Big Data Innovation, Issue 16

Issue 16 | theinnovationenterprise.com

ISSUE 16 Big Data As A Catalyst For Healthcare Improvement

Plus | The Three Golden Rules When Selecting A Big Data System

LETTER FROM THE EDITOR Welcome to Issue 16 of Big Data Innovation.

Following the success of our Big Data San Jose events, we are pleased to bring you the latest issue of the magazine.

Much has happened in the world of Big Data in the last few years. We have seen companies that were non-existent 5 years ago now worth billions, and others cementing their position as industry leaders thanks to their adoption of a data driven approach.

One thing has stayed the same throughout, which is that choosing the correct system on which to work is as difficult now as it has ever been. Chris Towers takes time out from organizing the San Jose events to discuss the three golden rules that companies need to follow when making this choice.

As well as its use in big business, we are also investigating how Big Data is having an impact on other areas of our lives. We therefore take a look at how Big Data is affecting healthcare through Laura Denham and investigate whether data could help scientists do the impossible and predict earthquakes.

We also look at why, despite

companies now having more data than ever before, many are not operating at their full data driven potential.

DJ Patil has also been appointed as the Chief Data Scientist for the US government. Gabrielle Morse discusses his appointment, why it came at the perfect time and how the White House have made a great appointment in choosing DJ for this role.

Managing Editor: George Hill Assistant Editor: Simon Barton Art Director: Oliver Godwin-Brown Contributors:

After his recent well received articles in the magazine and on the channels website, we are also pleased to welcome Matthew Reaney back to write about Big Data and wearable technology at work.

Laura Denham Chris Towers Matthew Reaney Gabrielle Morse

As always, if you are interested in contributing or have any feedback on the magazine, please contact me at ghill@theiegroup.com

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George Hill Managing Editor

Are you are looking to put your products in front of key decision makers?

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CONTENTS

P3.

BIG DATA AS A CATALYST FOR HEALTHCARE IMPROVEMENT Laura Denham tells us why Big Data will spark a healthcare revolution.

4 COULD BIG DATA PREDICT EARTHQUAKES? We investigate if there is a way to successfully use data to give sufficient evacuation warning.

21 THE THREE GOLDEN RULES OF BIG DATA SYSTEMS Chris Towers gives us the lowdown on what you should look for in a Big Data solution.

7 BIG DATA AND WEARABLE TECH IN THE WORKPLACE Matthew Reaney talks us through the implications of Big Data and wearables at work.

14 HOW TO MAKE DATA ACTIONABLE As data is more available in our society, how can companies make sure they are using it well?

23 WHY DJ PATIL WAS A GOOD CHOICE We look at why choosing DJ Patil as Chief Data Scientist was a great move by the US Government.

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Big Data As A Catalyst For Healthcare Improvement Laura Denham | Organizer, Big Data Summit

The way that people are being diagnosed and treated for medical conditions is changing every day, with new techniques and new cures being discovered all the time.

Traditionally, this has been done through extensive theoretical work, then lab work is needed to prove the theory through trials and data.

This is changing though, and this data that medical personnel are trying to find is now acting as the catalyst for future innovations.

This has all become possible through the use of Big Data and analytics in the medical process, from creating huge databases, to an individual tracking themselves through wearable devices.

It is all amalgamating to create an environment where healthcare may be undertaking its biggest revolution in living memory.

With society’s capacity for data gathering, it has become possible for databases containing millions or even billions, of case studies outlining every possible scenario or treatment to

be created. It allows for predictive modelling, where treatment success can be established based on insight from previous cases, so if a person fits a specific profile (e.g 51 year old, ex-smoker, caucasian, regular exercise) it becomes possible to see what their best course of treatment would be. Predictive modelling can create a better insight into what could be achieved from this and any side effects that this could create.

This kind of modelling also helps to find new and unexpected cures, such as an anti-depressant helping

BIG DATA AS A CATALYST FOR HEALTHCARE IMPROVEMENT

to treat some forms of lung cancer. If a patient deviates from the modelled path, it is possible to identify the outlying choices they have made in order to establish what has caused the positive or negative anomaly. This creates new opportunities for finding cures or potential side effects within treatments.

Data is not everything in medicine though, as regardless of how many choices there are within treatments they need to be effectively trialled before they can be used on the general public.

Data can help in creating the most comprehensive possible studies and will bring together the best test subjects. This helps ito create a study that incorporates a huge amount of vital testing information, from looking at as many backgrounds and medical histories as possible, through

to the interference it may have with other drugs being used.

