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All our data is modelled to current year and is available at postal code level (typically 20-35 people per postal code), DA level (typically 400-700 people per DA or Dissemination Area), CT level, FSA level (typically 23,000 people per FSA), CSD, CD, CMA, and custom geographic levels.

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CASE STUDIES

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DATA

METHODOLOGIES

REFERENCES

 

CASE STUDIES

United Way 
Red Cross
AIG

PUBLICATIONS

Clustering and visualization of a high dimensional dataset. Manifold and University of Rzeszow have jointly developed an approach to cluster and visualize high dimensional datasets. The application to a diabetes dataset reveals important factors that can help patients improve manage their conditions and quality of life.

A Recommendation for Improvement of Quality of Life Using Contrast Patterns. Using Contrast Pattern Based Collaborative Behavior, we developed a recommendation system for people with high-risk of chronic diseases to identify the most effective behaviours and develop positive psychological attitudes to improve their conditions, and reduce healthcare cost. Sentiment analysis and opinion mining of emotion, affect, subjective experience and perception were performed to find factors that have a direct effect on people’s behaviours.
Diabetes
Census 2016 

METHODOLOGY

Creating and Updating Estimates and Projections
CanaCode Lifestyle Clusters
Notes on Census NHS for Updating Super Demographics
Color codes and definition of indexes

 

REFERENCES

Data Update

CanaCode Summary

CanaCode Major Lifestyles
CanaCode Niche Lifestyles
Standard Geography
Geographic Terms
Type of Census Division
Type of Census Sub-Division
Data Sources
Vividata Data Product Description
Numeris Data Product Description
Numeris Scale Conversion
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