Contemporary analytical platforms like SPSS and SAS represent the some of the earliest and yet longest-lived examples of proprietary software […]
How alternative interfaces can help you get more out of R Read More »
Many of the analysts we speak to are being pushed over to R, primarily because it’s open source and therefore
Why R can be hard to learn Read More »
It’s not uncommon for people to say to us that they don’t understand why they should pay for industry standard
Six questions to ask before you opt for open source software Read More »
It’s not uncommon to talk to potential clients who consider themselves to already be very much data-driven in the way
What’s the difference between business intelligence and predictive analytics? Read More »
As we help our clients get up and running with the predictive analytics tools and skills they need, we see some
In part one of this video series Jarlath Quinn explains how operational analytics works, what data sources may be utilised and introduces the example case study that forms the basis of the subsequent videos in the series.
Predictive operational analytics part 1 Read More »
In part two of our predictive operational analytics video series, Jarlath Quinn introduces the IBM SPSS Modeler Software before showing how to explore the example data from the case study and carry out text analytics of engineer logs to categorise the information and create key fields for further analysis.
Predictive operational analytics part 2 – SPSS Modeler demo Read More »
In part 3 of this predictive operational analytics guide Jarlath uses the results from the previous analysis stage to show how to build and assess a predictive model that identifies whether or not a part replacement will be required during a maintenance visit.
Predictive operational analytics part 3 – predictive part replacement Read More »
In this final part of our predictive operational analytics video series Jarlath shows how we can use the predictive technology to go further by predicting the actual outcome of the visit including which part is likely to require replacement.
Predictive operational analytics part 4 – predicting task outcomes Read More »
Data science is everywhere at the moment. Nearly as everywhere as big data, but not quite. Books out there are
Data science is everywhere, so why no data scientists to be seen? Read More »
Jarlath provides a brief history of the concept of net promoter score before introducing the case study whereby Predictive Promoter was applied to data from the guests of a major hotel chain.
Predictive promoter part 1 – introducing predictive promoter scoring Read More »
In this video Jarlath shows how to automatically produce a model that predicts customer’s recommendation scores based upon transactional and operational data.
Predictive promoter part 2 – building a net promoter score predictive model Read More »
In this video Jarlath shows how easy it is to take a previously built model that has been generated based on known outcomes and apply it to customer data where the outcome is not known.
Predictive promoter part 3 – scoring with a net promoter score model Read More »
In this final part of our predictive promoter video series, Jarlath Quinn tackles the project’s most ambitious task: mining the open-ended guest comments to uncover important insights. Here you can discover how we can use text analytics to extract a series of concepts and sentiments from customer comments in order to categorise the guests’ responses.
Predictive promoter part 4 – text mining and conclusions Read More »
A is for Automation Why bother trying out loads of modelling techniques to see which one works best when Modeler
The A-Z of analytics with IBM SPSS Modeler Read More »
An in depth guide to using the chi-squared test to determine statistical significance.
What is a chi-squared test and when would you use it? Read More »
What is correlation? Correlation is a term that we employ in everyday speech to denote things that appear to have
What is correlation and why is it useful? Read More »
This post describes how to use Python scripts to create and modify Modeler supernodes, and control the execution of the
Supernode scripting in SPSS Modeler Read More »
We spend a great deal of our time at Smart Vision helping our clients to establish the use of predictive
Four reasons why getting started with predictive analytics is simpler than you think Read More »
The concept of the net promoter score was introduced to the world in Frederick Reichheld’s seminal Harvard Business Review article The
Understanding what drives your net promoter score – how data science can help Read More »
Data science is on the rise. A couple of years back Harvard Business Review suggested that ‘data scientist’ is the
Data science projects – what skills do you need and where can you get them from? Read More »
In this short video Jarlath Quinn demonstrates how to use the powerful simulation tools within IBM SPSS Modeler to perform What If analysis (also known as ‘Scenario Planning’). What if analysis allows business-focused analysts to go beyond simple predictive modelling to evaluate the impact of different choices and scenarios on predicted outcomes.
What If Analysis using IBM SPSS Modeler Premium Read More »
This video shows you how organisations with substantial capital assets can use IBM SPSS Modeler to predict when asset failure is most likely. Predicting asset failure can prevent problems before they happen and enables organisations to save money, reduce asset downtime and increase efficiency.