It goes further than simply treating diseases too. It is helping to both prevent and stop their spread during epidemics.

We have seen with the use of wearable technologies, that it becomes possible to track the routines of people, record their calorie intake and then process this with recommendations about making people healthier and therefore less likely to contract diseases. As this moves forward in the coming years, we are going to see the concept become even more important as we develop technologies that allow us to track even more personal data.

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to stop this spread. This was attempted during the recent spread of Ebola in Africa. Due to the severity of the situation, mobile providers made their data available, so that the movement of people and the spread of the disease could be evaluated and tracked to make decisions in order to minimize the spread moving forward.

Big Data is already having a massive impact on the way that we are looking at healthcare and medicine, moving forward this is only going to increase. The implications of a wider adoption of this is also profound, as the more we collect data in this way, the more use it could have in society.

With the spread of disease, data can also be used to track how it is spreading and this information can then be used

data that medical personnel are trying to find is now acting as the catalyst for future innovations

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HELP NEPAL

Could Big Data Predict Earthquakes?

George Hill | Editor

COULD BIG DATA PREDICT EARTHQUAKES?

We have all been shocked and saddened at the scale of death and devastation in Nepal after the 7.8 magnitude earthquake that is expected to have claimed 10,000 lives. The strength of the quake caused avalanches in the Himalayas, housing tumbled in the capital Kathmandu and strong tremors were even felt 900 miles away in India.

At times like this everybody asks whether there is more that could have been done to predict this earthquake earlier in order to help evacuate people and prevent so many casualties. It is generally accepted that there is no way to predict earthquakes accurately, but with the use of Big Data and technologies that can help us to analyze huge amounts of data, it is beginning to look like it is a distinct possibility in the future.

“

This is because earthquakes do not just happen. They

They may begin hundreds of miles underground, but they are not something that happens in isolation

may begin hundreds of miles underground, but they are not something that happens in isolation. The problem that those trying to predict earthquakes have, is that the changes are slight and can be explained by themselves, the cumulative effect of them give researchers a good indication that something is about to happen.

We have seen from previous quakes that there are some more obvious signs such as large numbers of animals waking from hibernation, strange clouds or changes in atmospheric conditions.

However, many of these happen very shortly before an earthquake, giving little time to take action or give warnings.

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A prime example of this in action was their February 22 prediction that there would be an earthquake of around 6.5 on the Indonesian Island of Sumatra, on March 3 the island was hit by a 6.4 earthquake.

Bringing several disparate data sources together, and using a Python based software running on an Apache server, it is possible for them to make accurate predictions of earthquakes where sensors are capable of picking up the information needed.

13,000 people die every year due to earthquakes

The ability to predict when these earthquakes are likely to happen should be seen as important work, not only because around 13,000 people die every year due to earthquakes, but also because $12 billion is also estimated to have been lost. If half of this loss could be invested in the technology needed to help predict these, then the chances of saving thousands of lives could be even greater.

The problem with this, as we have seen with the Nepal earthquake, is that the countries who have this kind of technology are often the richest, the ones who can afford this kind of infrastructure and the ones who are best prepared for earthquakes and will naturally have fewer deaths and disruption. Those with less money cannot afford this kind of new technology.

Terra Seismic are one of the companies who are trying to prove that earthquakes are predictable. They claim that through the use of satellite data they can predict major earthquakes anywhere in the world with a 90% accuracy.

We have seen that the importance of this could be huge from recent events and it should be a matter of international urgency to make sure that the opportunities to track this kind of information are in place.

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COULD BIG DATA PREDICT EARTHQUAKES?

IT SHOULD BE A MATTER OF INTERNATIONAL URGENCY TO MAKE SURE THAT THE OPPORTUNITIES TO TRACK THIS KIND OF INFORMATION ARE IN PLACE. Terra Seismic have already taken steps to make this a reality, having launched their own satellites to pick up this information rather than needing to rely on satellites owned by other companies or countries.

They have also made the information public with their website quakehunters. com where people can access information about earthquakes in their country.

A more powerful (and paid for)

version is also made available to companies and countries who are looking to minimize their risk in the future.

Through the marrying of data sources with in depth environmental information, it becomes possible to predict when and where earthquakes are likely to take place. The truth is that if we have more companies and countries working together the more accurate these predictions are likely to be.

