Merkle MENA Summit on the 19th February at Rixos Premium, Dubai. This event will have a large focus on use cases in region and networking. The day will consist of keynote talks, panels on data and digital topics supported by partners in region and then networking opportunities.
Please find the registration link here.
I recently joined a data science and advanced analytics company despite having no background in working with data. Within two months, I was staffing a stall at Data Summit – a two-day international conference held in Edinburgh on 21 and 22 March 2019 – talking to industry leaders about Internet of Things offerings.
While relishing such an exciting
transformation, I took a moment to rewind to my pre-data literate self, the one
with no knowledge of mathematics or statistics. Data has become quite the buzz
word – everyone is talking about the big data revolution, but who, apart from
data scientists, truly understands it?
Cambridge Analytica taps into deepest fears
To a data-illiterate person, I would
argue that this whole data revolution is something widely feared – it looks
like a fast-moving train heading your way. You are unsure of what it’s going to
do, how it’s going to impact you. The trouble is, you have no way of stopping
it, which makes it kind of scary. This feeling is not helped by recent
revelations about the likes of Cambridge Analytica, the company accused of
using big data to help Trump win the US election. Such narratives tell us that
data is dangerous and to be feared.
As luck would have it, the keynote
speaker at Data Summit was Chris Wylie, the
whistleblower in the Facebook-Cambridge Analytica scandal. From listening to
Chris, it’s clear that there is a massive consciousness within the data
community about the need for ethical boundaries and safeguards within this data
revolution. Indeed, two of the seven sessions at the Summit focused on Ethics,
Responsibility and Accountability.
AI and big data v ethics
Meanwhile, as part of our
sponsorship, we at Merkle Aquila brought together major players in the data
movement – Microsoft, Tableau, Data Lab and MBN – to debate whether automated
AI/ML is good for society. Recent developments in the Data Science world have
shown that the pressure to provide automated AI and ML tools is increasing. One
of the main talking points was accountability with automation. Who is
responsible for accidents with automated machines – the algorithm or its maker?
The ethical use of data raises questions that are being discussed by
scientists. These are the types of narratives that should be reaching
wider audiences as opposed to just the stories of data gone dangerous.
Into space and beyond
The world of data is not this alien
force that is only to be understood by a few. You don’t have to be a specialist
to understand the changes and implications brought by data science. This is
what was so brilliant about DataFest, in my opinion, it made data science
accessible to someone who, for example, had only just learned what segmentation
is. Not only is data science not to be feared but it is to be celebrated! From
Dr Maggie Aderen-Pocock’s inspiring talk on the use of data in space exploration
to robots improving safety in the workplace, my eyes were opened to the
potential for data to become the tool that leads to breakthroughs. As if that
wasn’t enough, it appears that I have somehow landed in an epicentre of this
data revolution. Edinburgh is one of the fastest-growing tech-hubs in Europe
and with Data Lab’smission to
maintain the data talent in Scotland… there are big things headed for this
So, my take-home points?
- The data revolution is not to be feared by the non-data literate. There are many emerging spaces where if you want to understand data, you can. There are data meetups and conferences designated to teach and discuss.
- DataFest has a wide variety of events, for people of all levels – data scientists and the data-illiterate. I would hope to see people of all backgrounds coming to attend these in the future.
And finally, there is no stopping this data train, so it’s best to hop on board.
Here are some upcoming events taking
place here at Merkle Aquila, click to find out more:
Scotland Data Science & Technology Meet-up
April 2 @ 6:30 pm – 9:00 pm
Bistro 210, 210 South Market Street
Aberdeen, AB11 5PQ
Neurons.AI Edinburgh Meetup: Robots and Autonomous Vehicles
April 4 @ 5:30 pm – 8:00 pm
Merkle Aquila, 7 Conference Square
Edinburgh, EH3 8AN United Kingdom
Is Data Science Free-to-Play or Pay-to-Win?
April 11 @ 6:30 pm – 9:00 pm
Merkle Aquila, 7 Conference Square
Edinburgh, EH3 8AN United Kingdom
Keep checking our events page for future listings.
Merkle Aquila is excited to announce that this year we will
be a Silver Sponsor of DataFest – a two-week festival of Data Innovation in
Scotland from the 11th to 22nd of March.
