How will the GDPR affect big data analytics?

With less than a year to go until it comes into effect, organisations are really starting to get to grips with what GDPR will mean in practice. We’ve talked to lots of customers who are concerned about the implications that GDPR might have for the way in which they collect and analyse customer data. Much of what constitutes ‘big data’ is personal data and the use of this kind of data definitely does have implications for data protection, privacy and individuals’ associated rights. And these rights are going to be strengthened by GDPR. So does this spell trouble for big […]

Which data science tools should you learn?

I’ve blogged several times now about different aspects of data science. A conversation I’ve been having more and more frequently now is about what tools people should learn if they’re hoping to develop a career in data science. Obviously there are many different factors to be taken into account here. You’ll want to think about whether there’s a tool that’s the standard in your particular industry. You’ll also want to consider whether you want to specialize in a particular area of data science and build a reputation as an expert in a range of related tools, or whether you’d prefer […]

Data science is everywhere, so why no data scientists to be seen?

Data science is everywhere at the moment. Nearly as everywhere as big data, but not quite. Books out there are making the concepts behind statistics and predictive analytics more and more accessible not only to those in business making decisions everyday but also to the average man or woman on the street.  Try Super Crunchers by Ian Ayres, Moneyball (the book  or the film which has the advantage of featuring Brad Pitt and therefore making the business of statistics much sexier than it has been),Freakonomics or the newer Superfreakonomics or pretty much anything by Malcolm Gladwell. All of these books have […]

Understanding what drives your net promoter score – how data science can help

The concept of the net promoter score was introduced to the world in Frederick Reichheld’s seminal Harvard Business Review article The One Number You Need to Grow in 2003. Reichheld’s research led him to believe that there was a deep and intrinsic link between profitable growth and customer loyalty. Two years of research revealed that, for most industries, the single best indicator of customer loyalty could be measured by asking people how likely they would be to recommend a particular company to a friend or relative. Reichheld and his colleagues at Bain and Company partnered with Satmetrix to develop a recommendation scale running […]

Data science projects – what skills do you need and where can you get them from?

Data science is on the rise. A couple of years back Harvard Business Review suggested that ‘data scientist’ is the sexiest job title of the twenty first century and the hype around data science shows no sign of abating. The term ‘data scientist’ itself was only coined in 2008 but since then the number of data science roles in organisations has grown exponentially, as the volume of data available for analysis also grows. But this presents a challenge for organisations – in such a new and fast-changing field how can they identify the skills they need, find appropriate people who have those skills, […]

A first look at IBM’s Watson Analytics

An analytical tool for the business user. It isn’t a new idea, more a nut that many of us have been trying to crack for years. Today, of course, this problem is more pressing than ever. There are more questions that can be answered with analytics, more data to analyse and fewer trained analysts to go round. And, as IBM rightly point out, analysts (and other data specialists) can be a bottleneck in the process. Where I’ve seen it work best in the past is generally when a software app, rather than a tool (like IBM/SPSS or SAS), has been designed […]

What makes for good data visualisation?

Data visualisation is a hot topic at the moment. And with good reason: a picture paints a thousand words … and the better ones can convey clearer meaning than a similar volume of numbers. There is also an ever-growing list of charts and infographics, both in the public domain and in research deliverables. They are not totally new of course as the Guardian newspaper demonstrated a while back with some historical examples. However, not all of today’s visualisations achieve their analytical/informational objectives. In order for data visualisation to be effective it is important that we keep sight of some long held principles about the […]

Is there a business case for the Chief Analytics Officer?

The past decade has seen huge growth in the practical use of data mining and analytics. Increasingly, analytics is being used not just to inform decision makers; it is being embedded into operational systems and processes. As analytics becomes increasingly business critical, I share a few thoughts on the question: is it time for the Chief Analytics Officer (CAO)? Contributions of a CAO Executive officer (CxO) roles are responsible for setting strategic objectives, making strategic decisions, leading employees to achieve objectives, directing day-to-day operations, executing change, and monitoring performance against the business strategy. A good starting point for defining the […]

Predictive analytics – how much data do you really need?

When I’m talking to prospective clients something I hear a lot is ‘but we don’t really have enough data to do any data mining’. It’s a common misconception that you need vast terabytes of data to be able to do anything meaningful in terms of analytics. In fact there are a number of similar misconceptions about data mining and predictive analytics that I want to talk about in this blog post. Myth one: it’s only worth mining huge datasets It’s certainly true that many data mining projects do involve working with massive datasets and these tend to be the ones […]

Predictive analytics: how small improvements can deliver big results

It never ceases to surprise me at the wide array of interesting and smart folks we have the privilege to meet through the course of our work at Smart Vision Europe. We are two months into 2014 and I have been checking back on my diary to make sure there are no loose ends. I’m encouraged by how busy we are and by the diverse range of businesses we’re talking to – so much so that I thought it was worth sharing. The purpose of sharing is not to showboat about how busy we are but to reinforce the point […]

Five myths about big data

Big data is everywhere at the moment. There’s a lot of talk about it, much of which presents big data as a problem to be solved rather than as an opportunity to be seized. There are many organisations that could be using big data for powerful predictive analytics but aren’t, because they’ve bought into one of the many myths about it that are in common circulation. Here are five of the big data myths that I come across most frequently in my work 1. Big data is new The terminology is new (and time will tell if it’s a term […]

Do you really need special software for predictive analytics?

When I’m talking to prospective clients, one of the questions I’m regularly asked is why they should invest in expensive predictive analytics software when they already have Excel. Excel has some useful features and for many organisations it can be a useful toe in the water of analytics but it’s really not built for the rigors of true predictive analytics. Organisations that stick to using Excel will never be able to truly reap the potential rewards that predictive analytics can offer. I’ve recently been working with a large B2B online publishing organisation and my experiences there illustrate this point perfectly. […]

Predictive analytics – art or science?

Predictive analytics uses statistical techniques and mathematical algorithms to analyse existing data and extrapolate it forward to predict what’s likely to happen in the future. Which customers are most likely to cancel their contracts? Which ad campaign will people most likely respond to? Which insurance claims are most likely to be fraudulent? On which assets should maintenance resources be most urgently focused? Most organisations understand how to use their existing data to understand what happened in the past – which campaigns were most successful, which customers left the organisation and so on – but predictive analytics takes this to the next […]

Big data analytics – when is enough enough?

There’s been a fair amount of discussion recently as to whether or not the whole big data analytics agenda has entered the ‘Trough of Disillusionment’ yet. The reality is that for many of us working in the advanced analytics arena, discussion of big data disappeared into the ‘Valley of Please-God-No-More’ some time ago. By that I mean it is in no way a dead horse, but good grief has it been thoroughly flogged. If you’re really unlucky, and have in fact spent the past couple of decades applying analytics to data sources of all shapes and sizes across all sorts […]