A first look at SPSS Modeler v18.2
In this video Jarlath Quinn takes a first look at SPSS Modeler v18.2 and demonstrates some of the new functionality that’s included within this release.
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Expert insights: Major Lester, founder of SPSS UK talks about fifty years of SPSS
This year SPSS is 50 years old. Development started in 1965 by a team of political scientists, frustrated at how much time they had to spent on manual data cleaning before they could start their analysis. The first release was in 1968 and by the end of the 1960s SPSS was in use in over …
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Three questions to ask when reading articles about artificial intelligence
You may have noticed by now that there seem to be a couple of recurring themes in the plethora of articles and news programmes about artificial intelligence (AI). These themes can be summed up as a) “The dangers of AI” and b) “The limitations of AI”. Articles addressing the dangers of AI tend to focus …
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Thinking of using spreadsheets for advanced analytics? Think again.
When we’re talking to potential clients about advanced analytics we often ask them what tools they’re currently using. More often than not they say they’re using spreadsheets. Spreadsheets are one of the most widely used tools for statistical analysis and of course, most businesses couldn’t run without them. However, when it comes to advanced analytics …
Thinking of using spreadsheets for advanced analytics? Think again. Read More »
Expert insight – Paul Jackson, Head of Advanced Analytics, Bonamy Finch
Can you tell us a bit about yourself, your background and how you came to be where you are career-wise? I started my career in 2001 at Research International’s Marketing Science Centre, following a degree in Sociology and Social Policy. Back then I was working mainly on analysis of market research surveys. Over time I …
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Expert insight – John Gill, Head of Insight and Analytics, Betfred
Can you start off by telling us a bit about your background, and how you came to be working in the analytics field? I came to analytics via a somewhat circuitous route. My first degree was in psychology, then I did a postgraduate qualification in newspaper journalism. Obviously psychology is all about the science of …
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Expert insight – Nick Di Paulo, Lead Customer Researcher, Hyde Housing Group
Can you start off just by talking a little bit about your background and how you came to be working in analytics in the first place? Yes, I did research methods at university and was experienced at using spreadsheets and things like that, and that’s where I picked up SPSS, and then I got into …
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5 key trends affecting technical training provision in predictive analytics
I have been in the business of delivering software applications and solutions that have advanced and predictive analytics at their core, in one form or another, for last 25 years. In a recent conversation with colleagues we were discussing how the wider market has changed and, more specifically, how this has affected the way that …
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Expert insight – Karsten Shaw, Director of Analytics, Populus
Could you start off just by telling us a bit about your background and how you came to be working in the area that you’re working in with analytics? I studied statistics with economics undergraduate level, then I went on to do a Masters in statistics at the LSE part-time whilst I was working at …
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Expert insight – Matt Harrop, Head of Yield Management and Analytics, Ladbrokes Coral Ltd
What’s your background? How did you come to be working in analytics? I came from an accounting background and then moved into retail where I worked across a variety of teams in finance, marketing analytics and strategy for various different retailers. I then left that to join a consultancy working with loyalty card data. I …
Expert insight – Emma Brooker, Customer Insight Manager, L&Q
What’s your background? How did you come to be working in analytics? I suppose accidentally really. I studied politics at university, then I happened upon a short-term contract for a market research company doing data entry and progressed from there. I found the work interesting and enjoyed the projects I worked on. I moved to …
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7 things you need to know about key driver analysis (KDA)
In most businesses it’s not enough to simply be measuring outcomes like customer satisfaction, sales, customer churn rates, subscription renewals, customer loyalty, cancellation rates and so on. To gain competitive advantage you also need to know what’s driving those outcomes. Which aspects of the service you provide most influence how likely someone is to renew …
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The benefits of survey research and how online platforms can make the research process more efficient and effective
Surveys remain one of the most popular forms of market research, and consequently we regularly work with customers on large survey-based market research projects. Most commonly this is customer satisfaction surveys, and these can be one of the most valuable forms of data that a company has. We also have clients who conduct broader market …
Analytics predictions for 2018
As it is the end of the year I’ve decided to devote this blog post to some thoughts on where we see the analytics market going in 2018. Unlocking the analytics potential of unstructured data Enterprises are collecting ever greater quantities of unstructured data. A recent survey by Forbes showed that the number of organisations …
How to ensure advanced analytics gives you a concrete competitive advantage
Most companies these days are aware of the potential value that advanced analytics could offer them. Lots of people are talking the talk of advanced analytics, hiring data scientists and investing in sophisticated analytics technologies. But these things on their own aren’t going to give you the competitive advantage that you’re hoping for. It’s not …
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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 …
Thinking of hiring a data analyst? What skills should they have?