Predicting asset failure using IBM SPSS Modeler Read More »
This video shows you how you can analyse customer comments or indeed any free-text data, using the power of the text analytics engine contained in SPSS Modeler Premium
Text analytics using IBM SPSS Modeler Premium (part one) Read More »
Learn how to exploit the power of the text analytics engine contained in SPSS Modeler Premium (video 2 of 3)
Text analytics with IBM SPSS Modeler Premium (part two) Read More »
Learn how to exploit the power of the text mining engine contained in SPSS Modeler Premium (video 3 of 3).
Text mining with IBM SPSS Modeler Premium (part three) Read More »
This short video shows how you can perform a simple affinity analysis using IBM SPSS Modeler. Affinity analysis can be used to understand interconnected relationships between key factors. For example, in retail it can be used to perform basket analysis, whereby retailers can identify which products are most commonly purchased together by customers in a single transaction or over a given period time.
Affinity analysis made easy Read More »
If you are considering making your first foray into predictive analytics or are interested in seeing the automated capabilities of IBM’s flagship analytical platform, this video will demonstrate the power and ease of building a predictive model in SPSS Modeler.
Building a predictive model in SPSS Modeler Read More »
You will learn how to: Summarise your data fields using simple descriptive statistics such as frequency counts, percentages, means, standard
Unlocking IBM SPSS Statistics (part 3) Read More »
Part two You will learn how to: Get your data ready for analysis in IBM SPSS Statistics Transform your data
Unlocking IBM SPSS Statistics (part two) Read More »
You will learn how to: Read data into IBM SPSS Statistics from other sources such as Excel files Format your data
Unlocking IBM SPSS Statistics (part one) Read More »
Prescriptive analytics is a relatively recent development beyond the broader disciplines of predictive analytics and data science. In this blog
10 reasons why your organisation is ready for prescriptive analytics Read More »
In my career I’ve seen many examples of successful and unsuccessful data mining projects. I’m often asked how clients can
Nine tips for effective data mining Read More »
An analytical tool for the business user. It isn’t a new idea, more a nut that many of us have
A first look at IBM’s Watson Analytics Read More »
In this blog post I’m going to suggest some ways in which predictive analytics can help retailers weather the economic
How can predictive analytics help retailers weather the economic storm? Read More »
It’s well known that there’s a growing skills gap in the area of analytics. As organisations are waking up to
The widening analytics skills gap – how much of a problem is it? Read More »
When talking to companies who have yet to invest in predictive analytics I am often asked if I am sure
Predictive analytics – five ways your business can benefit Read More »
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
What do your customers care about most? Using key driver analysis to find out. Read More »
Data visualisation is a hot topic at the moment. And with good reason: a picture paints a thousand words … and the
What makes for good data visualisation? Read More »
In my last post I gave a brief overview of the new Python-based scripting available in Modeler 16. In this
Writing a standalone Python script for Modeler Read More »
Modeler scripts are used to automate the creation of streams, construction and configuration of nodes, stream execution and managing the
An overview of Python scripting in Modeler 16 Read More »
The past decade has seen huge growth in the practical use of data mining and analytics. Increasingly, analytics is being
Is there a business case for the Chief Analytics Officer? Read More »
Organisations hold information, lots of it. Often it’s all over the place and sometimes its not acknowledged as being useful
Using predictive analytics and the tax inspector’s nose to spot fraud Read More »
What is a data scientist? The predictive analytics field seems to love nothing more than giving a new name to an established
Do you have to be a data scientist to do predictive analytics? Read More »
I talked in my last blog post about the confusion that often emerges around how much data is enough to
Predictive analytics – what can you do with your results? Read More »
When I’m talking to prospective clients something I hear a lot is ‘but we don’t really have enough data to
Predictive analytics – how much data do you really need? Read More »
It never ceases to surprise me at the wide array of interesting and smart folks we have the privilege to
Predictive analytics: how small improvements can deliver big results Read More »
Predictive analytics can really pay dividends for charities but I often find that such organisations are reluctant to invest in
Why should charities invest in in-house predictive analytics? Read More »
Big data is everywhere at the moment. There’s a lot of talk about it, much of which presents big data
Five myths about big data Read More »
Moving beyond RFM analysis to create truly data-driven customer segments RFM stands for recency, frequency, monetary value and is a
Assessing the value of your customers Read More »
