Employment and Social Development Canada (ESDC) requires a Data Conversion Specialist for the following tasks: • Outlining what needs to be classified. Determine the types of sensitive information such as personal records, financial data, or confidential correspondence—that require automated identification and protection. This step aligns with the Purview initiative’s goal of mapping "who owns what" in terms of data and authority. • Data Collection and Preparation • Gather representative samples of data from relevant systems. Clean and label this data to ensure it can be used to train the classifier effectively. Data preparation also involves removing any ambiguities or inconsistencies, in keeping with Purview’s emphasis on quality and clarity. • Select Classification Methodology • Decide on the approach for classification, which may include keyword detection, pattern recognition, or context-based analysis using AI models. This choice should reflect both technical capabilities and organizational requirements. • Train and Validate the Classifier • Use the prepared data to train the classifier, teaching it to recognize specific types of information based on defined criteria. Validate its performance by testing it on additional datasets, refining its accuracy, and ensuring it meets established standards for privacy and compliance. • Integrate with Purview Mapping and Governance | Contrat gouvernemental · CanPursue
Employment and Social Development Canada (ESDC) requires a Data Conversion Specialist for the following tasks: • Outlining what needs to be classified. Determine the types of sensitive information such as personal records, financial data, or confidential correspondence—that require automated identification and protection. This step aligns with the Purview initiative’s goal of mapping "who owns what" in terms of data and authority. • Data Collection and Preparation • Gather representative samples of data from relevant systems. Clean and label this data to ensure it can be used to train the classifier effectively. Data preparation also involves removing any ambiguities or inconsistencies, in keeping with Purview’s emphasis on quality and clarity. • Select Classification Methodology • Decide on the approach for classification, which may include keyword detection, pattern recognition, or context-based analysis using AI models. This choice should reflect both technical capabilities and organizational requirements. • Train and Validate the Classifier • Use the prepared data to train the classifier, teaching it to recognize specific types of information based on defined criteria. Validate its performance by testing it on additional datasets, refining its accuracy, and ensuring it meets established standards for privacy and compliance. • Integrate with Purview Mapping and Governance