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.
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.
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.
In this video Jarlath shows how to automatically produce a model that predicts customer’s recommendation scores based upon transactional and operational data.
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.
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.
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 …
An in depth guide to using the chi-squared test to determine statistical significance.
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 …
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, …
Understanding what drives your net promoter score – how data science can help 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.
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.
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
Learn how to exploit the power of the text analytics engine contained in SPSS Modeler Premium (video 2 of 3)
Learn how to exploit the power of the text mining engine contained in SPSS Modeler Premium (video 3 of 3).
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.
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.
You will learn how to: Summarise your data fields using simple descriptive statistics such as frequency counts, percentages, means, standard deviations and so on Run different kinds of descriptive statistics for different kinds of data Display your data visually via customisable tables Examine the relationships between variables using crosstabs Select different kinds of charts and …
Part two You will learn how to: Get your data ready for analysis in IBM SPSS Statistics Transform your data and create new fields e.g. creating an ‘age range’ field from date of birth information Ways in which you can transform different types of data
You will learn how to: Read data into IBM SPSS Statistics from other sources such as Excel files Format your data and tidying it up for effective analysis Save time by using previously formatted files as templates for your new IBM SPSS Statistics data file
While reading Jared Diamond’s excellent book on the rise and subsequent global dominance of Eurasian societies Guns, Germs and Steel, I was stopped in my tracks by his chapter on the evolution of technology entitled Necessity’s Mother. Diamond briskly demolishes the commonly-held view that necessity is the mother of invention. In fact he argues that many …
Why not now? The barriers to adopting true predictive analytics. Read More »
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 …
In my last blog post I talked about how it’s now possible to automate large parts of your predictive analytics projects, removing the need to get stuck into the complex statistics yourself. In this post I’ll suggest some ways to maximise the chances of your predictive analytics projects being successful. 1. Use a proven analytics …
6 ways to increase the value of your predictive analytics project Read More »
What do you think of when you hear phrases like predictive analytics, data mining or machine learning? For many people these terms sound suspiciously like ‘statistics on steroids’ and unfortunately, even in the more data-centric and numerate industries, that isn’t likely to elicit the most enthusiastic of responses. To be fair that’s hardly surprising, as …
Getting started with advanced analytics – advice for analytics virgins Read More »