Now in its third year, DataFest will showcase Scotland’s
leading role in data science and artificial intelligence, whist offering platforms
to interact with local and international talent, industry, academia and data
enthusiasts. This year, the focus for the event is #DataTogether, which aligns
with Merkle Aquila’s attention to collaboration and community within the data
sphere. Thus, this event will be a fantastic opportunity to learn from and connect
with many of the leaders in the data innovation space in Scotland.
We will be involved in a variety of events across the week and
would encourage anyone who is interested to come join us. We will be hosting a free
Fringe event at our office on the 18th, we will be present all day
at Data Talent with a Merkle Aquila stand and will be conducting a breakout
session, amongst other exciting things, at the Summit on the 21st.
This is going to be a fantastic festival – with something
for everyone— and we highly recommend that everyone gets involved.
You can find out more about the festival at: https://www.datafest.global/.
For more information, you can reach us at:
Our website: https://www.aquilainsight.com/
See you there!
Tudor week is about to hit the Great British Bake Off tent. With only five bakers left, this theme will take over the eighth episode of the popular show. As it has never been done before the bakers may have a tough time trying to impress Paul and Mary with their XVI century creations.
Can Data Science help them?
As distant as they may seem, culinary arts and data science may have more in common than one may think. Using data visualisation techniques, scientists have been able to link common flavour compounds across world’s most famous cuisines, drawing a fantastic flavour map. This map shows how unique combinations of certain chemical compounds give great dishes its characteristic flavour, and how particular ingredients combine well with certain others.
Principles and Future of Food Pairing
If we can link ingredients that will taste good together, we can also raise the question of whether there are any hidden patterns or general rules that hide the secret of tasty dishes. This article that applies network analysis to flavour pairing offers some answers to this complicated matter. The answer is not that simple either! Apparently, Western cuisines show the tendency towards using ingredients closer to each other regarding flavour. On the opposite spectrum, Eastern cuisines try to surprise the palate by mixing ingredients a little bit further apart in the flavour map.
As you can guess, regional cuisines have developed their best dishes using whatever flavours were available in their region and period, with ingredients differing significantly across the globe. With the possibility of stochastic recipe creation, new horizons open for the culinary arts, one thinking that a great food pairing being held apart by geographical barriers is yet waiting to be discovered!
What can the bakers do?
But even if the bakers are not in a rush to algorithmically list their ingredients, this method that uses social network analysis to predict how successfully a recipe will be rated in recipe.com may help them when assessing which show-stopper will truly impress Paul and Mary. As Mel and Sue always say: on your marks, get set… BAKE!
Jamie Botham of Aquila Insight looks at the impact of monitoring and tracking performance data in sport, exercise and athletics.
Most of my friends and colleagues are aware and are likely getting bored of hearing, that I am training for a half marathon and (fingers crossed) a full marathon over the coming months.
So I thought what a great opportunity to tell everyone again…
Tracking exactly how long to Hold the Line Barry
Since starting training I have become hooked on apps such as Strava, MapMyRun and MyFitnessPal, tracking countless useful (or useless, depends on your view) pieces of information about how I’m doing.
One example is how long it takes to run ‘Hold the line Barry!’; a specific stretch of road near my house. I can then compare my time against the performance of people I’ve never met, for some much-needed encouragement next time I decide to head in Barry’s direction. I can also track my average pace, total distance covered each week, my elevation gain, split pace and so on. All of which I am convinced will help me run that bit faster on September 25th.
Using data to help set Olympic medal goals
Seeing all of this fitness data has got me thinking, in the wake of Team GB’s success at the Rio 2016 Olympics, which athletes are using data to help win that all-important Olympic Gold medal:
- Team GB’s Boxers – ‘iBoxer’ is a piece of software that has helped the boxing team analyse potential threats from opponents and areas of opportunity to get that all important competitive edge.
- Cycling – As bikes are becoming almost 100% efficient, there is renewed focus on data. USA cyclists use augmented reality glasses so they can receive real-time data collected from bike sensors, to help train harder than ever before.
- Rowing Team – Team GB are on the path to creating models that allow the team to see how previous winners performed at various ages of their career, how much they lift, their performance in the boat, to help with talent identification and tracking.
Easier to track data, training still harder
Using Strava and MapMyRun may not win me Olympic Gold it’s true, but what’s clear is that data and analysis can be applied to a whole host of different industries including sport and athletics with potentially huge benefits and rewards. Data might be what gets Team GB even more Golds at the next Olympics in Tokyo… and it might be what gets me over that finish line.