Many of our clients regularly hire new analysts and we’re often involved in discussions about what the core skills are that they should be looking for. Similarly, I often talk to people looking to build a career in analytics who want to know what skills they need to develop. The most skilled analysts are in …
Thinking of hiring a data analyst? What skills should they have? Read More »
Do I need SPSS Statistics or Modeler? How to choose the right product for your needs
We often talk to people who are unsure whether they need SPSS Statistics or whether SPSS Modeler might be more suited to their needs. In fact, it’s not always a clear cut choice as to which tool is more appropriate as it depends on the context in which the technology might be used. With that …
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Fear and loathing in machine learning
Over the past two years I’ve noticed a steady stream of articles in the mainstream press and business journals centred on the themes of a) the dangers of machine learning 1 2 or b) the limitations of machine learning 3 4. Many of these articles refer to incidents where machine learning initiatives have echoed and …
How alternative interfaces can help you get more out of R
Contemporary analytical platforms like SPSS and SAS represent the some of the earliest and yet longest-lived examples of proprietary software in the industry. When we think of the tectonic shifts the technology landscape has witnessed in last four decades, through the mainframe era, the rise of the PC, browser wars, the dotcom bubble, the smartphone …
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Why R can be hard to learn
Many of the analysts we speak to are being pushed over to R, primarily because it’s open source and therefore a free alternative to commercial data analytics packages for which the costs can sometimes run into tens of thousands of pounds (or more). However, even experienced analysts often find that getting to grips with R …
Six questions to ask before you opt for open source software
It’s not uncommon for people to say to us that they don’t understand why they should pay for industry standard analytics products like SPSS or SAS when there are strong open source alternatives freely available such as R. Indeed the development of R has really transformed the analytics marketplace in many ways. It’s tempting to …
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What’s the difference between business intelligence and predictive analytics?
It’s not uncommon to talk to potential clients who consider themselves to already be very much data-driven in the way that they operate. However it’s very rare to find a potential client that truly is exploiting the full potential of the data that they hold. That’s because companies often confuse business intelligence with predictive analytics, …
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How repeatable application templates will maximise the effectiveness of your first predictive analytics project
As we help our clients get up and running with the predictive analytics tools and skills they need, we see some trends emerging in terms of the kind of applications for which clients tend to use predictive analytics most commonly. These are what we call ‘repeatable application templates’. In my previous post I outlined the 4 …
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 …
Data science is everywhere, so why no data scientists to be seen? Read More »
The A-Z of analytics with IBM SPSS Modeler
A is for Automation Why bother trying out loads of modelling techniques to see which one works best when Modeler can do that for you? Modeler can test many permutations of the same algorithm and multiple instances of different methods before selecting the best performers according to a pre-specified criteria. Oh and it will also …
What is a chi-squared test and when would you use it?
An in depth guide to using the chi-squared test to determine statistical significance.
What is correlation and why is it useful?
What is correlation? Correlation is a term that we employ in everyday speech to denote things that appear to have a mutual relationship. In the world of analytics correlations are specific values that are calculated in order quantify the relationships between variables. This kind of analysis is powerful because it allows us measure the association between …
Supernode scripting in SPSS Modeler
This post describes how to use Python scripts to create and modify Modeler supernodes, and control the execution of the nodes within the supernode. If you’re after a basic overview of Python scripting in Modeler then this post may be of interest, and I’ve also written about how to write standalone Python scripts in Modeler here. As …
Four reasons why getting started with predictive analytics is simpler than you think
We spend a great deal of our time at Smart Vision helping our clients to establish the use of predictive analytics in their business. For many organisations, getting started with predictive analytics can feel like a real departure from more traditional and familiar areas of activity. That said, organisations in almost every industry sector are becoming …
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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, …
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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 …
Data science projects – what skills do you need and where can you get them from? Read More »
10 reasons why your organisation is ready for prescriptive analytics
Prescriptive analytics is a relatively recent development beyond the broader disciplines of predictive analytics and data science. In this blog post I want to explain a bit about what it is and discuss why I think many organisations are already on the road to using it, without even knowing it. Prescriptive analytics is the third …
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Nine tips for effective data mining
In my career I’ve seen many examples of successful and unsuccessful data mining projects. I’m often asked how clients can maximise the chances of their project being successful and, based on the many projects I’ve been involved with over the years, I think there are 9 things that really help. When these factors are in …
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 …
How can predictive analytics help retailers weather the economic storm?
