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Resource Library

Resource(s) Found: 6

October 29, 2012

Think Quarterly: The Data Issue

Author: Matt Brittin


At Google, we often think that speed is the forgotten ‘killer application’ – the ingredient that can differentiate winners from the rest. We know that the faster we deliver results, the more useful people find our service. But in a world of accelerating change, we all need time to reflect. Think Quarterly is a breathing space in a busy world. It’s a place to take time out and consider what’s happening and why it matters. Our first issue is dedicated to Data – amongst a morass of information, how can you find the magic metrics that will help transform your business? We hope that you find inspiration, insights, and more, in Think Quarterly.


Keywords: data, statistics, creativity, graphics, government, private investment, global development, corporate responsibility


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October 29, 2012

Best Practices in Data Mining Executive Summary

Author: Richard Boire, Paul Tyndall, Greg Carriere, Rob Champion


Canadian marketers have long used data mining as an important tool to help improve the effectiveness of their marketing campaigns, and over this period some organizations have emerged as industry thought leaders in data mining. Perhaps the survey’s first significant finding was that the process of defining and understanding the business problem at the core of every data mining project is not a straightforward, linear process. Instead, we found that gathering information and developing a suitable analytical approach defies a neat, sequential description. Instead, information requirements and analytical development overlap each other and typically require multiple iterations. In addition, we found that the longer an organization had been involved in data mining, the larger and broader the stakeholder group having influence in defining the problem and gathering the information. In fact, there is a strong correlation between the length of a firm’s data mining experience, and the size of the group involved in information gathering and exchange. In our survey, those indicating many sources of information outnumbered those with a more ad hoc approach (and quicker passage of this phase of the project) two-to-one. As a firm’s experience with data mining grows, so does the extent of its information gathering. However, there does not appear to be a direct correlation between the size of the organization and the extent of its formal processes. Prioritization of data mining projects is a significant issue for Canadian marketers, as resources are not infinite. Almost half of respondents indicated some formalized returnon- investment calculation or process is used to determine priorities, although there is significant variation in the use of formal metrics versus forecasts, estimates and assumptions. Firms with longer experience were more formal in their use of return-oninvestment calculations. Another large group of respondents (38 per cent) indicated that priorities are set in the context of meetings held to discuss the organization’s needs, with resolution of remaining issues escalated to a higher management level.


Keywords: data mining, return on investment, SAS


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October 29, 2012

Cluster Analysis

Author: unknown


Identifying groups of individuals or objects that are similar to each other but different from individuals in other groups can be intellectually satisfying, profitable, or sometimes both. Using your customer base, you may be able to form clusters of customers who have similar buying habits or demographics. You can take advantage of these similarities to target offers to subgroups that are most likely to be receptive to them. Based on scores on psychological inventories, you can cluster patients into subgroups that have similar response patterns.


Keywords: cluster analysis, discriminant analysis, Hierarchical Clustering, analysis, analytics


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October 29, 2012

Stability of the World Trade Web Over Time – An Extinction Analysis

Author: Nick Foti, Scott Pauls, and Daniel N. Rockmore


The World Trade Web (WTW) is a weighted network whose nodes correspond to countries with edge weights reflecting the value of imports and/or exports between coun tries. In this paper we introduce to the macroeconomic system the notion of extinction analysis, a technique often used in the analysis of ecosystems, for the purposes of investigating the robustness of this network. In particular, we subject the WTW to a principle set of in silico knockout experiments, akin to those carried out in the investigation of food webs, but suitably adapted to this macroeconomic network. Broadly, our experiments show that over time the WTW moves to a robust yet fragile conjuration where is it robust under random attacks but fragile under targeted attack. This change in stability is highly correlated with the connectance of the network. Moreover, there is evidence of sharp change in the structure of the network in the 1960s and 1970s, where the most measures of robustness rapidly increase before resuming a declining trend. We interpret these results in the context in the post-World War II move towards globalization. Globalization coincides with the sharp increase in robustness but also with a rise in those measures (e.g., connectance and trade imbalances) which correlate with decreases in robustness. The peak of robustness is reached after the onset of globalization policy but before the negative impacts are substantial. In this way we anticipate that knockout experiments like these can play an important role in the evaluation of the stability of economic systems.


Keywords: WTW, world trade, economic networks, network analysis, extiction experiments, data visualization


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October 29, 2012

Euro Area Banking, Sector Integration: Using Hierarchical Cluster Analysis Techniques

Author: Christoffer Kok Sørensen and Josep Maria Puigvert Gutiérrez


In this study we apply cluster analysis techniques, including a novel smoothing method, to detect some basic patterns and trends in the euro area banking sector in terms of the degree of homogeneity of countries. We find that in the period 1998-2004 the banking sectors in the euro area countries seem to have become somewhat more homogeneous, although the results are not unequivocal and considerable differences remain, leaving scope for further integration. In terms of clustering, the Western and Central European countries (like Germany, France, Belgium, and to some extent also the Netherlands, Austria and Italy) tend to cluster together, while Spain and Portugal and more recently also Greece usually are in the same distinct cluster. Ireland and Finland form separate clusters, but overall tend to be closer to the Western and Central European cluster.


Keywords: financial integration; cluster analysis; banking sector


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October 29, 2012

Data Mining – Best Practices

Author: Louise Francis


This paper covers topics regarding data mining best practices. Topics include: Data Mining for Management, Data Quality, Data augmentation, Data adjustment, Method/Software issues, Post deployment monitoring, and References & Resources.


Keywords: data mining, data mining best practices, analytics, CRISP-DM, EDA, CAS data management


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