Have you ever asked yourself why you shop in the same shop? Why you bank with your bank? What is it that attracted you to this particular brand? Your answer won’t be an accurate way to understand the brand relationship, Aquila Insight discovers.
Perhaps better than asking ‘how did you hear about us?’ a brand should seek to understand what drives awareness, purchase and loyalty? Whether it is price, a debate on social media, a referring website, distance to the store, a search engine result, or receiving mail at the right moment. All are good reasons to give a brand a chance, even more so coming on the back of a friend’s recommendation.
When asked ‘How did you hear about us’, the brand can transport you back in time, to when you purchased or used their products and services for the first time. The company may have evolved with your needs, provided great customer service, with products that exceeded your expectations, at a price you consider appropriate, thus, increasing your trust, satisfaction and engagement with the brand. Suddenly, much to your surprise, you find yourself promoting the brand to a friend. That’s called word-of-mouth, and it’s free, but for a business, it requires time, talent and … some data.
It’s not enough to ask
The answer to ‘how did you hear about us?’ is incredibly useful for any businesses. If used well, the information could be the goose that lay the golden egg. The trouble is that you won’t get an accurate response when asking your customers directly (if they answer). People don’t remember. Whereas data never forgets.
Interrogate data to learn the truth
Fortunately, you can automatically capture and track the source of every web lead, by effectively planning and testing your offline campaigns, maintaining and looking after your CRM system and customers’ database. This allows your business to identify which marketing or advertising campaigns generate the most qualified leads. Even better, you can identify the most profitable customers and focus not only on what is driving acquisition but also loyalty and future revenue.
A smarter way to drive customer acquisition
At Aquila Insight, our team of data experts have experience in connecting online and offline interactions to plot the full path of a customer towards purchase, engagement and loyalty. These days, rather than ask customers how they found out about their brand, smart marketers use data to know exactly how their marketing spend is working.
The language of data analytics is easy to understand, as long as we all make an effort to speak to each other, says Aquila Insight.
Attending a training course along with a few colleagues, we were asked to close our eyes and think of a horse running. Five seconds later we were prompted to open our eyes, turn to our neighbour and tell them what the colour of our horse was.
It came as no surprise that people had different colours in mind. Even though we seemingly thought of the same thing – a horse – we differed in how we perceived the basics.
Different ways to view our world
I left thinking, does this apply to analytics? Analytics relies on maths and common sense. One plus one equals two, and there is no truth other than that.
Well, the reality is we work in multidisciplinary and multinational teams. As consultants, we engage with many different functions of a business: Marketing, Pricing and Digital to name but a few. A variety of disciplines and backgrounds can be nothing but positive for the success of a project. But we need to be extra cautious when we find ourselves in such teams and jointly design solutions.
Data is a language
Even the universal language of maths can be misinterpreted. For example, the word ‘model’ has a different meaning to a data scientist and a market research analyst. Similarly, local idioms may be perceived the wrong way or even ignored by a non-native speaker.
The solution is to collaborate and communicate openly and adjust our jargon depending on the audience. Both sides should make an effort to find common ground and use terminology that maps to the same concept.
Data shares common traits
Because at the end of the day, we are all thinking of a horse when we close our eyes, it’s just that the colour may not necessarily be the same.
Businesses are finding big data has become, well, bigger.
Cheaper and increasingly mobile communications coupled with fast high-bandwith broadband are now taken for granted.
Every kind of information imaginable is within easy reach as we switch onto a vast range of multi-screen and multi-sized technological devices.
It’s all got so big tackling the challenges of this commercial phenomenon can become overwhelming to say the least.
From a business perspective just how to harness data and gain an edge over the competition is proving a far from easy task.
Blue-chip organisations are spending fortunes, through cloud platforms or their own data centre, to take full advantage of how such information-based computing power can help shape their business operations.
They’ve realised as they attempt to capture, analyse and use information to serve customers, that a far greater accuracy in analysing key information leads to superior operational efficiencies and significant cost reductions.
However, perhaps it should be relabelled ‘wee data’ to give early career professionals and senior managers at small to medium-sized businesses more confidence to tackle what represents a myriad of deskbound and mobile applications.
Definitions are varied. Computer scientists Jonathan Stuart Ward and Adam Barker at the University of St Andrews prefer the MIT Technology Review version: “Big data is a term describing the storage and analysis of large and or complex data sets using a series of techniques.”
Critics describe it as a vague term and subject to hype but it has become something of an obsession with entrepreneurs and scientists, even governments. What it has unleashed on the business world is a veritable tsunami of computerised commercial intelligence from innumerable global sources.