It is not going to be possible to predict every single earthquake, but with the use of Big Data we are closer to than ever to being able to decrease the preventable deaths which are caused by them.

If you want to donate to t he Nepal Earthquake relief, you can do so at oxfam.org

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BIG DATA & WEARABLE TECH IN THE WORKPLACE Matthew Reaney | Founder and Director at Big Cloud

Big Data offers huge opportunities to improve both our professional and personal lives. It allows us to draw conclusions that we would not previously have been able to quantify and gives certainty to decision-making where there was previously doubt.

There is, however, one big restriction to the Big Data industry, and it is a fairly

You have to collect the data to work with in the first place

rudimentary one: you have to collect the data to work with in the first place. In industries like Healthcare, this is more than possible, and there will be massive steps forward once existing patient data can be properly analyzed. In the working environment, however, this is not always possible. How do you assess someone’s productivity if you cannot record what they are doing?

I’m writing this whilst watching rugby on TV, and the answer is staring me in the face.

The players wear electronic trackers on their backs, which measure their every move.

After the game, the data is downloaded and analyzed.

You can see who has run the most, their positioning and why certain moments in the game happened the way they did. You could say that this is television’s version of Wearable Tech, and it is facilitating innovation in all aspects of the game.

Is Wearable Tech the answer for compiling the data that business needs to take it to the next level? You can be certain that it will be used in many industries to measure various aspects, although the employees may view it as a step too far.

BIG DATA AND WEARABLE TECH IN THE WORKPLACE

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I can see a day where a CV might contain “activity” data Activity is the first battleground. Retail employees can be tracked around the store, logistics workers will be shown how to work more effectively, office workers might be “encouraged” to take a 1km walk every lunchtime. It may even get to the point where they can tell how many words you are typing per minute or how long you spend talking with people every day.

Health is the second battleground. Companies will be able to track your vital statistics, your eating habits and your general lifestyle, in general. I can see a day where a CV might contain “activity” data – companies want to hire active and energetic types.

Those who like to slump on the sofa in front of the TV every evening should watch out.

Activity is the first battleground

Analysis is the third battleground. Whenever Google Glass style tech becomes mainstream, built-in cameras will analyze body language and facial expressions, built-in microphones will listen to speaking patterns, and various conclusions will be made and relayed to the wearer. Does your negotiation opponent sound nervous?

Your Wearable Tech will tell you to a 99.9% probability, as it will have analysed millions of conversations, facial expressions and previous outcomes.

As the technology improves, the combination of Wearable Tech and Big Data in the workplace will bring insights that we didn’t previously believe possible.

The real question is whether employees will have any choice in the matter?

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How To Make Your Data Actionable Chris Towers | Head of Big Data, Innovation Enterprise

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HOW TO MAKE YOUR DATA ACTIONABLE

Data is a great thing. It can show us why somebody is doing something, where a particular delivery is or even how best to approach a particular problem.

Below are the key aspects that you need to concentrate on in order to make your data more actionable.

What it can’t do is make people use this insight to improve their decision making.

Using data is not a simple exercise, it is why data scientists are almost always well paid. If anybody could use complex data sets then we would not have the current skills gap.

There are numerous reports showing how the use of data analytics is spreading and how people are effectively using it to make key decisions within their organizations, but the reality is that more could be done with it. At the moment some people are not using it effectively, if at all.

So why is this? It seems like a no-brainer that if you have a wealth of data, that you would want to use it to help yourself.

However, whilst most people see this opportunity, for several reasons it is not being utilized effectively.

Having a clear mandate about how each team should be using their data will be key to the success of the overall data programme

Create Understanding

However, this is not true for using the data you already have to make decisions, it is just a case of understanding what it means and how it could affect you. The people who work outside of a direct data role are, in fact, in the best position for this. As they work within the actual business areas where data will have an impact, it means that they have the knowledge of how the numbers on screen could relate to a real business situation.

The success of this will come down to making sure that people are trained in how to use the data in front of them and how to look at it properly.

Make Time Giving employees time to use data effectively is going to be one of the key drivers in the success of any data programme.

If somebody is already

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working at their optimum, adding an extra element to what they need to do will undoubtedly decrease their effectiveness in other areas.

This could have a negative effect on both their quality of work, but most importantly on their mental approach to data.

Once negative connotations are associated with a particular action, they are hard to change. This means that making the most of their data comes down to giving them the time to do so. This could be through using effective time management or even bringing in one or two new team members to spread the workload to allow people to have time to effectively use the data available to them properly.

