Statistics Canada uses machine learning models to process large volumes of data from diverse sources including retail scanner data, transportation records, housing information, financial institution data, administrative records from other government agencies, web-scraped content, international trade transactions, and satellite imagery. This system was developed to overcome limitations of traditional data processing approaches and reduce the reporting burden on survey respondents by leveraging existing big data sources.
The system affects how government employees access and analyze data for statistical purposes. By automating the processing of complex, large-scale datasets, it enables faster insights while maintaining data quality standards. The system is currently in production and primarily used by Government of Canada employees.
Please note: This system processes data that may include personal information. The machine learning approach allows Statistics Canada to extract value from administrative and transactional data sources while working to minimize respondent burden through reduced survey requirements.