Yet the commercial IT skills to cope are in severely short supply and this is having a profound effect on organisations in a wide variety of sectors.
They are faced with the fact traditional data processing applications are proving inadequate, especially when it comes to handling such advanced predictive analytics solutions that can extract vital extra value for a business.
“It’s a buzzword,” says Geoff Kell, managing director at Pufferfish. “It’s what you actually do with it that counts.”
In his company’s case it involves successfully handling data sets for clients as diverse as Audi, National Museum of Scotland and top band Coldplay.
Pufferfish designs and develops new platforms for displaying digital content outside the confines of the traditional flat screen.
Rather, its range of spherical display systems deliver 360 degree video simply and quickly across a range of commercial and artistic projects.
This has now extended to the PufferSphere 3D display, officially launched earlier this year at France’s Laval Virtual.
“Imagine being able to physicalise 3D digital objects in the real world, bringing them out of the screen and into the room, in a way that has been largely the realm of science fiction,” adds Kell. “That’s what we can now achieve.”
Gillian Docherty, CEO at The Data Lab, says: “We don’t have the word ‘big’ in our title,” as she points to the skills needed to exploit what is undoubtedly a data opportunity that are in great demand but in short supply.
A report by e-skills UK revealed that between 2012 and 2017 some 132,000 jobs will be have been created in what it describes as the “big data field”. This is where The Data Lab comes in.
Docherty told an EMC panel of experts in Edinburgh: “We are all about enabling new collaborations between industry, public sector and universities, driven by common interests in the exploitation of data science to help develop a local ecosystem by building a cohesive data science community.”
A move by Dell SecureWorks to establish its new European Security Operations Centre (SOC) in Scotland is also addressing the skills gap.
To date it has equipped its state-of-the-art facility with around 150 research, engineering and security operations technologists and is busy recruiting more.
Safe handling of big data lies at the heart of the leading global information security services provider’s work, but vice president and general manager Michael Cote warns: “The threat landscape is constantly changing and organisations are realising security is no longer an IT issue but a business issue.”
Cote’s outfit acts as an extension to the IT team for many clients, providing the very best security protection together with latest intelligence data to combat threats.
“Here in Scotland we already have a quality team in place and are continuing to grow that team with some of the very best talent available,” he says.
The hub is equipped to handle European, Middle East and Africa (EMEA) wide and global roles.
Deputy First Minister and Cabinet Secretary for Finance, Constitution and Economy John Swinney officiated at the opening: “The launch of this cutting-edge facility here in Edinburgh is a huge endorsement of all that Scotland has to offer in terms of talent, skills and infrastructure,” he said.
Another initiative is Scotland’s first dedicated software skills academy.
The aim of CodeClan is to build on the country’s vibrant digital sector but recognising the global shortage of skills, with forecasts that Scotland could offer up to 11,000 job opportunities annually rising by 2,000 a year.
CodeClan’s recruitment executive Rebecca Heaney says: “Digital is part of everyday life and we aim to fast-track access into shaping that world with a CodeClan qualification creating countless career paths and giving students skills they can take anywhere.”
It is based on academies like New York’s FlatIron, and Stackademy in Berlin, and is backed by Scottish Government start-up funding as part of a £6.6m cash boost to Scotland’s IT sector.
Courses lasting 10 weeks start in October aimed at producing a continuous wave of web and mobile software developers.
Euan Robertson, CTO at Aquila Insight data analytics, says: “With the data he had available Henry Ford infamously said you could have any colour of car you want as long as it is black. Such an impersonal approach is now long gone.”
Internet protocols are allowing new devices to be connected together almost daily.
“If we move or speak we generate data from the phones we use, TVs we watch, cars we drive, social conversations we have, games we playy, even the light bulbs we use,” says Robertson.
However, converting that activity into business value appears easier said than done.
Harvard Business Review warns turning insights from data analytics into competitive advantage requires changes many businesses may be incapable of making, and also that companies are not doing a good job with the information they already possess.
Simon Fielding-Turton, principal and founder of Aurea Consulting, says: “An avalanche of big data is threatening to engulf organisations so it’s vital to determine what use you want to make of the data, and also to be clear with clients, partners and staff about what is being gathered and to what end.
“Most organisations today already have a surfeit of information which they struggle to harness and this is only going to get more challenging.”
On the big data front something has got to give.