In this blog post I’m going to suggest some ways in which predictive analytics can help retailers weather the economic storm they’re currently facing. The UK’s battered retail sector has been enduring an ongoing perfect storm following the financial crisis of 2007 / 2008. The government would like us to believe that things are much better …
How can predictive analytics help retailers weather the economic storm? Read More »
The widening analytics skills gap – how much of a problem is it?
It’s well known that there’s a growing skills gap in the area of analytics. As organisations are waking up to value contained within their data, so demand for statisticians, data scientists and analyst grows. It’s great that so many organisations are realising the power of analytics and the competitive edge that it can give them. But …
The widening analytics skills gap – how much of a problem is it? Read More »
Predictive analytics – five ways your business can benefit
When talking to companies who have yet to invest in predictive analytics I am often asked if I am sure that they will benefit. Will it be worth the time and effort involved in setting up a predictive analytics project? What kinds of benefits can they realistically expect? Are they large enough to reap the …
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What do your customers care about most? Using key driver analysis to find out.
After basic significance tests, T-tests, Z-tests and so on, key drivers analysis (KDA) is probably the second most popular statistically-based technique in market research. Given an outcome of interest a KDA gives us a measure of the relative importance of a set of attributes (potential drivers).Typical outcomes of interest in research are: Satisfaction – customer, employee etc. Purchase intent – how …
What do your customers care about most? Using key driver analysis to find out. Read More »
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 …
Writing a standalone Python script for Modeler
In my last post I gave a brief overview of the new Python-based scripting available in Modeler 16. In this post, I will cover Modeler 16 scripting in a little more detail. This assumes some familiarity with Python such as the Python module mechanism and exception handling. There are three types of script in Modeler: …
An overview of Python scripting in Modeler 16
Modeler scripts are used to automate the creation of streams, construction and configuration of nodes, stream execution and managing the execution results such as saving models to file or a content repository. A major new feature in Modeler 16 is the introduction of Python as the default scripting language. Python replaces the original bespoke language Modeler …
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 …
Is there a business case for the Chief Analytics Officer? Read More »
Using predictive analytics and the tax inspector’s nose to spot fraud
Organisations hold information, lots of it. Often it’s all over the place and sometimes its not acknowledged as being useful but there is always lots of data from customer interaction and transaction information to production line or stocking information. The trick is learning how to use past data to do better in the future. Organisations …
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Do you have to be a data scientist to do predictive analytics?
What is a data scientist? The predictive analytics field seems to love nothing more than giving a new name to an established concept. In my last post I argued that the concept of ‘big data’ itself is nothing new. Over the last few years I’ve seen more and more job ads recruiting ‘data scientists’ and I find myself rather unjustifiably irritated …
Do you have to be a data scientist to do predictive analytics? Read More »
Predictive analytics – what can you do with your results?
I talked in my last blog post about the confusion that often emerges around how much data is enough to effectively deploy predictive analytics. I argued that sample selection is much more important than sample size when it comes to ensuring accurate results. As an example I talked about two political polls from the 1936 …
Predictive analytics – what can you do with your results? Read More »
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 …
Predictive analytics – how much data do you really need? Read More »
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 …
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Why should charities invest in in-house predictive analytics?
Predictive analytics can really pay dividends for charities but I often find that such organisations are reluctant to invest in it or unsure of what value it can really bring. Smart Vision Europe has worked with quite a number of charities with the aim of helping them benefit from the power of predictive analytics. Over …
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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 …