Have a Clear Mandate Having a clear mandate about how each team should be using their data will be key to the success of the overall data programme. Marketing will use a data set in a completely different way to finance and sales will use it in a totally different way to senior management. This means that the mandates given to each department need to be both clear and individually tailored.

Only saying ‘here is the data, use it’ is not enough and will never hit the heights that a clear mandate will allow for.

HOW TO MAKE YOUR DATA ACTIONABLE

Those who can make changes based on their data are the ones who are likely to have the most success in their roles Alongside this, the ROI of data needs to be viewed not as an individual aspect, but incorporated into the entire ROI of a department. This comes from not only looking at the short term returns, but the long term impacts. Data should never be viewed in isolation.

If this message is not clear and well communicated, it will be deemed as a short term experiment and there will be diminished drive to achieve the success that it could bring.

Even in the assessment stage, it is important not to allow people to coast through, but instead to make the most of what has been created for them. This needs to come from the most senior leaders in the company to show that it is truly a company wide change, not just a small experiment.

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better results for individuals.

Philosophizing about the merits of becoming more actionable with your data is great, but having somebody who can embody this success is going to be key to its overall success. It could come down to the most successful taking the time to show the rest how they are achieving these results. It may ultimately mean that the individual success of that person is slightly blunted, but will create a situation where many data champions are created.

Lead By Example

Senior Buy-In

Those who can make changes based on their data are the ones who are likely to have the most success in their roles.

It is therefore important to create champions, who are a clear example of what can be achieved through using data in a specific way.

There needs to be a clear message from senior management that ‘this is how we work now’.

Using these employees as an example will be a fantastic way to spread the idea that adopting data will provide

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The 3 Golden Rules For Choosing A Big Data Solution Chris Towers | Head of Big Data, Innovation Enterprise

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THE 3 GOLDEN RULES

It is now an established fact that those companies who have implemented a data strategy at an early stage are outperforming their competitors. It has been documented in some areas as a 2:1 improvement.

important for companies to remain informed of their options and which would be the best choice for them.

In fact those who haven’t, need to make it a business priority in the next 12 months otherwise they may find that their competitors are too far ahead to catch up.

Future Proof

The problem that many of these chasing companies have is that they are not aware of which system they should be using to start their data programmes. With hundreds on the market, from barebones, free options to multi-million pound packages, choosing the perfect system is hard.

With this huge variety and massive disparity in what could be invested, it is

With hundreds on the market, from barebones, free options to multimillion pound systems choosing the perfect system is hard BIG DATA INNOVATION

We believe there are three key points to look at when new systems are being considered.

Big Data and analytics are developing at a breakneck speed. People are constantly changing what can be done with data, right at this second we are seeing companies move from traditional Hadoop systems to Spark, which marks a move into the high speed data analysis that in-memory systems can bring.

The two questions regarding the technology you need is; what do you need now and what will you need in the future?

If you already hold a large amount of data and you want to analyze it fast, then you will need to have a super fast and expensive system. Ideally this would be in-memory capable, which requires high speed hardware and relatively complex systems straight away.

If the programme you envisage does not need this straight away, but may do in the future, then it is worth looking at a system that can be easily and cheaply upgraded.

If you need to spend a few thousand more on a system

that has the potential to add the capabilities you need in the future, rather than saving money initially on a system that can’t, you will ultimately save money.

Affordable and Useful A Big Data programme is only as good as the company it works within. This means that although it may seem progressive and positive to jump in with both feet and invest in the best system straight away, the reality is quite different.

The multi million dollar systems that are available now, are available simply because the companies who started with a single data scientist using one simple system have grown to the extent that they are needed.

Starting small and getting good ROI before investing more heavily is ultimately the way that businesses will get the most benefit from using Big Data initiatives. If a company jumps straight in and loses hundreds of thousands of dollars in the first couple of years without making any meaningful impact, then support for the programme will dissipate quickly.

Even with companies who would be considered as a similar size can have a huge variation in their data maturity and thus the requirements from their

THE 3 GOLDEN RULES

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The two questions regarding the technology you need is; what do you need now and what will you need in the future? systems. If a company is just starting out in data analysis, the chances are they will not need to have a system that can digest gigabytes of data in milliseconds. It is far more beneficial to invest in a system that can scale easily in the future, but doesn’t bankrupt your company in the present.

How Educated Are You? How much of the analysis of the data can be done in house? Do you have the skills to write algorithms or run complex queries? There are multiple systems that can cater to both the skilled and unskilled users, choosing the correct one is vital to the success of your business.

