scale uses of this are at car parks, where the number and location of parking spaces can be monitored and displayed, perfect for optimising parking utilisation. This type of monitoring, along with monitoring the number of people waiting at bus stops, can be a step on the road to creating true smart city application.

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Big Data could help save lives

medical-dataBig data is viewed by most of the public with immense caution and fear, conjuring images of Big Brother watching your every move in an Orwell-esque nightmare. We are well versed in films, books and tv shows which display thought-police controlling us and robots enforcing the law of a tyrannical government. However, in reality, Big Data saves lives, and is making a better world for the future. The only problem is that restrictions in the availability of data, in particular medical research, are really delaying the development of Big Data.

One of the biggest problems here is that data restrictions is in the fight against cancer; researchers will often pinpoint lack of data availability as one of the biggest challenges faced in their research.

The idea is that this data could be brought together and examined so that it is more than the sum of its parts, but this data is often in ‘data silos’, and there is no communication between these groups. Furthermore, it is common to find the genetic make-up of cancer cells from a patient in one silo, and a completely separate and difficult to navigate database containing the patient’s information, symptoms, and response to treatment. These two pieces of information only have value when studied side by side, where there is the possibility they will reveal previously unknown causes of cancer, and help towards the development of more effective treatments.

Furthermore, this data availability problem is also harmful in other areas of medical research. In terms of rare diseases, it seems as though it would be a lot better for doctors to be able to easily access the research of others, and share their research. This could lead to a superior understanding of the disease, and would lead to an international body of research that would be helping researchers and patients from other sides of the world. Through responsible and effective sharing of data over, in effect, a ‘genomic internet’, data collaboration can help save lives.

Patients are also playing a role in the development of data sharing. For example, ROS1 is a gene that, when damaged, can give rise to cancer. Spurred on by a lack of progress with this disease, over 130 patients from 11 different countries came together and have approached a foundation to develop a clinical trial for this disease. It is likely that we will see a lot more patient-driven approaches in coming years, which promises to be beneficial for rare disease and cancer research.

There has recently been a call for a change in policy, which would enable data sharing that will eventually increase survival rates and improve the quality of life of cancer patients. Patient involvement is at the heart of this work, giving the public a vital role to play in making this a reality. Only with the support of the public can Big Data be used for such a good cause worldwide.

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Are the police force infringing on the privacy of the public?

data acquisition

Data acquisition is fast becoming a common and accepted part of large companies; collecting data and information in order to acquire knowledge about users, and therefore determine their interests, beliefs and often location. This can cause difficulties with privacy, and if there is a breach it can cause companies a lot of trouble. In recent years, the bodycam industry has been growing steadily, with particular usage increasing in the police force.

Police forces are equipping more and more officers with bodycams, to record events and permit more data acquisition. Furthermore, the latest AI technology is being developed and installed to make all the videos captured by the bodycams searchable for data acquisition.

Specifically, a new branch of AI called deep learning is being implemented by the police, and promises to take the internet by storm. Using sophisticated data acquisition technology, it can save time sifting through mountains of often useless information and focus on things that are actively important, pertinent and relevant to police investigations.

This increase in the use of bodycams is supposed to increase police accountability, but there are issues of privacy to consider. How do we stop them becoming nothing more than mobile CCTV cameras? The data acquired in this manner will have to be regulated in some way so as to avoid any privacy issues from arising. Exactly how police forces and other corporations will incorporate AI systems such as these into their everyday strategy remains to be seen, it seems that, in terms of data acquisition, these systems are very much part of the future.

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Should big data be regarded is the same way as a commodity or a national asset?

The value of datathe big data industry is increasing exponentially, and is expected to reach $100 billion by 2025. As a consequence, trillions of dollars of value will be added to other industries. The problem in his new age of digital economy is that each country has its own rules, in terms of data regulations. The current global system hasn’t adapted.

There are three aspects that have been identified as potentially problematic. Number one is having a right to privacy, number two is the absence of a legal framework suitable for the processing of big data, and the third is lack of governmental controls. Current infrastructure, as we have mentioned, is insufficient for this new digital age. A new digital platform provider may be required to keep up.

The solution is a common marketplace of shared, cross-industry digital platforms. And new training methods will certainly be needed in order to allow employees to properly and effectively deal with the inevitable challenges thrown up by managing big data.

The key to all of this will be investment in people, training and technology, so that the new digital economy can be managed properly. As the big data industry evolves, these issues will require solving, and new regulations will come into play.