White papers

In this white paper we briefly describe the tenant satisfaction measures (TSMs) and tenant survey
requirements (TSRs). We then illustrate the reality of the data preparation and analysis that is involved so TSM can be properly implemented to enable the desired organisational behaviours and tenant
outcomes.

This white paper provides an overview of significance testing – one of the most commonly used but also most frequently misunderstood terms in statistics and data analysis.

Download this ebook to learn how DataRobot and Intel® work together so that enterprises can quickly train large datasets and build production-ready machine learning models, and more.

Our report, The Business Value of MLOps by Thomas Davenport, highlights some of the most impactful benefits of MLOps tools and processes for different types of organisations. It is based on interviews with MLOps user companies and several MLOps experts.

In this ebook, you’ll see how business leaders are leveraging AI to decrease machine downtime, improve demand forecasts, and accelerate supply chain logistics. You’ll discover that AI isn’t an intimidating technology, but rather a practical tool to grow your business and change the world.

Our ebook, AI in Customer Analytics: Tapping Your Data for Success, takes a deep dive into the many ways that companies can put their AI to work for better customer success.

In our 10 Keys to AI Success in 2021 ebook, we show how organisations are overcoming hurdles and realising the enormous rewards that AI can bring to any organisation.

If you’re familiar with programming languages such as Python or R then you can use them to extend the functionality of SPSS, automate more processes and make your jobs more stable and robust. This white paper tells you how to develop such IBM SPSS Statistics extension commands.

This free white paper presents some points you should consider if you use, or plan to use, a spreadsheet to perform statistical analysis. It also describes an alternative that in many cases will be more suitable.

This white paper discusses survey research by breaking it up into a seven step process — and clearly detailing how you maximize your efforts every step of the way. At each stage, it also shows how IBM SPSS predictive analytics technology can improve your results.

This paper considers the role service quality plays in predicting customer satisfaction and customer behavioral intentions in two types of service industries: lodging and retail banking.

This white paper presents a number of typical, real world examples of predictive analytics and shows how it can be used to address key business issues, with the aim of illustrating practical ways in which analytical capabilities can be deployed in a range of different organisations.

The purpose of this paper is to demonstrate the benefits of using R and SPSS together, rather than simply trying to go it alone with R. With SPSS software, R users get access to superior data management, a point-and-click interface, presentation-quality output and improved scalability.

Predictive analytics uses advanced algorithms to analyze donor data and deliver a 360-degree view of individual donors. Read this white paper to learn how to gain insight into the needs, preferences and behaviors of donors.

This white paper is designed to explain predictive analytics, followed by a look at how it can impact activity at the highest levels of institutional management. We provide examples of how predictive analytics has been used at a variety of institutions, including a review of its potential pitfalls and benefits.

This white paper provides an overview of geospatial analytics and why it is important to organisations seeking deeper insights about their business, customers or constituents.

Using the CRISP-DM framework can help make this process much simpler and give you a clear structure and set of criteria that you can use for your assessment. We have prepared a short guide explaining how best to use CRISP DM as a framework for evaluating data mining tools.

This whitepaper explores the practical applications of predictive analytics within retail and how it can be used to deliver a smarter shopping experience.