Essentially if you have an amazing data scientist already within the company, then data science could technically run for next to nothing. Aside from

A Big Data programme is only as good as the company it works within

their wage and a basic system, they can run a programme from Hadoop alone, meaning that there are no additional costs apart from storage.

can keep up without breaking the bank.

On the other hand, if there is a scarcity of these kind of skills within your company then solutions exist that will run these queries for you, mine your data and even help to gather and store it.

The second option is more expensive, but one that negates the problems of finding a qualified and skilled data scientist at a time when they are scarce and demand increasingly high wages.

Often these options allow for customization and exist on the cloud, meaning that finding the necessary space to house servers or equipment is gone.

Ultimately, the most important element to remember when choosing a Big Data solution is that there is no one size fits all. It is going to act like a golf club; you can buy the most expensive set, but if you give Rory McIlroy the most basic, he will still beat you. The best advice that we have is that scaling your systems must be at the heart of your choices, as your data usage will increase and you will need systems that

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Why The US Government Needed A Chief Data Scientist Gabrielle Morse | Organizer, Data Visualization Summit

Firstly, we would like to congratulate DJ Patil on his appointment as Chief Data Scientist for The US Government. We think that he was a great choice and will bring considerable experience and drive to the role.

Having somebody who is universally respected across the data community is the best way to start. DJ has been important in the creation of the data programmes for Linkedin and Facebook, two of the largest data holders in the world.

His appointment comes at an important time, a time when the government desperately needed to have an expert like him working with them.

In addition to this, he is widely credited (alongside Jeff Hammerbacher) with coining the term Data Science, so he is a great face to have for the first US Chief Data Scientist.

But why is this?

Data Crisis

Constantly Changing Landscape

We have seen the government take a huge hit on the way they deal with data from the Edward Snowden release.

Their reputation has been severely damaged and the only way to salvage it is through this appointment.

Not only does it take a face and name to help alleviate the crisis, but it also needs somebody who knows what is happening within the data community. This is vital and with DJ they have managed to bring in somebody who has

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their finger on the pulse of the latest trends and patterns within the industry.

Governments are often labeled as backwards and lacking the ability to be truly reactive. Hiring a Chief Data Scientist will potentially allow this to change.

This is due to them knowing when things can be changed and when they can’t. For instance, DJ will know exactly which data legislation will be most important for companies and which could wait.

With the speed in which the industry is currently moving, it is important that as new potential issues that need regulation arise, the government has somebody with the knowledge of the area who can put together workable rules that are fit for purpose. We have seen

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WHY THE US GOVERNMENT NEEDED A CHIEF DATA SCIENTIST

statements from world leaders that show how out of touch governments are, such as the idea from David Cameron that there should be no encryption on internet communications.

Having DJ advising on what should and shouldn’t be said and done is going to be important for the world’s most powerful government he will promote the industry without leaving it open to abuse.

Working With Data Companies As we have mentioned, DJ has worked with some of the biggest data holders in the world and even those who he hasn’t worked with directly will know about him and his work. This means that when potential changes are being discussed with companies, they know that they will be discussing it with somebody on a level playing field.

We often hear from civil servants that they are ultimately being managed by somebody who doesn’t know about the intricacies of what the industry requires.

For instance if we look to the UK, the Chancellor of the Exchequer, George Osborne, has no previous financial experience. Jeremy Hunt, has also been moved from the secretary of state for culture to the secretary of state for health, with no experience of either.

Having somebody who is from the industry representing the government gives far more credibility to any actions taken in the future. It comes at a time when governments are increasingly at loggerheads with data titans, so the timing could not be better.

Managing Expectations In a similar point to working with data companies, it is going to be important to have somebody in place who can mediate effectively between the two sides.

Private companies will always want to be self regulating, something that up until now has more or less been the case when it comes to data. The existing legislation is out-of-date and companies can exploit this, causing controversy amongst governments and creating animosity in the relationship between the two parties.

Having somebody who can act as an intermediary in this relationship is going to be one of the single biggest elements in the ongoing success of the state’s relationship with the companies who hold the most information on their citizens.

Governments want to make sure that their citizen’s data is safe whilst companies want to continue to experiment and use this information to create new things.

Having somebody on the inside who understands the needs of both, is respected by both and can speak both languages, is vital for this to remain successful and DJ Patil is perfectly placed for this task.

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